at-0311

Buy high, sell higher: relative strength system p. 48

Capturing “alpha” with momentum and contrarian strategies p. 30

international etF trading system p. 24

intraday stock-index futures setup p. 18

Oil back in the spotlight p. 16

$4.95 Printed in the U.S.A. www.activetradermag.com

• TRADING STRATEGIES FOR THE FINANCIAL MARKETS •

March 2011 • Volume 12, No. 3

®

tale of a hedge fund p. 58

Prepping for tax season p. 62

March 2011

Active Trader

ETF rotation

Byline

4 www.activetradermag.com•March2011•ACTIVE TRADER

COnTenTS

8 Contributors

10 Opening Trades Trends and events

movingthemarkets.

68 Stocks Snapshot Volume, volatility, and momentumstatisticsforstocks.

69 ETF Snapshot Volume, volatility, and

momentum statistics for ETFs.

70 Futures Snapshot Volume, volatility, and

momentum statistics for futures.

71 New Products & Services

71 Key Concepts

72 Trader’s Bookshelf

73 Upcoming Events

73 Advertising Index

74 Trader’s Marketplace

76 Trading Calendar

March2011•Volume12,No.3

TradiNgSTraTegieSforThefiNaNcialMarkeTS

Trading Strategies18 Time filtering scalp trades analyzinghour-by-hourperformanceofanintraday

setuphighlightsoptimaltradingtimes.

ByactiveTraderStaff

24 Trading international stock-index eTFs with relative strength

rotatingintothestrongestexchange-tradedfundsrepresentingdifferentcountries’stockmarketsshows

thepotentialtoboostreturnsandreducevolatility.

ByJaykaeppel

30 Active alpha investing for the market’s “new normal” inamarketenvironmentwithpotentiallylittleto

offer,asimpleeTfsectorrotationapproachshows

theabilitytooutperform.

By Prof. Davide Accomazzo and Rosario Rivadeneyra

38 execution and management of iron condors Timingthecomponentspreadsofthisfour-option

positioncanhelpavoiditsdrawbacksandmaximize

itspotential.

BygeoffryWong

in every issue

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Contents

Advanced Concepts42 Base metals and Chinese monetary policy Are sliding prices for base metals a

currency trade in disguise?

By Howard L. Simons

Trading System Lab48 Buy high, sell higher Arelativestrengthstocksystembeatsthe

marketbyawidemarginintesting.

ByRobertSucherJr.

Trading Basics54 Order up: 2011 Don’tgetyourOCOs,SCOs,andMOCs

mixedup.Thisprimeronordertypes

willmakesenseofthealphabetsoup.

By Active Trader Staff

The Face of Trading 57 Nurturing patience Learningtowaitforthetradesthatmatter.


Active Trader Interview58 A new hedge-fund world Inpart2ofourinterviewwithLars

Kroijer,theformerhedgefundmanager

discussesthefutureofhedgefundsandthe

alternative to “alternative” investments for

individualtraderslookingforanedge.


The Business of Trading 62 Handling IRS notices and exams IfyoufindyourselfconfrontedwithanIRSnotice,

learnhowtoproceedtoavoidtaxtrouble.

By Robert A. Green, CPA

The Economy

66 U.S. economic briefing Updates on economic numbers and

themarket’sreactiontothem.

Trade Diary80 Goinglongafterabearishweek

inthecrudeoilmarket.

Byline

COnTRiBUTORS

Howard Simons is president of Rosewood Trading Inc. and a strategist for Bianco Research. He writes and speaks frequently on a wide range of econom-ic and financial market issues.

Geoffry Wong is a private trader using the technical analysis tools and strategies he has developed over many years. Previously, he was a propriety options and derivative trader for Goldman Sachs, where he was involved in all aspects of trading in options on futures, equities, and derivative products. Wong also assisted in research for the firm and used in-house technical and fundamental analysis to select various option strategies. At Goldman Sachs, he developed option-pricing models to find anomalies in mispriced options, and developed trading practices to profit from those anomalies. He can be contacted at [email protected] or (917) 951-0364.

Davide Accomazzo has been trading professionally since 1996. From 1996-1997 he was a Euro-convertible bond/international equities sales trader with Jefferies Group, where he covered many international funds. In 1998 he left to trade his own capital, and in 1999 he started Kensington Offshore Limited, a speculative hedge fund that outperformed the S&P 500 during the 1999-2002 boom and bust economic cycles. In 2001 he launched Kensing-ton Capital Management LLC, a commodity trading advisor that focused on trading options on futures and currency futures. In 2004 Accomazzo was recruited by UBS Wealth Management USA to manage the portfolios of high net worth investors. In 2005, Accomazzo co-founded Cervino Capital Man-agement LLC as managing director, head of trading and is the sole principal trader for the company’s managed futures programs.

Rosario Rivadeneyra is co-founder and managing partner at Quant Invest-ments, an investment advisory firm based in Monterrey, Mexico. She holds a Master’s in finance from EGADE, a leading business school in Mexico, and studied at the Graziadio School of Business and Management of Pepperdine University. She is a contemporary dancer and performing arts supporter.

Jay Kaeppel is the author of Seasonal Stock Market Trends (Wiley, 2009) which was selected as one of the “Top 10 Trading Books for 2009” in the Hirsch Organization’s 2010 Stock Trader’s Almanac. A former commodity trading advisor, Kaeppel is an independent trader and trading strategist with Optionetics. He writes a syndicated weekly column called “Kaeppel’s Corner” for Optionetics.com. His previous books include The Four Biggest Mistakes in Option Trading (Trader’s Library 1998), The Four Biggest Mistakes in Futures Trading (Trader’s Library 2000), and The Option Traders Guide to Probability, Volatility and Timing (Wiley 2002).

Robert A. Green, CPA, is CEO of Green & Company (GreenTraderTax.com), a CPA firm focused on traders and investment-management businesses. Green is also founder and CEO of the GreenTraderTax Traders Association. He is the author of The Tax Guide for Traders (McGraw-Hill, 2004) and Green’s 2010 Trader Tax Guide. GreenTrader provides tax preparation, accounting, consulting, entity, and retirement-plan formation services; IRS/state tax exam representation; and trade-accounting software. For more information or to participate in free conference calls, visit www.greencompany.com.

Robert Sucher holds a M.S.E.E. in signal processing from C.S.U. North-ridge (1992). After working 12 years in the military aircraft industry, he moved to the Canary Islands (Spain) where he began actively trading stocks and futures in 1999. In 2002, he started an ongoing journey with Wealth-Lab.com, assisting customers with trading tools.

Editor-in-chief: Mark Etzkorn

[email protected]

Managing editor: Molly Goad

[email protected]

Associate editor: Rakesh Sharma

[email protected]

Contributing editor: Howard L. Simons

Contributing writers: Marc Chandler, Keith Schap, Robert A. Green, Chris Peters

Editorial assistant and webmaster: Kesha Green

President: Phil Dorman

[email protected]

Publisher, ad sales: Bob Dorman

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Volume12,Issue3Active TraderispublishedmonthlybyTechInfo,Inc.,POBox487,LakeZurich,IL60047-0487.Copyright©2011TechInfo,Inc.Allrightsreserved.Informationinthispublicationmaynotbestoredorreproducedinanyformwithoutwrittenpermissionfromthepublisher.Annualsubscriptionrateis$59.40.

TheinformationinActive Trader magazineisintendedforeducationalpurposesonly.Itisnotmeanttorecommend,promoteorinanywayimplytheeffectivenessofanytradingsystem,strategyorapproach.Traders are advised to do their own research and testing to determine thevalidityofatradingidea.Tradingandinvestingcarryahighlevelofrisk.Pastperformancedoesnotguaranteefutureresults.

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TRADING Strategies


U.S. stocks follow through into new year2009-2010inthetop10percentoftwo-yeargainssince1960.

Opening TRADES

A classic “holiday” rally closed 2010 near the year’s high, capping one of the strongest two-year runs for stocks in the past 50 years.

Although it was a double-digit year for equities overall, small-cap and technol-ogy stocks led the broad market by a wide margin: The S&P 500 (SPX) gained 12.79 percent in 2010, but the market-leading Russell 2000 (RUT) doubled that return, rallying 25.41 percent. The Nasdaq 100 (NDX) wasn’t too far behind with a 19.24-percent gain.

But despite the S&P’s more modest 2010 gain, its 39.23-percent return for 2009-2010 was the ninth largest two-year rally since 1960. And that gain pales in compari-son to the index’s 84-percent gain from the March 2009 financial-panic low to the end of 2010.

The bullishness carried into the first full week of trading in 2011: All U.S. indices were in the black through Jan. 7, with the Nasdaq 100 (+2.65 percent) leading the pack by a relatively wide margin, while the Russell 2000 eked out a marginal gain (+0.51 percent).

The rally dampened market volatility in December nearly to its lowest levels of the year. The CBOE volatility index (VIX) fell be-low 15.50, the lowest it has been since April 2010, which was the last time the market sold off sharply. The declining volume trend evident since the fourth quarter of 2009 re-mained intact through the end of 2010, with the first week of January 2011 producing a not-uncommon spike in trading activity. ◆

U.S. INDICES ON THE YEAR, 2010

12/31/09 12/31/10 +/-

Russell2000 625 784 25.41%

Nasdaq100 1,860 2,218 19.24%

S&P500 1,115 1,258 12.79%

Dow 10,428 11,578 11.02%

U.S. INDICES, FIRST WEEK OF 2011

12/31/10 1/7/11 +/-

Nasdaq100 2,218 2,277 2.65%

S&P500 1,258 1,272 1.10%

Dow 11,578 11,675 0.84%

Russell2000 784 788 0.51%

S&P 500 LARGEST TWO-YEAR GAINS, 1960-2010Years Open High Low Close One-year Two-year

1997-98 1163.62 1244.92 1136.88 1229.23 26.67% 65.95%

1995-96 757.02 761.75 716.69 740.74 20.26% 61.29%

1996-97 955.4 986.25 924.92 970.43 31.01% 57.56%

1975-76 102.49 107.46 102.12 107.46 19.15% 56.81%

1998-99 1388.91 1473.1 1387.38 1469.25 19.53% 51.40%

1985-86 249.05 254.86 241.27 242.16 14.62% 44.80%

1988-89 350.62 354.1 339.62 353.39 27.25% 43.03%

1979-80 137.21 140.66 125.32 135.75 25.76% 41.24%

2009-10 1186.6 1262.58 1186.6 1257.64 12.78% 39.23%

2003-04 1173.83 1217.33 1173.76 1211.92 8.99% 37.75%

Opening Trades


T he financial crisis of 2008 ravaged markets and rattled the financial system to its core. The Dow Jones Indus-trial Average (DJIA) fell 33.84 percent that year, its worst showing since 1932, early in the Great Depression, and

trillions of dollars of shareholder wealth evaporated. The crisis also exposed long-ignored loopholes in financial regulations that enabled Wall Street to run amok, resulting in widespread outcry for regulatory reform.

Congress passed the Dodd-Frank Act into law in June 2010 in an attempt to address U.S. regulatory shortcomings, especially the lack of accountability in over-the-counter (OTC) derivatives

trading, such as the now-infamous credit default swap transac-tions that helped destroy Lehman Brothers and other investment banks. Although specific applications are still being drafted, the new rules — from proposed restrictions on proprietary trading to increased margin requirements and suitability standards — are likely to impact institutional firms and banks more than indi-vidual investors. However, there is some concern the changes will result in higher operating costs that firms will ultimately pass on to end customers — that is, average investors and traders. Overall, there is still a big gap between what the law mandates and how regulatory agencies and financial firms will satisfy the new requirements.

“You don’t have the playbook as yet,” says Ken Grant, risk pro-fessional and president of Risk Resources LLC. “I would say 20 to 25 percent of the law’s impact is known while 70 to 75 percent of its impact is unknown.”

Educating the individual investorIn addition to Wall Street chicanery with OTC derivatives, a widely held view is that widespread financial illiteracy also contributed to the financial crisis. In response, Dodd-Frank ap-proved the creation of two new agencies (the Financial Stability Oversight Council and the Consumer Financial Protection Bu-reau) to protect retail investors, along with an Office of Financial Literacy to educate investors (see Figure 1).

It has also mandated increased communication between brokerages and their customers. For example, brokers are now required to disclose short-sale activities once a month to custom-ers, including information relating to compensation or financial incentives for each sale. In addition, brokers must provide cus-tomers with the option to not have their securities used in short sales.

“The biggest area of impact for individual investors is that they will now have access to a constant stream of continued commu-nication from companies,” says Charles Rotblut, vice president of the American Association of Individual Investors (AAII) in Chi-cago. “It is important for [investors] to know that they are active business owners if they invest in a company’s stock and active lenders if they invest in bonds.”

However, Rotblut sounds a note of caution regarding the practical effect of the new information that will be available to investors. “As we have seen in the case of dieting, reinforcing a message or increased communication does not always work,” he

Industry adjusts to Dodd-FrankAmoretransparent,stablemarketplace?Higherfeesandfewerchoices?Brokeragefirms

andanalystsdiscusstheimplicationsofDodd-Frankforindividualtradersandinvestors.

By RakEsh shaRma

FIguRE 1: NEW REguLaTIONs, NEW WaTChDOgs

Dodd-Frankmandatednewgovernmentagenciesintendedto protect and educate public investors.

CONSUMER FINANCIAL PROTECTION BUREAU

• Independent head and budget•Autonomous rule-writing

National consumer complainthotline;OfficeofFinancialLiteracy

Banksandcreditunionswithassetsover$10billion

Totheregulation-making process

Creates Regulates

Contributes

FINANCIAL STABILITY OVERSIGHT COUNCIL

•Chaired by the Treasury secretary•Consists of 10 federal financial regulators, an

independent member, and five nonvoting members

Emerging risks in thefinancialsystem

Rulesforcapital,leverage, liquidity, and risk management

Nonbankfinancialcompanies

Identifies Recommends Regulates

ACTIVE TRADER •March2011•www.activetradermag.com 13

says. “Similarly, increased communication might not always result in an educated investor.”

Proprietary trading Section 619 of Dodd-Frank has special implications for invest-ment firms. The section, also known as the Volcker rule, named after former Fed Chairman Paul Volcker, deals with proprietary trading (in-house trading with firm, rather than customer, funds). Proprietary trading desks have become huge sources of profits for large banks and trading firms, an increasing number of which have turned to high-frequency trading strategies that now drive as much as three-quarters of the volume in the U.S. stock market.

According to its advocates, the upside of proprietary trading is that it adds liquidity to the market. The downside, according to detractors, is that it increases leverage and risk at these firms, thus endangering the financial system as a whole. According to the Roosevelt Institute, a New York-based policy research insti-tute, Wall Street firms suffered an estimated $230 billion in pro-prietary trading losses by April 2008. The Volcker rule prohibits banks from engaging in proprietary trading. But, the new law provides regulators with a 15-month observation period before deciding how to enforce it. In the meantime, banks are reportedly exploring ways to reorganize their proprietary trading groups, including spinning them off into “hedge funds,” to skirt the law.

James Heinzman, managing director of securities solutions at Actimize, a New York-based risk and compliance solutions firm, and former managing director of Bear Sterns, says there are two schools of thought on this issue. According to the first school, the ban on proprietary trading will lead to greater transparency and a more level playing field.

The second school believes the ban could lead to loss of liquid-ity. “There will be a reduction in the pools of liquidity avail-able to investors, especially in the case of retail investors,” says Heinzman. Less liquidity will mean greater price volatility and spreads. “In the extreme, retail investors could end up paying higher prices and be forced to accept more risk as well,” he says.

Rotblut, however, thinks limits to proprietary trading are unlikely to affect individual investors. “Hedge funds or large investment firms have more exposure to stocks with large market volumes, such as CISCO,” he says. “A reduction in proprietary trading should not impact their liquidity.”

Grant says the ban will be positive for individual investors. “It takes away access to information and, consequently, the proxim-ity advantage that institutional firms enjoy,” he says.

Broker obligations: a question of standardsDodd-Frank also calls for uniform “fiduciary standards” for brokers and investment advisors, which represent the obligation to act in a client’s best interests. Although it has not defined the standards, the law empowers the SEC to do so.

Brokers are currently governed by the so-called “suitability obligation” to advise their clients. This obligation contrasts with the “fiduciary duty” that governs investment advisors, because the former incorporates factors such as client age, net worth, and time horizon into investment advice.

Imposition of a more rigorous standard could impact a large cross section of traders and investors, according to some industry participants.

“We have an awful lot of clients who know what they want to do in terms of trade,” Christopher Nagy, managing director at TD Ameritrade, says. “Depending on how fiduciary duty is defined, it might affect client actions.” For example, in the case of a completely self-directed investor, he says “the firm would have to check his or her liquidity and other information, which might result in delays and other problems for the investor.”

According to Heinzman, introduction of a uniform standard might also affect asset classes available to investors; certain products may be deemed too risky or complex for certain market participants.

“Whole classes of less sophisticated and less affluent investors may no longer have access to the products and services offered by large global investment banks,” he says. “The result will be less investment opportunities available to retail investors.”

The key to making the new standards work, Heinzman says, is to “harmonize the rules between investment advisors and brokers.”

Increase in brokerage costs?The new law could end up having a significant impact on brokerage costs, for two reasons. The first cause is the “Meeks amendment,” which approves an increase in the quote fees stock exchanges charge to brokers. According to Nagy, this could have

Brokersmustgivecustomersthe

optiontowithholdtheirsecurities

fromshort-salelending.

continued on p. 14

Opening Trades


BaRCLay TRaDINg gROuP’s maNagED FuTuREs PERFORmaNCE as OF NOv. 30Top 10 traders managing more than $10 million

Trading advisorNovember

return 2010 YTD

return

$ under mgmt.

(millions)

1. Beneficentia(Essentia) 21.74% 11.11% 104.2

2. GlobalInvest.Mgmt(HighFrequency) 20.70% 105.50% 16.4

3. TacticalInvest.Mgmt.(Inst'l) 9.44% 53.09% 60.0

4. 24FXManagementLtd 7.89% 60.64% 49.5

5. Astmax(AMCI) 6.53% 4.21% 10.1

6. eStatsFundsMgmt(Delev) 5.16% 7.74% 12.0

7. AquilaCapitalConcepts(Pharos) 4.93% -17.02% 19.5

8. InterkraftEnergyFund 4.89% -1.22% 14.5

9. AquilaCapitalConcepts(PharosEvol.) 4.72% -12.54% 12.1

10. AISFuturesManagement(3X-6X) 4.45% 24.91% 80.5

Top 10 Traders managing less than $10 million and at least $1 million

1. LevelIIIManagement 10.50% 89.45% 1.9

2. eStatsFundsMgmt(Composite) 10.40% 14.64% 6.0

3. GenuineTrading(USAIndex) 10.36% 88.13% 6.5

4. BrockCap'lMgmt(HeartlandAg) 10.20% -14.58% 2.6

5. Sagacity(HedgeFX100) 9.78% 3.85% 1.0

6. CenturionFxLtd(6X) 7.26% 66.06% 3.5

7. SteinInvest.Mgmt(TradingEdge) 6.78% 27.63% 2.1

8. GTAGroup(FXTrading) 6.54% 21.80% 1.9

9. MisfitFinancialGroup(Delta) 5.63% 7.74% 2.5

10. VermillionAssetMgmt(Indigo) 5.51% 7.42% 9.7

Basedonestimatesofthecompositeofallaccountsorthefullyfundedsubsetmethod.Doesnotreflecttheperformanceofanysingleaccount.PASTRESULTSARENOTNECESSARILYINDICATIVEOFFUTUREPERFORMANCE.Source:BarclayHedge(www.barclayhedge.com)

a major impact on TD Ameritrade’s fee structure. “It has the effect of increasing fee structures significantly and impacts my ability to charge commissions,” he says.

Second, the new regulations could result in higher IT costs for financial firms. David Thetford, securities compliance analyst at compliance and technology solutions firm Wolters Kluwer Finan-cial Services, says the fiduciary duty will place an added burden on brokerages and dealers. “Implementation of the fiduciary standard will result in extra labor and more conversations about regulation,” he says. “This will likely result in higher costs for the firms.”

Whether those costs are then passed onto traders remains to be seen.

The bottom lineAlthough much about Dodd-Frank remains uncertain, what is clear is the law heralds a new era of increased market regula-tion.

“We let the genie out of the bottle,” says Terence Dolan, chief executive officer at Benjamin & Jerold, a New York-based boutique financial services firm. “The question before us now is how to get it back into the bottle.”

For retail investors, industry regulation is the most impor-tant part of the act.

“The key for individual inves-tors is that the SEC has the ability to enforce regulations and continues to adapt as the fi-nancial industry evolves,” AAII’s Rotblut says.

According to Ameritrade’s Nagy, a balanced approach to regulation is important. “Too much regulation is a bad thing, and too little regulation is also a bad thing,” he says. “The pieces of regulation that don’t work need to be repealed.” For example, he says, strict compli-ance with certain sections of the Sarbanes-Oxley law (which requires all publicly traded companies to submit an annual

report of the effectiveness of their internal accounting controls to the SEC) had the unintended consequence of creating a high bar-rier to entry for some firms.

There may be other unforeseen downsides to increased regula-tion. “The risk of companies moving businesses offshore to less-restrictive regimes is a very real risk,” Heinzman says.

It might take years to ensure clarity and impact of the new law, according to Risk Resources’ Grant. That said, he is pretty confi-dent Wall Street will come out of it OK — despite complaints of being overburdened with regulation. “Ultimately, Wall Street will benefit because they have the resources to turn whatever happens to their relative advantage,” he says. ◆

Opening Trades


I n early January crude oil (CL) pushed to its highest level since 2008 — the highest, in fact, since the market was in the process of collapsing from its stratospheric July 2008 high above $147 per barrel on its way to a February 2009 low

below $34 (Figure 1). As of Jan. 3, crude oil had nearly tripled in price from that nadir, reaching $92.58 after staging a choppy 30-percent rally off its August 2010 swing low (Figure 2).

Long the most actively traded and widely watched commod-ity market, crude mostly disappeared from the headlines after its implosion, only gradually recapturing ink from the mainstream press as it sustained prices above $75 in early 2010, and espe-cially after it tested its late-May low and clawed its way back above $90 — the final round-number threshold in the path of the psychologically loaded $100 level.

However, the oil market has arguably entered a new paradigm since 2008, and the recent rally has thus far failed to engender the same level of hype that accompanied the market’s first run to $100.

Underlying market dynamicsOn the fundamental side, analysts point to several reasons for the recent bump in prices. Dominant among them is positive news about the global economy, according to Chris Lafakis, economist at Moody’s Analytics. While economic growth has been slow, especially in the U.S., it has remained positive for many months, and there has been an absence of bad news to reverse the trend.

“Recent positive macroeconomic data has increased investor expectations that the global economy will recover strength in 2011,” he says.

As economies recover, of course, oil demand increases. “Due to an increase in demand from China and other emerging

economies, and the prospects of a U.S. economic recovery, we are returning to a constrained supply environment,” says Allen Good, equity analyst at Morningstar. “That means demand may outstrip supply.”

However, few analysts seem to view the market as overheated the way it was two to three years ago, and supply concerns are

generally muted.The current situation is “funda-

mentally different from what hap-pened in 2008,” according to Lafakis says, who says tremendous demand from China, which was buying oil and oil products in preparation for the Beijing Olympics, was the main reason for the 2008 surge. “The strong demand caught investors off guard, and they panicked, sending oil futures higher,” he says.

The market is less likely to be squeezed today. For example, Lafakis says OPEC currently has excess capacity of 4 million barrels per day that can be brought online if oil prices increase to $100.

Some analysts think oil will hur-dle $100 in the coming months, but few see the potential for a extended run beyond that threshold. In an in-vestment note released in December 2010, Goldman Sachs economists described a “structural bull market”

FIgUre 1: 50-PerCeNT CrUDe reBOUND

AtthebeginningofJanuary,crudeoiltopped$90forthefirsttimeinmorethantwoyearsandrecoveredmorethanhalfofitsmassive2008-2009sell-off.(Pricesshownareweeklyestimatesanddonotreflectdailypriceextremes.)Source:U.S.EnergyInformationAssociation(http://tonto.eia.doe.gov)

Oil flirts with triple digits in new yearAlthoughthreeyearsagotheideaof$100crudeborderedontheapocalyptic,fewmarket

watchersseemtoexpectanotheroilgusher,evenaspricesagainedgetowardthecenturymark.

By ACTIve TrADer STAFF


FIgUre 2: THe reCeNT rALLy

AsofJan.3,Marchcrudeoilfutureshadtopped$92,havingralliedapproximately30-percentfromlateAugust2010.Source:TradeStation

that would lift oil prices back to $100 per barrel.Although he says oil could hit $100 this year, Lafakis does not

believe it is a sustainable level.“A price of $100 would trigger an increase in oil production,”

he notes. Another question is whether the increase in oil prices could

derail the still-fragile economic recovery. Lafakis doesn’t think so. “A $1 per barrel increase results in a $1 billion increase in consumers’ annual energy costs,” he says. He says it would take an approximately $20 increase to appreciably slow GDP growth.

Oil stocksRising crude prices have, of course, buoyed the prices of oil-related stocks. “Stocks of oil companies are probably pricing in slightly higher right now,” Good says.

However, the rise in prices may not result in a bonanza across the board. “Oil producers, whether they are [sovereigns] such as OPEC countries or companies such as Exxon or Shell, stand to benefit the most from increased oil prices,” says Lafakis.

Refineries, on the other hand, are less likely to profit from higher-priced crude.

“Refiners face long-term head-winds,” Good says. “In the short term, their margins may have peaked. Now, profits depend on further accel-eration in growth and demand.”

Price actionAlthough crude oil’s behavior over the past 18 months bears little re-semblance to its 2007-2008 run, the market has regained more than half the ground it lost in the subsequent sell-off. (However, the 50-percent rebound represents a technical hurdle in and of itself, as Fibonacci enthusi-asts will likely sell into this antici-pated resistance level.)

The lack of momentum in the current uptrend also plays against the participation of trend-following commodity trading advisors and hedge funds that played a big part in the 2007-2008 crude bubble (and the hedge-fund universe has been particularly decimated since then). While the initial rebound off the 2009 low was robust, price gains have been more haphazard since mid-2009. Every significant push past a $10 threshold — into the $60s, $70s, then the $80s, has been relatively short-lived and was typically followed by stagnation, and then a $5 to $10 retracement that nipped momentum in the bud just as it seemed the market might mount an extended rally.

Nonetheless, there is little way to predict what might happen if the market does manage to stay above $100 for an extended pe-riod. Markets, like the people who comprise them, have relatively short memories. ◆

By Active trAder StAff

trAdiNG Strategies


time filtering scalp trades

Analyzinghour-by-hourperformanceofanintradaysetuphighlightsoptimaltradingtimes.

trAdiNG Strategies

continuedonp.20

t here are several old saws about the best and worst times to put on positions during the trading day: avoid the open and close (because they’re too volatile), avoid the middle of the day (because it’s not volatile enough), and so on.

The intraday volatility of the stock market does follow, on average, a very predictable intraday profile: The beginning and the end of the day are, in fact, the most active periods, as traders react to early news and establish positions at the open (or get out of bad positions held overnight) and then unwind many trades before the closing bell. The middle of the day — lunchtime in New York and Chicago, as often noted — features much less movement and volume because the early news has been absorbed and most positions have been established; the market often con-solidates, or jerks back and forth, until activity picks up again in the last hour or two of the trading session.

For intraday traders, the implications are fairly obvious: If you’re looking for directional moves and follow-through, avoid the “dead-zone” in the middle of the day and focus on those peri-ods when the market is most likely to move. (Conversely, traders looking to take contrary positions may choose to sell resistance and buy support during midday ranges.)

Let’s look at a basic intraday buy setup, applied on the five-minute time frame, and see what we can learn from analyzing its behavior during different periods of the day.

the pattern: three up and three downWe will start with the simplest of patterns: three five-minute bars with successively higher lows followed by three bars with

successively lower lows. This pattern can be expressed by two simple rules:

1. The lows of the five-minute bars three, four, and five bars ago are above the lows of their respective preceding bars.

2. The lows of the current bar and the two preceding bars are below the lows of their respective preceding bars.

As formulas, these rules are:

1. Low[5] > Low[6] and2. Low[4] > Low[5] and3. Low[3] > Low[4] and4. Low[2] < Low[3] and5. Low[1] < Low[2] and6. Low[0] < Low[1]

(Note: A version of the pattern that requires the most recent five-minute bar’s low [Low[0]] to be a certain amount below the previous low will be discussed at the end of the article.) Basically, these rules simply identify situations in which there has been upward pressure for at least three five-minute bars (notice that it can be more than three), followed by three bars of downward price action (lower lows).

This representative pattern was unoptimized and was selected only because of its simplicity and relative frequency. It was origi-nally analyzed in five-minute data in the S&P 500 ETF (SPY),

Trading Strategies

but here it will be tested on five-minute bars in the E-Mini Dow futures (YM) from Feb. 1, 2010 through July 16, 2010 — a total of 9,412 price bars, or the equivalent of more than 37 years of daily price bars. Only regular-session data was used, 8:30 a.m. to 3:15 p.m. CT. Figure 1 shows a few examples of the pattern.

Raw pattern performanceThe pattern formed 135 times in the 118 days in the analysis period — just a little more than once a day, on average. This is far too infrequently for a genuine scalping pattern, but it nonetheless provides enough samples to do a relatively thorough analysis.

Table 1 shows the E-Mini Dow’s performance in the first 12 (five-minute) bars following the pattern, using an entry one point (tick) below the low of the second-to-last bar of the pattern (i.e., entering as soon as the final bar makes a lower low). Gains and

losses were calculated based on exiting at the closes of the follow-ing 12 bars. Figure 2 graphs the average and median post-pattern performance along with the market’s average and median one- to 12-bar returns for the entire analysis period. While the pattern’s returns are extremely modest, they do outperform the even more static performance of the market overall. (The analysis period as a whole was flat, dominated by an early uptrend, then a volatile sell-off highlighted by the May 2010 flash crash. The E-Mini Dow had 68 up days, 48 down days, and gained a total of 41 points between Feb. 1 and July 16, 2010.)

Figure 3 (p. 22) looks beyond the closing gains to compare the pattern’s median largest up moves (LUMs) to the largest down moves (LDMs). The LUM is the biggest gain from the pattern entry to the highs of each of the following 12 bars, while the LDM is the biggest loss from entry to the lows of each subsequent

bar (the chart shows the absolute value of the LDMs to make comparison easier). It’s appar-ent the pattern was followed by notably more up movement than down movement in the first few bars (along with the highest win-ning percentages, as shown in Table 1), but this edge quickly eroded until, by bar 12, the LUM/LDM ratio had fallen to 1.00. There was a somewhat stable zone in the middle: Upside movement held a small but steady edge from bar 5 to bar 9, and the median LUM ranged from 17 to 21 points during this window.

Now let’s see how the pattern behaved at different times of the day.

Time of day: Frequency and winning percentageFigure 4 (p. 22) shows the distribution of pattern occurrences throughout the trading day. There’s the expected activity early in the session, but after a brief lull, another uptick occurs from around 10:10 to 10:50 CT. The period from 11 a.m. to a little after 1 p.m. is relatively quiet, except for an anomalous high reading at the 12:35 bar. A small surge in activity from 1:15 to 1:30 is followed by a


Table 1: POST-PaTTeRN PeRFORMaNCeBar 1 2 3 4 5 6 7 8 9 10 11 12

Avg 2.3 1.34 2.63 1.58 0.23 0.77 1.29 2.33 2.45 1.07 1.50 2.67

Med 3 2 2 1 1 1 2 2 5 3 5 5

Min -59 -61 -71 -65 -66 -66 -60 -63 -81 -88 -85 -90

Max 33 47 49 58 72 65 64 79 97 98 92 92

Sum 308 177 331 196 28 93 152 272 284 124 171 302

Win% 62.96% 54.81% 54.81% 51.85% 54.07% 53.33% 53.33% 53.33% 54.81% 53.33% 51.85% 53.33%

Thepattern’sgainsweremodest,withthebiggestrelative(perbar)edgeoccurringinthefirstfewbars—especiallybar1,whichwastheonlybartohaveawinningpercentagehigherthan60percent.

FiguRe 1: TRaDe SigNalS

Thepattern,whichtriggeredapproximatelyonceaday,consistsofthreehigherlowsfollowedbythreelowerlowsonthefive-minutetimeframe.

brief respite before a final high-activity period from 2:15 to the day’s end.

With the exception of the relatively high frequency mid-morning period (10:10-10:50) period, the profile essentially adheres to the common pattern of activity clustering toward the beginning and end of the trading day, with a lull in the middle.

Now look at Figure 5 (p. 23), which shows the winning percentages associated with pat-terns occurring at different times of the day. One of the most interesting things about the results is that, rather than indicating certain time periods are uniformly better than others, it shows particular time periods are associated with a tendency toward success or failure ei-ther in the first bars after the pattern or in the later bars. For example, patterns that occurred

continued on p. 22

ACTIVE TRADER • March 2011 • www.activetradermag.com 21

Figure 2: PATTerN PerFOrMANCe

The pattern had modest, somewhat haphazard performance (blue lines), although it was more bullish than the market’s overall performance (reddish lines)

Trading Strategies

in the 1:05 to 2 p.m. period (red) tended to have lower winning percentages in bars 1 to 4, but from bar 5 forward, the odds of a gain were 60 percent or higher, and in three cases above 70 percent. Patterns that were triggered in the 8:45 to 9 a.m. period (medium blue) had winning percentages near 65 percent for bars 1 and 2, but that probability dropped off sharply at bar 4 and never again climbed above 50 percent. Conversely, the patterns in the 12:05 to 1 p.m. category had low winning percentages

(almost all below 50 percent) through bar 6, but these jumped notably (55-60 percent) from bar 7 forward.

Overall, the most consistent time periods were the 10:05 to 11 a.m. (light purple) and 2:05 to 3:15 (dark blue) periods. With a few exceptions (e.g., bar 1 for the 2:05-3:15 patterns), trades that were triggered during these periods had win rates at or above 60 percent, with the 2:05-3:15 patterns particularly strong from bar 8 to bar 12.

The consistently worst period was, in fact, 11:05 a.m. to 12 p.m. (light blue), which had a winning percent below 50 percent for nine of the 12 bars. If nothing else, it appears that avoiding trades during this period would be beneficial to overall performance.

Keeping time on your sideAlthough intraday volatility patterns are fairly stable, it is worthwhile to research how a specific pattern or strategy per-forms at different times of the day. The results shown here, while still preliminary, indicate that not only are some times more advantageous than others, but different times of the day may require using different holding periods or trade horizons. In this case, the same entry signal was more prof-itable with a short holding period (one to four bars) early in the trading session, but late in the trading session a longer holding period (6 to 12 bars) was associated with a higher winning percentage. They also point to the potential for good results — and a relatively high trade-signal frequency — in a period (roughly 10-11 a.m. CT) that is typically thought of as a uneventful time of the day.

One final bit of analysis: We analyzed a modified version of the pattern on more recent data (Aug. 1, 2010, to Jan. 10, 2011, again in the E-Mini Dow futures) to see how the results compared to the initial test. This iteration of the pattern added the requirement that the low of the final bar be at least 10 points below the low of the previous bar — a criterion designed to capture more-significant price drops that were thought likely to be followed by quick bounces.

The results suggested the modification might be successful in this regard, although trade frequency was quite low. There were only 35 signals, but the median gain at bar 4 was 5 points — much higher than the 1-point median gain of the original

22 www.activetradermag.com • March 2011 • ACTIVE TRADER

Figure 3: uP MOVeMeNT VS. DOWN MOVeMeNT

There was, on average, more up movement than down movement following the pattern, but that edge was most prominent at bars 1 and 2.

Figure 4: TrADe DiSTriBuTiON

Aside from a bump in the number of trade signals between 10 and 11 a.m. CT, the pattern was most active toward the beginning and end of the trading session.

pattern. However, perfor-mance dropped off sharply after bar 4, suggesting these were relatively brief trade opportunities. Nonetheless, incorporat-ing a price-movement parameter into this type of setup could be a first step in creating a more robust signal. Analysis showed the median low-to-low decline for the final two bars of the setup was 5 points and the average was 7.3. A more moderate decline require-ment (e.g., 2-4 points) for these bars might improve returns without eliminating too many signals. ◆


Figure 5: WiN PerCeNTAge BY TiMe PeriOD

The pattern had a low probability of success in the 11:05-noon period, but favorable odds in other periods depended on the trade’s time horizon.

By Jay Kaeppel

TRaDING Strategies


Trading international stock-index eTFs with relative strength

Rotatingintothestrongestexchange-tradedfundsrepresentingdifferentcountries’

stockmarketsshowsthepotentialtoboostreturnsandreducevolatility.

TRaDING Strategies

continuedonp.26

T he concept of investing in the strongest areas of the mar-

ket has been a winning strategy for many stock inves-

tors over the years. Like any strategy, a relative-strength

approach — i.e., buying the stocks that are currently

outperforming others — is by no means perfect, and can, in fact,

result in above-average volatility. Nonetheless, the potential for

outsized returns can outweigh this risk.

Traditionally, relative-strength investing consists of buying a

portfolio of top-performing stocks, and research has shown this

approach can greatly outperform a buy-and-hold approach over

time. The increased volatility of the approach stems from the real-

ity that any individual stock — even a high-flyer — is susceptible

to an adverse event, such as a surprisingly unfavorable earnings

report, that can knock it out of the sky.

In time, the relative-strength method has been improved by

focusing on sectors and industry groups. Although an individual

stock can be knocked down by a one-off event, sector trends are

less likely to turn on a dime and typically take a longer time to

play out. Momentum in a top-performing sector will often taper

off — resulting in another sector assuming the top spot — before

it enters a prolonged decline.

This fundamental concept can be exported around the globe

through trading single country exchange-traded funds (ETFs),

which track the performance of different international stock in-

dices. In 1996 the iShares family of ETFs launched several ETFs

to track the major stock market averages of a number of various

countries around the globe. This universe has expanded over the

years to include dozens of international stock-index ETFs. Not

surprisingly, there is a high degree of correlation among them. If

there is a global stock bull market, most country ETFs will rise in

value, while most will decline in the face of a global bear market.

Nevertheless, for trading purposes, we can treat each of these

instruments as distinct sectors.

applying a relative-strength strategy to international eTFs The list of international stock-index ETFs shown in Table 1

(p. 26) is by no means exhaustive — it does not, for example,

include such important players as China and India. However,

those in the list all have data going back to 1996, which gives us

the ability to back-test a strategy over a meaningful time period.

Figure 1 (p. 27) shows four international ETFs (representing

Brazil, UK, Japan, and Malaysia, top to bottom) that have expe-

rienced varied results over the years (although all participated in

the 2008 market collapse).

Trading Strategies

There are many ways to measure the

performance of one market relative to an-

other, some of them very complex. How-

ever, the simplest approach — if based

on a sound concept — is often the most

useful. The technique used here measures

the one-year percentage return for each of

the ETFs at the end of each month. The

five ETFs with the best one-year returns

are held during the next month. Initially,

each of the five ETFs purchased receive 20

percent of the total portfolio equity. Sub-

sequently, each time an ETF drops from

the top five, it is sold and the proceeds are

used to purchase the fund that took its

place. If more than one fund drops out of

the top five at the end of a given month,

the proceeds from the funds sold are al-

located equally to the new funds that take

their place. If fewer than five funds show

a gain, then anywhere from 20 percent to

100 percent of the portfolio can be held

in cash. For example, if only two of the

funds show a gain over the previous 12

months, then those two funds would be

held while the remainder of the portfolio

would be held in cash.

The strategy purchases only ETFs that

have produced a gain over the previous

12 months; it does not buy the “smallest

losers.” If no ETF has a positive 12-month

return, then no position is held during the

following month, and the entire portfolio

is held in cash.

The relative-strength strategy rules are:

1. After the close of trading each month,

measure the one-year change for each

of the 21 ETFs in Table 1.

2. If five or more of these funds have

positive 12-month returns, during

the next month hold the five with the

highest returns. When starting out,

allocate 20 percent of capital to each

ETF.


TaBle 1: iSHaReS COUNTRy eTFS TRaDING SINCe 1996

iShares Fund Ticker

Australia EWA

Canada EWC

Sweden EWD

Germany EWG

Hong Kong EWH

Italy EWI

Japan EWJ

Belgium EWK

Switzerland EWL

Malaysia EWM

Netherlands EWN

Austria EWO

Spain EWP

France EWQ

Singapore EWS

Taiwan EWT

United Kingdom EWU

Mexico EWW

SouthKorea EWY

Brazil EWZ

U.S.TotalMarket IYY

Theseinternationalstock-indexETFsallhavepricehistoriesdatingbackto1996andrepresentequitymarketsinNorthAmerica,Europe,Asia,LatinAmerica,andOceania.

TaBle 2: peRFORMaNCe COMpaRISONSystem Buy-and-hold

No. trades 145 1

% profitable trades 59.3%

Avg. annual return 12.9% 9.0%

Net gain 344.3% 118.6%

StD of annual returns 18.9% 25.6%

Average winner +17.3%

Average loser -7.5%

Median winner +8.2%

Median loser -5.1%

Largest winner +260.1%

Largest loser -31.4%

Therelative-strengthstrategyoutperformedbuy-and-hold,anddidsowithreducedvolatility.

3. If a fund drops out of the top five at the end of a

given month, sell this fund and use the proceeds to

buy the fund that replaced it in the top five.

4. If two or more funds drop out of the top five and

are replaced by new funds, the proceeds from the

sold funds should be split as close to evenly as

possible between the new funds being purchased.

(This helps rebalance the portfolio holdings over

time.)

5. If a fund drops out of the top five at the end of a

given month and is not replaced by another fund

with a positive 12-month return (in other words,

if there are fewer than five funds with positive

12-month returns), then sell that fund and hold the

proceeds in cash.

6. If no funds have positive 12-month returns at the

end of a given month, sell any existing fund posi-

tions and keep the portfolio in cash.

7. If the entire portfolio goes to cash, each new fund

position should be allocated 20 percent of the total

account equity until five fund positions are held.

These rules were tested on the 21-ETF portfolio from

March 31, 1997 through Dec. 28, 2010 using an initial

account equity of $10,000.

Measuring the resultsTable 2 compares this strategy’s results to buying and

holding equal initial investments in all 21 ETFs from

Table 1. During 13 years and nine months of testing,

the strategy averaged an annual gain of 12.9 percent vs.

9 percent for buy-and-hold. The strategy’s ending net

profit was 344.3 percent, which was nearly three times

the buy-and-hold profit of 118.60 percent. Figure 2 continuedonp.28


FIGURe 1: INTeRNaTIONal STOCK-INDeX eTFS

ThesefourinternationalETFs(representingBrazil,UK,Japan,andMalaysia)haveexperiencedvariedresultsovertheyears.Therelative-strengthstrategyrotatesintothestrongestETFs(fromapoolof21)eachmonth.

Trading Strategies

shows the strategy’s trade-by-trade percent-

age returns, while Figure 3 compares the

strategy’s equity curve to buy-and-hold based

on a $10,000 initial investment.

The system made money in 10 years and

lost money in four. It also outperformed the

benchmark “all funds” index, which repre-

sents buying and holding all 21 funds, in 10

of the 14 years. Also, the system’s volatility

(as measured by standard deviation of annual

returns) was less than 75 percent that of buy-

and-hold (18.9 percent vs. 25.6 percent).

Diversification and momentumUsing simple relative-

strength analysis with

international stock-

index ETFs allows

investors to diversify

stock holdings across

the globe and achieve

an above-average rate

of return by focusing

on those markets that

are outperforming the

rest. ◆ Forinformationontheauthor,seep.8.


FIGURe 2: TRaDe-By-TRaDe ReSUlTS

Thestrategypostedawinningpercentageofnearly60percent.Thelargestsinglewinner(+260percent)occurredinEWOheldfromOctober2002toDecember2005),whilethelargestloser(-31percent)occurredinEWH(November2007toSeptember2008).

FIGURe 3: eQUITy CURVeS

Thestrategy’sequitycurvemirroredbuy-and-hold’strajectory,butoutperformeditbyawidemargin.

By Prof. DaviDe accomazzo anD rosario rivaDeneyra

TraDinG strategies


active alpha investing for the market’s “new normal”

Inamarketenvironmentwithpotentiallylittletooffer,asimpleETF

sectorrotationapproachshowstheabilitytooutperform.

TraDinG strategies

Go to p. 71 for more information about:

• Sharpe ratio• Variance and standard

deviation

i n trading there are two main approaches: momentum, when a trader bets price will continue in the direction of the previous period; or mean-reversion, when a trader bets prices are in a short-term overbought or oversold situation and are therefore

expected to revert to a longer-term mean or fair value. Of course, identifying a trend in a momentum-based strategy

or a contrarian overbought-oversold condition also requires de-termination of a time horizon. A two-week directional move may be considered a trend by one type of trader, while another may require a two-month move to qualify as a trend.

Given these general investment parameters, I started research-ing different momentum-based ideas, testing different time periods to see if trading advantages could be found across the board by implementing simple momentum or contrarian rules to different asset classes. Further, the convergence of two factors — the realization that for a few years the passive beta approach of buy-and-hold would have been a loser, and the explosion of exchange-traded funds (ETFs) — created the conditions for this type of research.

The first analysis of this idea was conducted in 2008 immediately be-fore the financial crisis as an exercise for students at the Graziadio School of Business and Management at Pep-perdine University. In this article, the study is updated with two additional rotation studies using forex and commodity ETFs.

Beyond buy-and-hold: Goodbye beta, hello alphaFor years Wall Street has relentlessly promoted the buy-and-hold investment approach. Over time this strategy morphed into a quasi-Holy Grail of investing for two major reasons: first, its winning streak over a fairly long time period, thanks to one of the most powerful equity market bull runs ever recorded (1982 to 2000); second, its simplicity and cost efficiency in terms of execution.

The buy-and-hold strategy also fits rather well with the opera-tional needs of the Street. It creates a constant and stable inflow of money into equities, and it frees stockbrokers and financial advisors from the heavy work of actually managing portfolios and allows them to concentrate on asset gathering. The buy-and-hold mantra also helps mutual funds by securing stable flows of capital

It’sunlikelyeconomicconditionswill

favorapassiveinvestmentapproach

intheforeseeablefuture.

into investment products while minimizing liquidity issues.The success of buy-and-hold also helped validate passive

investing and indexing (i.e., beta replication), an investment approach that forgoes market timing, active asset allocation, and stock picking in favor of replicating benchmark performance at low execution and management costs.

All investment strategies, including buy-and-hold and index-ing, experience market cycles with favorable macro and struc-tural conditions. Inevitably, however, these cycles are followed by unfavorable periods. For example, since the bursting of the tech bubble in March 2000, equity market performance has been inconsistent and stocks have underperformed most other asset classes. As a result, a strictly passive strategy has very little performance to show over the past decade. The S&P 500 index originally peaked on March 24, 2000 with a closing price of 1527.46. It then proceeded to lose about 50 percent over the next two years before rallying to a new closing high on October 11, 2007 at 1554.41. This peak was followed by another crash — a 55-percent decline over the next year and half (Figure 1).

In early 2011, the S&P had rallied back above 1250, still

approximately 20 percent below its 2007 peak. And although on a rolling basis holding U.S. stocks passively for at least 10 years has rarely produced significantly negative performance in real terms (there are only three general periods of underperformance since 1880), 2000-2009 has left passive investors with large losses. To make things even more depressing for the indexing crowd, it is unlikely economic conditions will favor the passive approach in the foreseeable future. The long-term implications of the credit-deleveraging process, along with the inflationary pres-sures that have been steadily building up because of aggressive global monetary and fiscal policy, suggest uneven performance for equities for quite some time. For the next few years a “new normal” is likely to emerge in both the real economy and the fi-nancial markets, as they will probably reflect Main Street’s uneven performance with low-beta returns.

Not so shockingly to the astute investor, active risk manage-ment and active asset allocation seem to be back in fashion. “Alpha investing,” the technique of actively seeking alternative and possibly uncorrelated sources of return beyond the passive

continuedonp.33


fiGure 1: uneven Performance

SincetheburstingofthetechbubbleinMarch2000,equitymarketperformancehasbeeninconsistent,andpassiveinvestmentstrategieshavelittletoshowforthepastdecade.

Trading strategies


TaBLe 1: eTf universeAvailable since May

2003

Available since

Dec. 2007

Basic Materials

MXI Yes

IYM Yes Yes

Construction & Real Estate

ITB Yes

IYR Yes Yes

Consumer Goods

KXI Yes

RXI Yes

Energy

IEO Yes

IEZ Yes

IXC Yes Yes

Financials

IAI Yes

IYF Yes Yes

IAK Yes

IAT Yes

IXG Yes Yes

Health Care

IHF Yes

IHI Yes

IHE Yes

IBB Yes Yes

Industrials

ITA Yes

IYJ Yes Yes

EXI Yes

Natural Resources

IGE Yes Yes

Technology

IGN Yes Yes

IGV Yes Yes

IXN Yes Yes

SOXX Yes Yes

Telecom

IYZ Yes Yes

IXP Yes Yes

TaBLe 1: eTf universeAvailable since May

2003

Available since

Dec. 2007

Transport

IYT Yes

Utilities

IDU Yes Yes

JXI Yes

International

IEV Yes Yes

FXI Yes

AIA Yes

EEM Yes Yes

EWZ Yes Yes

Fixed Income

EMB Yes

MBB Yes

TLT Yes Yes

TIP Yes

Commodities

GSG Yes

IAU Yes

Commodities Available Dec. 2007

DBA Yes

GLD Yes

GSG Yes

RJI Yes

SLV Yes

UNG Yes

USO Yes

Currencies

FXE Yes

FXC Yes

FXY Yes

FXM Yes

FXB Yes

FXS Yes

TheETFsusedinthestudycoveredawiderangeofstocksectors,fixedincomemarkets,commodities,andcurrencies.

performance produced by beta exposure, is going to be the cen-tral and pivotal element of every successful portfolio.

investment philosophyThe original study looked at a simple and cost-effective way to actively manage a primarily equity-based portfolio. This article adds studies of commodity and forex ETFs as well. We focused on ETFs as low-cost allocation vehicles to help build a diversi-fied portfolio that could be actively managed using simple rules, and applied the aforementioned major investment styles — mo-mentum and contrarian. Although there are myriad ways to define these two approaches, the philosophy behind them can be

deconstructed as follows:

1. Momentum will overweight the portfolio toward those sec-tors/asset classes that are showing price outperformance.

2. Contrarian will overweight the portfolio toward those sec-tors/asset classes that are suffering price underperformance

The exact rules and composition of the portfolio are described in the following section (“Trading method”).

The idea was to create a model that would allow for an active sector, commodity, or forex rotation in the search for market

continuedonp.34


TaBLe 2: oriGinaL sTuDiesSTUDY 1 STUDY 2 STUDY 3

Period: May 2003 to April 2008

Period: June 2006 to May 2008

Period: October 2006 to May 2008

Sample: 18 ETFs Sample: 30 ETFs Sample: 36 ETFs

Portfolio: 4 ETFs Portfolio: 7 ETFs Portfolio: 9 ETFs

Weight per ETF: 25% Weight per ETF: 14.29% Weight per ETF: 11.11%

Sectors: 4 Sectors: 7 Sectors: 5-9

Period Momentum Value SPY Momentum Value SPY Momentum Value SPY

1 month

Annualizedreturn

8.50% 12.24% 9.33% 17.54% 3.94% 7.02% 17.17% 3.91% 3.13%

Periodavg.return

0.71% 1.02% 0.78% 1.46% 0.33% 0.59% 1.43% 0.33% 0.26%

Periodmax.loss

-8.97% -7.54% -6.05% -6.54% -5.07% -6.05% -5.03% -6.13% -6.05%

Dailymax.loss

-3.79% -2.80% -2.60% -3.04% -2.07% -2.60% -3.20% -2.44% -2.60%

3 months

Annualizedreturn

20.59% 12.29% 9.21% 16.29% 7.49% 6.47% 15.56% -5.87% -3.19%

Periodavg.return

5.15% 3.07% 2.30% 4.07% 1.87% 1.62% 3.89% -1.47% -0.80%

Periodmax.loss

-12.35% -11.53% -10.71% -5.85% -7.69% -9.51% -3.93% -10.84% -9.29%

Dailymax.loss

-3.09% -2.64% -2.74% -3.09% -2.69% -2.74% -4.38% -1.89% -2.68%

12 months

Annualizedreturn

13.03% 17.62% 7.81% 7.21% -7.74% -6.68%

Periodavg.return

13.03% 17.62% 7.81% 7.21% -7.74% -6.68%

Periodmax.loss

-4.65% - -4.95% - -7.74% -6.68%

Dailymax.loss

-3.83% - -2.96% - -3.27% -2.96%

TheoriginalanalysisincludedETFdatathrough2008.

Trading strategies

anomalies. Consistent with the premise that economic and equity performance will be significantly uneven in the future, we looked for an active strategy that would capitalize on such sector discrepancies.

We also decided not to run correlation studies, but to build and rebalance portfolios strictly on sectors selected by the general rules. The philosophy supporting this decision was to concen-trate on a strategy dedicated to significantly outperforming the benchmarks, and then analyze the risk of the portfolio by looking at how the largest losses compared to the index and by calculat-ing the strategies’ standard deviation and Sharpe ratio.

Trading methodFor the sector ETF studies (Studies 1 and 2) we first looked at the available sectors for trading via iShares and chose 42 ETFs rep-resenting the following 15 sectors: Basic Materials, Construction & Real Estate, Consumer Goods, Energy, Financials, Health Care, Industrials, Natural Resources, Technology, Telecommunications, Transportation, Utilities, Fixed Income, International, Fixed Income, and Commodities.

One drawback inherent in this approach is the relatively short historical period available for analysis. We believed we had to back-test at least five years of performance for the results to have a solid foundation. Because a large number of ETFs were introduced in 2006, only 19 of the 42 selected ETFs had data go-ing back at least five years (see Table 1 on p. 32 for the complete universe of ETFs). Therefore, we decided to expand the research into two studies to compare how results would vary when more ETFs were included in the sample. The commodity and forex studies were especially impacted by limited liquidity and short history (three years), as well as a limited number of ETFs from which to choose. Despite these constraints, this was not a sig-nificant problem, as the available ETFs were diversified, liquid, and had enough price history to validate the analysis. (Over time,

interested researchers can conduct additional studies as more data accumulates for these ETFs.)

Each study had different test periods, but all were recalibrated using the same rules: rebalancing every month, rebalancing every three months, and rebalancing every 12 months. At the end of each period (monthly, quarterly, or annually) we would rank the percentage performance of the available ETFs for that period. Then, for the momentum portfolio, we would buy the ETFs in the top 25 percent of the ranking for the following period. For the contrarian portfolio, we would buy the ETFs in the bottom 25 percent of the ranking in the next period.

We equally weighted the positions of the ETFs forming the portfolio, and only included one filter: no more than 25 percent was to be invested in each of the 15 sectors. Our benchmark was SPY, the ETF that tracks the S&P 500.

Study 1 spanned May 2003 to November 2010; 19 ETFs were available for trading and the portfolio consisted of a total of four ETFs. Study 2 spanned December 2007 to November 2010; 42 ETFs were available and the portfolio contained 10 ETFs.

The commodity and currency portfolios (Studies 3 and 4) were rebalanced monthly and quarterly, and they consisted of only one ETF. For the momentum portfolio, the best-performing ETF in the current period was allocated 100 percent of capital the fol-lowing period. For the contrarian portfolio, the worst-performing ETF in the current period would be the only ETF held in the fol-lowing period. The commodity study included seven ETFs, while the currency study included eight ETFs. The benchmark for the currency study was PowerShares DB US Dollar Bullish Fund (UUP), which tracks the performance of being long U.S. dollar futures against six other currencies. The S&P GSCI Enhanced Commodity Trust (GSC) was used as the benchmark for the com-modity portfolio.

The strategies were tested on adjusted monthly closing prices (from Yahoo Finance), except for SOXX (data provided by Fidel-ity). Adjusted daily closing prices were used to determine the maximum daily loss within the worst period. The results do not incorporate commissions or slippage.

Test resultsThe results in Tables 2 (p. 33), 3, and 4 (p. 37) suggest a cost-ef-fective and simple active alpha strategy is achievable. Momentum strategies have outperformed in most time frames and different

continuedonp.36


Momentumstrategiesseemtowork

betterwithquickerrebalancing,while

contrarianapproachesneedlonger

timeframestoarbitragemispricings.


TaBLe 3: uPDaTeD resuLTsETFs ETFs

Period: May 2003-Nov. 2010 Period: Dec. 2007-Nov. 2010

Sample: 19 ETFs Sample: 42 ETFs

Portfolio: 4 ETFs Portfolio: 10 ETFs

Weight per ETF: 25% Weight per ETF: 10%

Period(months)

Sectors: 4 Sectors: Min. 4, Max. 10

Momentum Value SPY Momentum Value SPY

1

Annualizedavg.return 11.52% 0.14% 5.65% 3.30% -4.75% -2.83%

Periodavg.returns 0.96% 0.01% 0.47% 0.28% -0.40% -0.24%

Average gain 3.78% 3.56% 2.94% 4.99% 5.04% 4.76%

Averageloss -4.69% -4.85% -3.92% -5.33% -6.85% -5.87%

Periodmax.return 18.06% 12.15% 9.94% 14.31% 11.02% 9.93%

Periodmax.loss -14.67% -28.14% -16.52% -15.24% -25.05% -16.51%

Winningperiods 66.67% 57.78% 63.33% 54.29% 54.29% 51.43%

Losingperiods 33.33% 42.22% 35.56% 45.71% 45.71% 45.71%

Annualizedstd.dev. 18.12% 20.23% 15.04% 21.51% 26.74% 22.00%

SharpeRatio 0.63 0.00 0.37 0.15 -0.18 -0.14

3

Annualizedavg.return 12.95% 12.14% 7.29% -1.02% 1.42% -0.65%

Periodavg.returns 3.24% 3.04% 1.82% -0.25% 0.36% -0.16%

Average gain 10.76% 8.73% 6.44% 10.02% 9.56% 10.79%

Averageloss -8.05% -10.26% -7.41% -15.67% -13.45% -11.11%


Periodmax.loss -32.38% -30.22% -21.57% -27.70% -31.71% -21.57%

Winningperiods 60.00% 70.00% 66.67% 60.00% 60.00% 50.00%

Losingperiods 40.00% 30.00% 33.33% 40.00% 40.00% 50.00%


SharpeRatio 0.53 0.55 0.42 -0.04 0.04 -0.03

12

Annualizedavg.return 7.42% 10.16% 4.69% 10.33% 33.18% 16.88%

Periodavg.returns 7.42% 10.16% 4.69% 10.33% 33.18% 16.88%

Average gain 17.54% 21.32% 11.61% 10.33% 33.18% 16.88%

Averageloss -53.33% -17.75% -36.80% N/A N/A N/A


Periodmax.loss -53.33% -34.46% -36.80% N/A N/A N/A

Winningperiods 85.71% 71.43% 85.71% 100.00% 100.00% 100.00%

Losingperiods 14.29% 28.57% 14.29% 0.00% 0.00% 0.00%


SharpeRatio 0.26 0.30 0.23 3.94 0.87 1.25

Theupdatedanalysisincludedperformanceresultsinto2010.

Trading strategies

asset classes. Momentum outperformed benchmarks across the board, with a notable exception in the three-year study using an-nual rebalancing, where the value strategy performed much bet-ter (probably because of the 2008 market dislocations). However, value also did better in the longer seven-year study using annual rebalancing, indicating momentum strategies seem to work bet-ter with more frequent rebalancing while contrarian approaches need longer time frames to capitalize on mispricings.

Particularly noteworthy is momentum’s outperformance in the commodity sector using one-month rebalancing, where it posted an annualized average rate of return of more than 23 percent, vs. -7.25 percent for the commodity benchmark. In forex, a three-month rebalancing strategy performed well, both relative to the benchmark and in absolute terms, with an annualized rate of return above 10 percent.

One caveat is the larger standard deviations of momentum strategies. However on a risk-adjusted basis the returns remain attractive because their Sharpe ratios are generally higher than

the benchmarks and in some cases higher than those of the value strategies.

cheap and simple alphaAs mentioned, the motivation behind this analysis was to test a simple and cost-effective way to produce an active alpha strategy that could replace or at least complement more traditional beta-driven portfolios.

The ultimate portfolio optimization comes from the ability to identify sources of return produced by active and skilled invest-ment management. The consistent ability to create enhanced performances by superior market timing and security selection — or more simply, alpha — is today more than ever a central tenet of an optimal portfolio. Over the past decade, indiscriminate exposure to a generalized beta has produced negative returns, and future conditions do not seem to indicate a change in this situation. As a result, the need to actively incorporate alpha-seek-ing strategies in traditional portfolios is a priority.

There is a considerable amount of research to validate the both the momentum and contrarian strategies as solid starting points. Momentum strategies seem to generally work across boundaries for several reasons: under-reaction to the dissemination of news (a practical discovery in clear contrast with the efficient market hypothesis), difficulty for large investment funds to deploy their capital quickly, and, ultimately, the simplicity of execution in momentum strategies that may lead to easy replication and self-fulfilling results. Interestingly, studies show momentum strategies seem to be more successful in shorter-term periods, while value strategies seem to outperform over longer time horizons (see “International Momentum Strategies” by K. Geert Rouwenhorst, Yale School of Management, February 1997). This study seems to validate these conclusions: While momentum outperformed the benchmark and contrarian strategies in most scenarios, it under-performed in the simulation using annual rebalancing, which the longest time frame tested with the least frequent rebalancing.

This switching of outperformance between time horizons could be exploited in a core-satellite type of portfolio, in which the core part of the portfolio is dedicated to long-term value beta expo-sure and the satellite is comprised of alpha-seeking momentum investing.

A simple ETF momentum strategy using quarterly or monthly sector, commodity, or FX rotation offers a cost-effective way to capture the critical alpha component every portfolio will need to offset negative conditions for traditional beta investing. ◆ Forinformationontheauthors,seep.8.


NicholasBarberis,AndreiSchleifer.“StyleInvesting.”HarvardInstituteofEconomicResearchDiscussionPaper1908,December2000.

BobLitterman.“ActiveAlphaInvesting.”GoldmanSachsAssetManagement,OpenLettertoInvestors,2008.

R.Schiller.“FromEfficientMarketsTheorytoBehavioralFinance.”JournalofEconomicPerspectives,17(Winter)2003.

E.Dimson,P.Marsh,M.Staunton.“TheWorldwideEquityPremium:ASmallerPuzzle.”LondonBusinessSchool,EFA2006ZurichMeetings,April7,2006.

H.Markowitz.“PortfolioSelection.”JournalofFinance7,No.1,March1952.

H.Hong,J.Stein.“AUnifiedTheoryofUnderreaction,MomentumTrading,andOverreactioninAssetMarkets.”TheJournalofFinance,Vol.LIV,No.6,December1999.

K.GeertRouwenhorst.“InternationalMomentumStrategies.”YaleSchoolofManagement,February1997.

Related Reading


TaBLe 4: uPDaTeD resuLTs: commoDiTies anD currenciesCommodities Currencies

Period: Dec. 2007-Nov. 2010 Period: March 2007-Nov. 2010

Sample: 7 ETFs Sample: 8 ETFs

Portfolio: 1 ETF Portfolio: 1 ETF

Weight per ETF: 100% Weight per ETF: 100%

Period(months)

Commodities: 1 Currencies: 1

Momentum Value GSC Momentum Value UUP

1

Annualizedavg.return 23.35% -29.50% -7.25% 3.21% -0.98% -0.65%

Periodavg.returns 1.95% -2.46% -0.60% 0.27% -0.08% -0.05%

Average gain 8.91% 7.01% 5.71% 2.78% 3.09% 2.25%

Averageloss -7.86% -9.56% -7.29% -3.72% -2.49% -2.36%


Periodmax.loss -23.73% -24.28% -27.54% -8.35% -15.42% -7.01%

Winningperiods 57.14% 42.86% 51.43% 61.36% 43.18% 50.00%

Losingperiods 40.00% 57.14% 48.57% 38.64% 56.82% 50.00%


SharpeRatio 0.68 -0.82 -0.24 0.22 -0.08 -0.07

3

Annualizedavg.return -3.21% -25.95% -8.83% 10.11% 9.09% -1.88%

Periodavg.returns -0.80% -6.49% -2.21% 2.53% 2.27% -0.47%

Average gain 7.95% 18.15% 16.34% 8.96% 6.12% 3.38%

Averageloss -13.94% -17.05% -14.57% -7.76% -2.21% -4.95%


Periodmax.loss -27.85% -31.45% -43.97% -17.24% -8.92% -8.86%

Winningperiods 60.00% 30.00% 40.00% 61.54% 53.85% 53.85%

Losingperiods 40.00% 70.00% 60.00% 38.46% 46.15% 46.15%


SharpeRatio -0.11 -1.25 -0.21 0.50 1.45 -0.40

12

Annualizedavg.return N/A N/A N/A N/A N/A N/A

Periodavg.returns N/A N/A N/A N/A N/A N/A

Average gain N/A N/A N/A N/A N/A N/A

Averageloss N/A N/A N/A N/A N/A N/A

Periodmax.return N/A N/A N/A N/A N/A N/A

Periodmax.loss N/A N/A N/A N/A N/A N/A

Winningperiods N/A N/A N/A N/A N/A N/A

Losingperiods N/A N/A N/A N/A N/A N/A

Annualizedstd.dev. N/A N/A N/A N/A N/A N/A

SharpeRatio N/A N/A N/A N/A N/A N/A

TheupdatedanalysisaddedcommodityandcurrencyETFs.

By Geoffry WonG

TrADInG Strategies


execution and management of iron condors

Timingthecomponentspreadsofthisfour-optionpositioncan

helpavoiditsdrawbacksandmaximizeitspotential.

TrADInG Strategies

A lthough option traders are often attracted to strategies that offer limited risk and a relatively high probability of success, these approaches are often more difficult to apply than they appear on paper.

The iron condor is a four-option strategy with limited risk that is designed to profit when the underlying market remains in a relatively low-volatility condition during the life of the trade. It is a “credit spread” — that is, the trader collects premium upon establishing an iron condor, and this net credit is the position’s maximum profit.

The components of an iron condor are:

1. Short one out-of-the-money (OTM) put;2. Long one OTM put with a lower strike price;3. Short one OTM call;4. Long one OTM call with a higher strike price.

The trade’s maximum profit occurs when the underlying’s price is between the strike prices of the short put and short call.

Notice options 1 and 2 comprise a bull put spread, while op-tions 3 and 4 represent a bear call spread (see “Option terms” for definitions of these positions). The long call and long put options essentially protect the position against large up or down moves in the underlying instrument.

Although the iron condor seems to represent a fairly straight-forward concept — collect premium and keep it as long as the

underlying market does not break the short strikes in either di-rection and implied volatility remains low — it is easier to profit from these positions in theory than in practice.

The reason goes back to thinking of the iron condor as the combination of a bear call spread and a bull put spread. In short, traders typically collect too little premium on either the bear call spread or the bull put spread portion of the position when enter-ing all legs of the trade simultaneously (and they give away the bid-ask spread, too). This is a result of the differences between call and put options that are equidistant from the underlying price in a given situation.

Let’s look at the mechanics of properly executing an iron con-dor.

Before the tradeThere are a few basic steps for entering any options trade. The first is identifying an appropriate underlying stock or commodity. This is more challenging than it might first seem. Basically, you should be intimately familiar with the underlying market you are interested in trading. It is not in your best interest to apply a strategy unless you have a complete understanding of the under-lying stock or futures contract’s historical highs and lows, annual and quarterly reporting dates, average daily true range (volatility), and volume, as well as the open interest (the number of open po-sitions) in the specific option contracts you might trade. All these factors play an important role in price movement.

Selecting an underlying instrument with the appropriate char-acteristics is an important step in capturing the most premium (credit) possible. Stocks such as Apple (AAPL) will have more premium value simply because their interday volatility is greater than that of many other stocks. For example, if you sold a bear call spread on AAPL a few strikes OTM (i.e., selling an OTM call and buying a higher-strike OTM call with the same expiration date), you would expect to receive more money than if you sold a call spread on, say, Microsoft, which has much lower volatil-ity. Larger underlying price moves translate into higher option premiums.

Another factor that effects the premium value is market per-ception, or “bias.” Using Apple stock again, the market prices the OTM calls higher, which results in higher premiums and call-spread values. For example, the market bias a few months ago was that it was willing to pay more for OTM calls than OTM puts. As a result, calls were more expensive than puts that were equidistant from the current stock price.

At times, option deltas may explain this anomaly or relationship.

The significance of deltaOne of the overlooked aspects of delta is that it is synonymous to the probability of exercise — that is, the odds the underlying will be at a given (strike) price at options expiration. As a result, you need to be careful when simultaneously selling call spreads and put spreads with the same delta but different premiums. Equal prob-ability of exercise should yield equal premium, all else being equal.

If the calls in our example are trading at a premium to the puts but their deltas are the same, there is a value disconnect. If you decide to sell a call spread that is $10 OTM with a delta of 25 percent (.25) and receive a $2 credit, you would expect to receive the same $2 credit when selling a $10 OTM put spread with a 25-percent delta. However, this is often not the case.

For example, in the month of January, AAPL was trad-ing around $340. The $360 call expiring in one month was trading for $5 with a .20 delta — in other words, reflecting a 20-percent chance AAPL would be trading at $360 in one month. By comparison, the $340 put was

continuedonp.40


fIGUre 1: Iron ConDor ProfILe

Theironcondorhaslimitedriskandlimitedprofitpotential,andcanbebrokendownintobearcallspreadandbullputspreadcomponents.

Premium: Thepriceofanoption.

Bear call spread: Acreditspreadthatconsistsofashortcallandahigher-strike,furtherout-of-the-money(OTM)longcallinthesameexpirationmonth.

Bull put spread: Acreditspreadthatconsistsofashortputandalower-strike,furtherOTMlongputwiththesameexpirationdate.Thespread’slargestpotentialgainisthepremiumcollected,anditsmaximumlossislimitedtothepointdifferencebetweenthestrikesminusthatpremium.

Delta: Theratioofthemovementinanoption’sprice(premium)foreveryone-pointmoveintheunderlyinginstrument.Anoptionwithadeltaof0.5(50percent)wouldmoveahalf-pointforeveryone-pointmoveintheunderlyingstock;anoptionwithadeltaof1.00(100percent)wouldmoveonepointforeveryone-pointmoveintheunderlyingstock.

Strike (“exercise”) price: Thepriceatwhichanunderlyinginstrumentisexchangeduponexerciseofanoption.

Time value (“time premium”): Theamountofanoption’svaluethatisafunctionofthetimeremaininguntilexpiration.Asexpirationapproaches,timevaluedecreasesatanacceleratedrate,aphenomenonknownas“timedecay.”

Option terms

Trading Strategies

trading for $3.50 with a .20 delta, which implies a 20-percent probability AAPL would be trading at $340 at expiration. Why should you sell the OTM put for less than the OTM call if the odds are equal AAPL will be trading at either $340 or $360 at expiration? One of these premiums is too cheap.

This may be a good reason to try and leg into the iron condor and receive a higher premium for either the bear call spread, the bull put spread or both. However, because of its risks (described later), this approach is suggested for more seasoned traders. execution: Legging into an iron condorEntering the call-spread and put-spread components of the iron condor separately makes it possible to collect equal premiums for them. The call spreads and put spreads are sold based on favorable conditions in the underlying. For example, if the stock or commodity is approaching major resistance, you can attempt to sell the call spread first. You would be selling into strength with the understanding the market is approaching long-term resistance. Here, you are deferring to the chart. If this analysis of the underlying is correct, the stock will hold resistance and will retreat or sell off at some point. When the downside correction occurs, you can then sell the put-spread component because the market will pay more premium when the stock is dropping in

value. You are taking on some additional risk by selling one leg at a

time, and entering the spread in this fashion requires patience. If you sold your call spreads first, you must understand you are now short the underlying instrument and have risk exposure if it rallies. For example say you sold a $29 Microsoft call and bought a $30 call. The $29 call has a delta of .25 and the $30 call has a delta of .10. This is a bear call spread, so the net difference between the two strikes is 15 percent, which in the case of selling one spread would make your short 15 shares (15 percent of 100 shares). The opposite is true if you sold the put spreads first: You would be long a certain percentage of shares.

Iron condor managementAs with all trading, profiting from an iron condor is a matter understanding your risk and knowing how to manage it. With condors the risk is well-defined: the difference between the strike prices and the credit received for selling the spread.

For example, let’s say AAPL is trading at $340 and you sell a $360 call and buy a $380 call (a $360-$380 bear call spread) for a $2 credit. If AAPL settles at $340 at expiration, the trade profit is $2. If AAPL is trading at $365 at expiration, you would lose $5 on the $360 short call but would keep the original $2 credit, so the total loss would be $3.

Determining the optimum time to sell an iron condor is a bit tricky. A good rule of thumb is to determine a consistent percentage to exit any trade — for example, a 15-percent decline in the value of the spread’s collected premium. Many traders are inclined to let their iron condors ride until expiration to collect the maximum profit. Although this works out sometimes, in the long run it usually leads to traders letting positions move against them and producing losses. Traders should clearly define their risk level for these trades and be disciplined about exiting when that loss is reached.

Finally, the time value factor is very important. The goal is to optimize the decay curve — that is, catch it at its peak. Time decay is not linear; most option models show the maximum ero-sion occurs in the final two weeks before expiration. Accordingly, these types of strategies are most advantageous when entered with three weeks remaining until expiration. ◆

Forinformationontheauthor,seep.8.GeoffryWongwillbea

speakerattheTradersExpoinNewYorkonFeb.22

(www.tradersexpo.com).


Truerange(TR)isameasureofpricemovementorvolatilitythataccountsforthegapsthatoccurbetweenpricebars.Thisprovidesamoreaccuratereflectionofthesizeofapricemoveoveragivenperiodthanthestandardrangecalculation,whichissimplythehighofapricebarminusthelowofapricebar.

ThetruerangecalculationwasdevelopedbyWellesWilderanddiscussedinhisbookNewConceptsinTechnicalTradingSystems(TrendResearch,1978).Truerangecanbecalculatedonanytimeframeorpricebar—five-minute,hourly,daily,weekly,etc.Usingdailypricebarsasanexample,truerangeisthegreatest(absolute)distanceofthefollowing: 1.Today’shighandtoday’slow. 2.Today’shighandyesterday’sclose. 3.Today’slowandyesterday’sclose. Averagetruerange(ATR)issimplyamovingaverageofthetruerangeoveracertaintimeperiod.Forexample,the20-dayATRwouldbetheaverageofthetruerangecalculationsoverthepast20days.

True range

By Howard L. SimonS

TradinG Strategies


Base metals and Chinese monetary policy

Are sliding prices for base metals a currency trade in disguise?

advanCed Concepts

T he various creators of the euro may have had certain

goals in mind for the common currency, but there

is no reason to believe its spread to various funding

currencies as part of global carry trades and the use of

these spreads as risk barometers were on that list. Yet twelve

years into the common currency experiment, this is where we

find ourselves (see “A cross rate to bear,” Currency Trader, May

2009).

As China has pegged its currency to the low-yielding dollar,

plus or minus a little revaluation here and there, the excess

carry return from the Chinese yuan into the euro can be used

as a risk barometer the same way the yen carry has been (see

“The Robin Hood carry,” Currency Trader, July 2010). This

carry trade is composed in turn of two parts, the net interest

rate gain to be made from borrowing three-month yuan and

lending into three-month euros and the change in the spot

rate. Any increase in short-term Chinese interest rates relative

to European rates has the dual effect of tightening domes-

tic credit conditions in China and lowering the interest rate

spread.

This had been readily observable in the time zones out-

side of the green rectangle in Figure 1 when we mapped the

carry of the yuan (CNY) into the euro against the shape of the

Chinese money-market yield curve as measured by the for-

ward rate ratio between six and nine months (FRR6,9

) plotted

inversely. This is the rate at which we can lock in borrowing

for three months starting six months from now divided by

the nine-month rate itself; the more this FRR6,9

exceeds 1.00,

the steeper the yield curve is. The carry trade index should

lead the FRR6,9

by three months given the movement of future

interest changes “rolling down the curve” into the present.

This trade had been disrupted during the Eurozone’s sover-

eign credit crisis from December 2009 – May 2010, the time

period noted in the green rectangle.

One of the great surprises of 2009 given China’s key role

Oneofthegreatsurprisesof2009given

China’skeyroleinarrestingtheglobal

recessionisinterbankcreditconditionsin

ChinabegantotighteninlateMay2009.

in arresting the global

recession is interbank

credit conditions in China

began to tighten in late

May 2009 (see “Viewing

the yuan from the grassy

knoll,” Currency Trader,

February 2011); they just

did not bother telling any-

one. Did this interest rate

action and the carry trade

into the euro have any

impact on global growth

prospects in general and

on base metals prices in

particular?

money and metalsFigures 2-7 depict the

three-month ahead

percentage price change

for an LME three-month

forward as a function of

the Chinese FRR6,9

led by

three months and of the

yuan carry into the euro.

Positive price changes

are depicted in colored

bubbles; negative price

changes in white. The


continued on p. 44

FiGure 1: Cny money markeT yieLd Curve and Carry inTo eur

Thecarrytradeindex’sleadwasdisruptedduringtheEurozone’ssovereigncreditcrisis(December2009–May2010,greenrectangle).

FiGure 2: THree-monTH aHead Tin PriCe CHanGeS aS FunCTion oF CHineSe moneTary variaBLeS

diameter of the bubble

corresponds to the ab-

solute magnitude of the

price change. The current

data points are indicated

with a bombsight; the

last datum involved

in calculating a three-

month-ahead return is

highlighted separately,

and an arrow from there

to the present is overlaid

on the chart.

As it turns out, the

high degree of correla-

tion between the six

metals involved, copper,

aluminum, lead, zinc,

tin and nickel, allows us

to make some consis-

tent observations. As an

aside, while this is good

for analytic purposes, it

makes no sense economi-

cally. With the exception

of lead and zinc, which

often are extracted from

the same ores, these

metals are produced in

very different areas and

under different mining

cycles. Moreover, the

substitution between

them is slight to say the

least; while copper and

advanced Concepts


FiGure 3: THree-monTH-aHead aLuminum PriCe CHanGeS aS FunCTion oF CHineSe moneTary variaBLeS

FiGure 4: THree-monTH-aHead Lead PriCe CHanGeS aS FunCTion oF CHineSe moneTary variaBLeS

aluminum both are used

in electrical wiring, we

would not suggest substi-

tuting copper for alumi-

num in aircraft manu-

facture, and the world

probably is not ready for

beer cans made out of

lead. The high correlation

of these metals’ prices is

due to the influence of

hedge funds and other

investors who insist on

trading them together as a

group.

The net result of

tightening trends for

Chinese monetary policy

is the bombsight had been

pushed toward the south-

ern edge of the charts;

the rebounding carry into

the euro has pushed the

bombsight eastward over

the past three months’ of

data. None of the six met-

als examined have a posi-

tive price expectation from

either this zone or trend in

the bombsight. As Chinese

demand has been setting

the global price for more

important metals such as


FiGure 5: THree-monTH-aHead ZinC PriCe CHanGeS aS FunCTion oF CHineSe moneTary variaBLeS

FiGure 6: THree-monTH-aHead niCkeL PriCe CHanGeS aS FunCTion oF CHineSe moneTary variaBLeS

continued on p. 46

copper, aluminum and

nickel for several years

now, anyone who is long

those metals as commod-

ities or who is long the

equities of mining firms

should run for cover each

time China decides to

tighten. The trade works

in reverse, of course.

This should indicate

global mining stocks’

relative performance is

nothing other than a cur-

rency trade in disguise,

and had been the case

until the weak revalua-

tion began in June 2010

(Figure 8). This develop-

ment, which promised

greater Chinese purchas-

ing power along with

various mining industry

mergers, pushed the

relative valuation of the

HSBC Global Mining

Index for Diversified

Miners against the MSCI

World index higher in a

quantum fashion. Once

this shock has been

absorbed, watch for both

the base metals and for

mining equities’ valua-

tions to resume being a

strong function of Chi-

nese monetary policy. ◆

Forinformationonthe

author,seep.8.

advanced Concepts


FiGure 7: THree-monTH-aHead CoPPer PriCe CHanGeS aS FunCTion oF CHineSe moneTary variaBLeS

FiGure 8: mininG SToCkS are a CurrenCy Trade in diSGuiSe

AsChinesedemandhassettheglobalpriceformoreimportantmetalssuchascopper,aluminum,andnickelforseveralyearsnow,anyonelongthosemetalsorlongmining-firmequitiesshouldrunforcoverwhenChinadecidestotighten.Thetradelogicalsoworksinreverse.

By RoBeRt SucheR JR.

tRADING Strategies


Buy high, sell higher

Arelative-strengthstocksystembeatsthemarketbyawidemarginintesting.

tRADING System Lab

System conceptThis system is inspired by techniques Stan Weinstein described in his book Secrets for Profiting in Bull and Bear Markets (1988, Mc-Graw-Hill), and includes several of Weinstein’s setups, triggers, and filters. Early in the book Weinstein writes that the “blueprint” to successful trading is less about buying low and selling high than it is about buying high and selling higher. Let’s investigate how that would have worked out for the past decade.

Setup conditions. Part of the trading approach is to avoid buying or holding a downtrending stock. Weinstein used multiple forms of chart analysis, including trendlines, but he recommended stocks trading below their 30-week simple moving average (SMA) should never be purchased. Therefore, the first rule ensures the stock’s 30-week SMA is above the previous week’s SMA value and that the stock is trading above it. Also, to ensure the broader market is on the trade’s side, the 30-week SMA of the S&P 500 cannot have declined more than three consecutive weeks at the time of a trade.

The next part of a trade setup incorporates the relative strength (RS) of the sector as well as the stocks within that sector. All else being equal, it makes sense to buy the strongest stocks in the strongest sectors. To realize this rule, the strategy identifies 10 sector exchange-traded funds (ETFs); all stocks in the test portfolio are segregated according to the sectors represented by

these ETFs. The 10 sectors are ranked according to their RS, and candidate stocks are selected from the top-three sectors.

Relative strength is calculated relative to a benchmark, such as the S&P 500 index. Weinstein’s RS formula (stock or ETF price divided by the benchmark) is used here, but applied somewhat differently. Instead of using the trend on an RS chart, the one-week RS rate of change (ROC) is used to rank sectors and stocks: the strongest sector ETFs and stocks are those whose RS values are increasing the fastest.

Trade triggers. Recalling the “buy high” theme, Weinstein ad-vises to identify stocks that have consolidated in a range and do not have nearby overhead resistance. A breakout above the top of the range triggers the entry. The system simplifies the approach by establishing all-time highs and the most recent “20-percent peak” (a top followed by a 20-percent or larger decline) as over-head breakout points.

Once a stock breaks above its overhead resistance, any major obstacle (sellers) impeding a stock’s advance is practically nulli-fied. Weinstein argues that when a stock pushes into new-high territory, no one is holding it at a loss, and new short sellers represent more eventual buying demand.

Position sizing/money management. Weinstein further recom-mends entering a trade with half the normal position size, but if the breakout volume is at least twice the most recent month’s


daily average (the average daily volume over a rolling month, approximately 21 days of trad-ing), the position size is doubled on a dip toward the breakout price. In this system, the posi-tion is instead doubled follow-ing the first daily lower low if the price-adjusted volume (volume*close) is more than double its monthly average. Also, instead of using a typical 10 percent (of account equity) position-sizing rule, the sys-tem will use 5 percent, which can result in owning up to 20 different stocks.

Exit. Weinstein advocates using sell-stop orders for exits instead of percentage targets. To simplify the test, the system uses the stock’s 30-week SMA as a primary trailing stop. However, each higher 5-per-cent low (a non-optimized, arbitrary value) is integrated into the trailing stop. In other words, if the stock pulls back and the daily low advances at least another 5 percent, that pullback low becomes the new stop price, provided it is above

continuedonp.50

Thesystemdidagoodjobofprotectinggains,takingthesystemtoallcash(orveryclosetoit)duringseveralroughperiods,mostnotablythe2002and2008bearmarkets.

FIGuRe 2: equIty cuRve

FIGuRe 1: SAMPLe tRADe

Justasthe“ProfitingwithStockSplits”system(TradingSystemLab,December2010)celebratedTIE,our“BuyHigh”systempickeditupaswell.Sourceforallfigures:FidelityWealth-LabPro/Developer6.0

Go to p. 71 for more information about:

• Rate of change (ROC)


trading System Lab

the SMA. A close below the trailing stop value triggers a sell at the market on the next day’s open.

System rulesSetup and filter conditions:

1. Relative strength: Candidate stocks must be in the top-three sectors as determined by RS ranking.

2. Overall market: The 30-week SMA of the S&P 500 has not moved down more than three consecutive weeks.

3. The 30-week SMA of the stock is higher than the previous week’s SMA value and the closing price is above the SMA.

Enter long if:1. The stock closes above a prior 20-percent peak, or2. The stock closes above the previous all-time high. (In this

case, the stock must be in a top sector, but the other setup conditions do not apply.)

3. In the event of a multiple candidates competing for capital on the same day, choose the one(s) with the high RS rate-of-change.

Exit rules:Sell at the market when the stock closes below any of the follow-ing:

1. An initial 10-percent stop below the close of the breakout day;

2. The 30-week SMA; 3. The most recent 5-percent trough low.

Figure 1 (p. 49) shows how a trade develops. The light green background indicates that TIE’s sector (Materials) qualified as one of the top-three sectors, and the system went long when price climbed to a new all-time high in May 2005. (Note: This was an all-time high within the test data range, beginning June 1, 1999, not an all-time high for the stock’s entire history.) The trade occurred on average volume, so only the 5-percent position was maintained, even as the sector lost its top-ranking status. The trade progressed well above the 30-week SMA (blue stair-step line) and was eventually exited by a close below a 5-percent trough low (which actually turned out to be a “shake out,” as the stock quickly reversed to the upside). Nonetheless, the system

Thebaselinetestresultswereapproximately15percentbetterthantheaverageMonteCarlo simulation.

FIGuRe 3: MoNte cARLo DIStRIButIoN oF Net PRoFIt


continuedonp.52

Profiting with stock splitsActive Trader,December2010Tradingsplitscanofferalonger-termedgeforstocktraders.

Secrets for Profiting in Bull and Bear Markets McGraw-Hill,1988

Related reading

re-entered a week later following the second split shown on Fig-ure 1’s chart, and that trade turned into a 40-percent winner.

Money management/position sizing: Allocate 5 percent of account equity per position on the initial breakout signal. If the price-adjusted volume is more than twice the most recent month’s average, add another 5 percent on the open after the first daily lower low.

Initial equity: $100,000. Deduct $8 per trade ($16 per round trip) in commissions.

Test data: The system was tested on the constituents of the S&P 500 index as of Dec. 10, 2010), as well as the following sec-tor ETFs: IXP, XLB, XLE, XLF, XLI, XLK, XLP, XLU, XLV, and XLY. Dividend data and non-dividend-adjusted price data provided by Fidelity.

Test period: June 1, 1999 to Dec. 10, 2010, which includes a 30-week “seed period” during which no trading takes place.

test resultsFrom the date of the first trade on April 18, 2000, the system performed exceptionally well in the U.S. market’s “lost decade,” returning 11.8 percent annually after costs. Although yield did not influence the entry logic, $23,361, or more than 10 percent of the net profit, is attributable to dividends received, which more than offset the $9,556 in commission costs. The maximum drawdown was moderate at -20.2 percent — and interestingly enough, it occurred in

July 2010 (when the system also made a new equity high, Figure 2, p. 49), not in 2008 or 2009.

More than 71 percent (1,565) of all trade candidates were rejected during the test because of insufficient purchasing power. (As an aside, one could capture a large number of those trades by using margin. Using 50-percent margin, annualized return

FIGuRe 4: PRoBABILIty oF AchIevING PRoFIt LeveL

TheMonteCarlosimulationalsoshowstheoddsaregoodofachievingthelevelofprofitabilityfoundinthebaselinetest.


trading System Lab

increased to more than 15 percent, although the drawdown also increased, to -36 percent.) In back-tests such as this, it is helpful to use a Monte Carlo simulation to get a better perspective on “typical” performance. After performing a “trade scramble” of all 2,175 trades in the back-test, Figure 3 (p. 50) shows the baseline test’s 230-percent net profit is just above the average and median values of 500 scrambled simulations. The distribution of returns in Figure 4 (p. 51) also indicates the probabilities of achieving a profit comparable to the one in the baseline test are excel-lent. Figure 5’s profit-by-instrument chart shows a few symbols accounted for outsized profits, but to a lesser extent than we’ve seen in most other Lab tests.

Because the system was back-tested using the relatively recent composition of S&P 500 index, the results contain a degree of survivorship bias. However, notice the dark-green cash regions in the system’s equity curve, especially during 2002 and 2008

(Figure 2). This shows how the system largely reverted to cash during the most grueling bear-market periods of the past decade. (Note that no interest was earned on free cash in the test.) Fur-thermore, following Weinstein’s method of avoiding stocks below their 30-week SMA should prevent positions from blowing up.

SuggestionsWhile this system’s design often leads to successful re-entries after a stop-out (as occurred in Figure 1), it’s possible the meat of a move is already in the past. Consequently, limiting entries to stocks that break out to new all-time-high territory following a lengthy consolidation could keep portfolio cash more readily available for other stocks showing that pattern. Also, no effort was made to short stocks with weak relative strength in down-trends — a worthy topic of research.

Buying low and selling high is more difficult than it sounds.

StRAteGy SuMMARy

ProfitabilityBuy-higher

systemBuy and hold

(SPY)Trade statistics

Buy-higher system

Buy and hold(SPY)

Netprofit $229,557 $682 No. trades 610 1

Netprofit 229.6% 0.7% Win/loss 42.1% 0%

Profitfactor 2.02 0.00 Avg.profit/loss 4.1% -13.9%

Payoffratio 2.75 0.00 Avg.holdtime 64days 2,678days

Recoveryfactor 4.08 0.00 Avg. win 19.6% 0%

Exposure 72.2% 98.2% Avg.holdtime(winners) 112days 0days

Max.DD -20.2% $8 Avg. loss -7.1% -13.8%

Longestflatperiod 588days -52% Avg.holdtime(losers) 29days 2,678days

Commissions $9,556 1,570days Maxconsec.win/loss 10/13 0/1

Strategy Summary notes: Portfolio-levelresultsincludea30-week“seed”periodinwhichnotradingoccurs(toallowfortheinitialcalculationofthe30-weekSMA).Thishastheeffectofcalculatingslightlylowerexposureandannualizedreturnsthanthoseactuallygeneratedbythesystem.Also,becauseofthe30-weekseedperiod,thebuy-and-holdresultswerecalculatedfromthedateofthefirsttrade,April18,2000.Finally,althoughbuyingandholdingSPYresultedinasmallnetprofitof$682,thetradeisshownasalossbecausethe$15,243incollecteddividendswereresponsibleforthatgain.Dividends,whichaddtotheequitycurveandportfoliomeasures,arenotconsideredwhencalculatingtradeperformancestatistics.

LEGEND:Netprofit — profitatendoftestperiod,lesscommission.Profitfactor — grossprofitdividedbygrossloss.Payoffratio — averageprofitofwinningtradesdividedbyaveragelossoflosingtrades.Recoveryfactor — netprofitdividedbymax.drawdown.Exposure — theareaoftheequitycurveexposedtolongorshortpositions,asopposedtocash.Max.DD(percent) — largest percentagedeclineinequity.Longestflatperiod — longestperiodthesystemisbetweentwoequityhighs.


Sure, it’s easy to buy stocks that appear to be at a low level, but these often continue to get even cheaper — as traders in 2008 and 2009 can attest. Weinstein’s approach of buying high and selling higher appears to have merit more than two decades later. ◆ Forinformationontheauthor,seep.8.

TradingSystemLabstrategiesaretestedonaportfoliobasis(unlessotherwisenoted)usingWealth-LabInc.’stestingplatform.Ifyouhaveasystemyou’dliketoseetested,pleasesendthetradingandmoney-managementrulestoeditorial@activetradermag.com.Disclaimer:TheTradingSystemLabisintendedforeducationalpurposesonlytoprovideaperspectiveondifferentmarketconcepts.Itisnotmeanttorecommendorpromoteanytradingsystemorapproach.Tradersareadvisedtodotheirownresearchandtestingtodeterminethevalidityofatradingidea.Pastperformancedoesnotguar-anteefutureresults;historicaltestingmaynotreflectasystem’sbehaviorinreal-timetrading.

FIGuRe 5: coNtRIButIoN chARt

Whileafewstockscontributedtooutsizedreturns,thischaracteristicismuchlessevidentthaninthemajorityofTradingSystemLabsystems.Alsointerestingisthat144stocksproducedonlynegativeresultsand217otherswere not traded at all.

PeRIoDIc RetuRNS

Avg. return

Sharpe ratio

Best return

Worst return

Percentage profitable periods

Max consec. profitable

Max consec. unprofitable

Monthly 1.0% 0.74 13.9% -16.6% 51.1% 8 9

Quarterly 2.9% 0.72 24.1% -15.1% 59.6% 10 3

Annually 11.5% 0.75 43.4% -8.7% 58.3% 5 3

LEGEND:Avg.return — theaveragepercentagefortheperiod.Sharperatio — averagereturndividedbystandarddeviationofreturns(annualized).Bestreturn — bestreturnfortheperiod.Worstreturn — worstreturnfortheperiod.Percentageprofitableperiods — thepercentageofperiodsthatwereprofitable.Max.consec.profitable — thelargestnumberofconsecutiveprofitableperiods.Max.consec.unprofitable — thelargestnumberofconsecutiveunprofitableperiods.


trAdiNG Strategies


Order up: 2011

Don’tgetyourOCOs,SCOs,andMOCsmixedup.

Thisprimeronordertypeswillmakesenseofthealphabetsoup.

trAdiNG Basics

A lthough trading technology continues to grow apace — especially at the professional level — one thing hasn’t changed: knowing what order type to use and when to use it is an important part of successful trading. Since

we last updated our primer on order types (“Order up,” Active Trader, November 2007), the biggest change for retail traders has been the increased availability of advanced “conditional orders” that allow you to combine two or more trade instructions into a single order, which can be triggered by a wide range of market circumstances.

When considering the different types of orders at their dispos-al, keep a few important points in mind. First, every brokerage is different, and while most of them offer the same basic menu of order-entry options, they will offer different advanced-order types, and/or use slightly different names for them or apply them somewhat differently. Contact your brokerage directly to see what orders they offer and to make sure you understand how they function.

Second, keep in mind that complex order types can provide flexibility in getting in and out of the market, but they often cost more — again, confirm fees with your broker. Finally, just because you have 10 order-entry options at your disposal doesn’t mean you necessarily need to use them. Know what works when, and why. You can know the difference between an AON and an FOK order, but if you don’t understand the potential benefits and risk of each type, and the appropriate situations in which to use them, it won’t do you much good.

While not exhaustive, the following list is representative of the most commonly used orders, along with some advanced order types. Your brokerage may offer order types not on this list, disallow some that are on it, or use different names or acronyms. Some brokerages also have order types that are available for one asset type (e.g., futures) but not another (e.g., stocks).

Market orderThe market order is the most basic order type. It is generally the default order type for brokerages (i.e., if you don’t specify an order type, it’s a market order). A market order is designed to be executed immediately at the best possible price. Traders who use market orders are less concerned with price than they are with the certainty of the order being filled.

If a stock is not particularly active, it’s possible a market buy order will be executed at the best “offer” or “ask” price (see “Bid and offer basics”). However, in a high-volume, highly active stock, where prices are frequently changing, the price you expect and the price you get may be vastly different.

Getting a worse price than expected may not be that big a deal for long-term investors — someone who buys $10,000 worth of stock with the intention of holding it for several years is often not very concerned with paying a few cents more than the quoted price.

However, if you’re a short-term trader, two cents here or a nickel there can seriously impact your ability to make a profit on the trade.

continuedonp.56


Market orders are generally the cheapest, because they are the easiest for the brokerage to execute.

Limit ordersLimit orders allow you to set the specific price at which you will buy or sell.

If you place a limit order to buy at $25, you won’t pay more than $25, and it’s possible (but not likely) you’ll pay less than $25. Likewise, if you place a limit order to sell at $30, you won’t get filled any lower than $30, and there’s a slim chance you’ll get filled higher.

The downside to limit orders is that there is no guarantee an order will be filled. If a stock is trading at 25.03, it may or may not trade down to 25. If it doesn’t, the aforementioned limit order will go unexecuted.

Historically, limit orders have been more expensive than mar-ket orders, although in an effort to obtain business, it’s common for brokerages to offer enticements that include identical commis-sions for market and limit orders.

Stop ordersA stop order is an order that becomes “live” when a certain price level is reached. There are three kinds of stop orders: stop-loss, stop-limit, and stop.

A stop-loss order is designed to cap losses on an open trade. Stop-losses are placed below (for long trades) or above (for short trades) the current market price, and will get traders out of posi-tions before a loss exceeds a certain amount or an open profit loses any more ground.

For example, a trader who enters a long trade at 25 may place a stop-loss at 24.50, hoping to cap his losses at 50 cents. How-ever, there is one drawback to a stop-loss: When the stop price is hit, the order becomes a market order, so there is no guarantee the position will be exited at 24.50.

In a fast-moving market, the price could blow through 24.50, and the order might get filled at a much lower price.

One way to avoid this is to use a stop-limit order. A stop-limit order functions in the same way as a stop-loss, except when the stop price is hit, the order becomes a limit order. This guarantees the exit price will be no worse than 24.50.

But there is a downside to stop-limit orders, as well: There is no guarantee the order will be filled, partially or at all. If price hits 24.50 and continues to fall rapidly, the trader may still have an open (and losing) position.

Stop-limit orders can consist of two prices — a trigger (or “ac-tivation”) price and the stop-out price. For example, a stop-limit order might be, “Sell 100 shares at 24.50 stop, 24.40 limit.” The first price is the “activation price” (i.e., the price the market must trade at to make the order live) and the second price is the actual limit price that represents the worst price at which you will ac-cept a fill. In this situation, as soon as the market trades at 24.50, an order is triggered to sell 100 shares no lower than 24.40. Again, there is always the risk you won’t get filled at all.

While the majority of stop orders are stop-losses or stop-limits, a plain “stop” order can be used to enter a trade. For example, if a stock is trading at 24.85, a trader could enter a stop order to buy

at 25. When (and if) the stock hits 25, the stop order becomes a market order to buy. Similarly, stop-limit orders can also be used to enter trades.

trailing stopA trailing stop lets traders move their stop up (for a long posi-tion) or down (for a short position) in set increments as the market moves in their favor. Trailing stops are designed to help traders protect open profits.

While trailing stops were not available at many brokerages a few years ago, they have since become relatively commonplace.

day orderDay orders are only good through the end of the current trading session, after which they are automatically cancelled. Most trade orders are, by default, day orders.

Good-till-cancelled (Gtc)A GTC order remains open until cancelled by the trader or the broker.

A trader who enters a limit order can designate that order “GTC.” That will keep the order open so it can be filled at a later date (if the market ever moves to the limit price). Most brokers will set a limit on how long GTC orders can remain open (typi-cally between 30 and 60 days for stock trades and until expira-tion for futures and options trades), so it’s important to check your brokerage’s policies before placing a GTC order.

Also, brokerages sometimes assess an additional fee for GTC orders.

fill-or-kill (fOK)A fill-or-kill is an order that must be executed immediately or cancelled.

All-or-none (AON)AON orders must be filled completely or not at all. If you’ve placed a limit order for 500 shares, and only 250 are available at that price, the order will be ignored until (and if) 500 shares become available.

Market-if-touched (Mit)An MIT is a market order that is automatically activated when a designated price level is hit. This guarantees an execution will be made, although a trader using an MIT order takes the risk that all or some of the order might get filled at a price worse than the designated price level. Because of its specific limitation, this order type might be best used in highly liquid but relatively low volatil-ity instruments that increase the odds of getting a favorable fill.

A trader in a profitable long trade might use an MIT order if analysis indicates the market might reach a certain price level but there is uncertainty whether the market will sustain that level for very long. In that case, the MIT order could be used to improve the chances (compared to a limit order) of getting out of the mar-ket, even at the expense of getting a worse price.

Trading Basics

Market-on-close (MOC)An MOC is a market order that is executed as close to the end of the trading day as possible. Some strategies are based on closing price and need to enter or exit a trade at or near that price. While placing a market order at the end of the day serves the same pur-pose, an MOC order can be placed at any time, eliminating the need for a trader to remember to place a last-minute order.

Market-on-open (MOO)A market-on-open is the same as an MOC order, but executed as close to the open as possible.

Limit-on-close (LOC)A limit order entered as close to the market close as possible.

Limit-on-open (LOO)A limit order entered as close to the market open as possible.

Stop-close-only (SCO)A stop order that is activated only if the stop price is triggered during the close of the trading session. If the stop price occurs before the market close, the order is ignored.

Order cancels order or one cancels the other (OCO)An OCO order cancels one order if another is filled. For ex-ample, if you were long and had both a stop-loss order below the market and a limit order to sell at a profit above the market, the two orders could be placed OCO — that is, when one order is executed, the other is automatically cancelled.

An increasing number of brokers are allowing more advanced OCO orders.

For example, you could place a limit order to sell at a profit, a stop-loss to exit with a loss, “OCO MOC” (order cancels order, market on close). This means the trade will be exited on the close if neither of the other two conditions are met and the orders are automatically cancelled.

One cancels all (OCA)The OCA order is similar to the OCO type, except the OCA al-lows for placing more than two orders. For example, if you want-ed to buy any one of three stocks (but not more than one) you could enter three buy-limit orders. The system will execute the order for the first company to reach the limits set by the trader. The buy action will result in cancellation of the other orders.

One triggers another (OTA)An OTA order is consists of two orders — a primary order, and a secondary order that goes live when the first order is filled. For example, you could enter an order to automatically buy Market B if when your limit order to buy Market A is filled. Or, a fill of the primary order could trigger the entry of a stop-loss or

profit-taking order (or both) for that trade. (An order that simul-taneously enters a stop-loss order and a profit-taking order for an open positions is sometimes referred to as a “bracket order.”)

Conditional or contingency ordersDepending on your relationship with your brokerage (i.e., how much money you have in your account), there is virtually no limit to the conditional trades you can design.

For example, you could place a conditional order to buy a certain stock if it makes a 10-day high on volume greater than 10 percent of its average daily volume. Or, if the three major indices are all trading within 1 percent of their five-day lows, sell a cer-tain amount of a particular stock.

Most online brokers only offer conditional orders to their most preferred customers; direct-access brokers are more likely to al-low them to the customer base as a whole.

However, an increasing number of brokerages are offering conditional orders based on a variety of market criteria (including indicator readings), while other brokerages offer automated trad-ing of advanced trading strategies and conditional rules.

Discretionary ordersThese orders give your broker permission (“discretion”) to execute an order as he sees best. For traders who trade only elec-tronically, this type of trading is not available. It is primarily part of the remaining pit-traded futures markets and large institutional trading. Unless you have a very close relationship with your bro-ker, these orders are not recommended.

Do your homeworkRemember, every brokerage is different. Check with your broker before placing any type of advanced or “exotic” order. Gener-ally, the more complex an order is to a brokerage, the more the brokerage will charge you to execute it. Also, there may be restrictions on the firm’s liability for certain types of orders. Many online brokerages have separate trading programs — one for traditional buy-and-hold customers and one for more active cus-tomers. Almost certainly, the latter will offer more order options.

Brokerages have created many more specialized order types over the past few years — often with proprietary names — that may reflect one or more of the order types shown here, and which may use an acronym that represents a very different order somewhere else. The downside of all the new choices is, unfortu-nately, a lack of standardization and the risk of confusion.

Finally, if you’re already feeling a little overwhelmed, keep in mind that it’s entirely possible to be a successful trader or inves-tor with just market, limit, and stop orders. However, knowing what else is available — and when to use it — is never a bad thing. An order type is a tool, and like any tool, you must know the right one for the job to get the desired result. ◆



Nurturing patience By active trader staff

Name: Ayad AmaryAge: 35Lives and works in: Allentown, Pa.

the face of tradiNG

Trading setup

Hardware: PC with 2.3 GHZ pro-cess, 3.25 GB RAM, two 24-inch monitors, one 17-inchSoftware: Sterling Trader Pro

Internet: High-speed cable

Brokerage: OptionsXpress

a fter graduating from college in 1997, Ayad Amary took a job at John Hancock selling mutual funds and life insurance. He did

well, but was always interested in learning more about the stock market.

So did some of his customers, appar-ently. “I was going out hustling insur-ance policies to business owners, and all they wanted to talk about were dot-com stocks,” he remembers. On the side, Am-ary studied for and eventually earned his Series-7 license.

In 2000 he resigned and went to work for a small regional brokerage firm and started building a customer book. He also started trading stocks for himself, then branched into options.

“I tried to carve out a niche with covered-call writing and income-gener-ation strategies,” he says. “I had [a good customer] book, generating a lot of com-missions because I had active customers.”

However, the firm’s goals shifted toward new business development.

“I wanted to sit at my desk and stare at my monitor and trade,” Amary says. But he soldiered on until 2005, focusing on new client generation and building a respectable $15-million customer book.

In 2005, he sold his client list to an-other broker and left the business to enter corporate pharmaceutical sales. Again, Amary achieved the highest sales status in the entire company, but he felt something was lacking.

“I did well, was making good money, had a company car and benefits working only 25 hours per week,” he says. “It made me lazy and complacent. I didn’t enjoy it but thought, ‘how can I walk away when I

am making good money?’” In 2009, despite being in the top 5

percent of the sales force in the entire company, Amary was laid off. He received a nice severance package, and he knew it was time to do what he wanted.

“I’m going to do it now, or I’m going to be stuck in this corporate rut for the rest of my life,” he says. With his severance money and income from his rental proper-ties he owned, he began trading full time.

Born in Syria, Amary moved to the U.S. when he was very young.

“I grew up around a lot of people, including my father, uncles, and cousins, who were gambling or playing poker at the house.” He found that when he began trading, the mentality was similar. In the beginning, Amary admits he was “look-ing for the action.” But he also learned “you can’t bail yourself out at three in the afternoon if you are down $500. You have to take your losses sometimes.”

He read book after book early in his new trading career, but he didn’t see consistent profitability for more than a year. However, over time he developed a trading plan and found “the patience you develop as a trader really does become a habit in the rest of your life.”

Trading approach: Trading stocks only, Amary puts on five to 15 trades per day lasting two minutes to six hours. He primarily trades from the open until noon because he finds fewer opportunities in the afternoon. He focuses “purely on price action,” not indicators.

Amary first identifies stocks that have gapped up or down at the open, which become his universe of stocks for the

day. While he trades several strategies, he estimates 50 percent of his trades are gap plays in which he trades the stock at the open in the direction of the gap, prefer-ably if the gap is in the opposite direction of the daily trends. For example, in an uptrending stock that gaps down on the open, he would sell short half his full posi-tion size, entering on the first one-minute bar that closes lower. Amary will expand to his full position size when the trade “matures” on the 5-minute chart — i.e., on the first 5-minute bar that closes lower. He places a stop-loss above the high of the day, with a target at previous support or at a pivot level from the daily chart. Became profitable when: Amary was a member of a chat room when he started trading, and he would offer up his ideas to the room, many of which turned out to be winning trades. But Amary would also trade other ideas he didn’t put out to the chat room. “I thought, why don’t I take only the trades I put out in the room? I was taking other high-risk positions that I shouldn’t have been trading.” He started to see consistent profits when he stuck to trading his best ideas.

Best thing about trading: “My time is my own. I don’t have to answer to a boss or corporation.”

When not trading: Spends time with family and friends, works out, and plays cards with his buddies.

Best books/websites: Trade Your Way to Financial Freedom by Van Tharp; Tradingwings.com. ◆



A new hedge-fund world

Inpart2ofourinterviewwithLarsKroijer,theformerhedge-fundmanager

discussesthefutureofhedgefunds,andthealternativeto“alternative”

investmentsforindividualtraderslookingforaportfolioedge.

Active trAder interview

“i t’s not like I’m sitting in front of three computer

screens at 7 a.m. anymore.”

That’s one of the ways Lars Kroijer describes life

today. While he hasn’t retired to a tropical island, he

is far removed from the day-to-day hedge-fund grind he expe-

rienced as head of Holte Capital from 2002 to late 2007, and

which he wrote about in his book Money Mavericks: Confessions of

a Hedge Fund Manager.

After closing his fund, spending some time traveling, and writ-

ing the book, Kroijer and his family moved back to the UK a little

more than a year ago. He now sits on the boards of three hedge

funds (run by “good friends”), which he says he enjoys.

“I wish I’d had someone [to consult with] who had been

through it already, just to talk through things,” he says. “Even to

address the minutiae of running a hedge fund: What fraction of

the portfolio does a trader have liberty to trade with? How much

should you pay for a compliance consultant? What should you

pay per square foot of office space? There’s all sorts of things like

that.”

Having experienced

the hedge-fund boom

years — launching a

fund at age 30, building

it up to $100 million in

less than a year, expand-

ing it to $300 million,

and closing up shop

before the 2008 mar-

ket debacle — he has

a unique vantage point

from which to comment

on the hedge-fund indus-

try’s past and future, and

its strengths and weaknesses.

It was the blunt assessment of some of these weaknesses,

especially the issue of high fees, that rankled some of Kroijer’s

hedge-fund compatriots, who took him to task as someone who

turned on his industry — but only after making a healthy profit

in it himself.

But Kroijer says he is simply pointing out what for him became

mathematically obvious: the difficulty for the end investor in

a fund of funds to outperform the market when two layers of

“There’snodoubtIwasburntout

—I’dbethefirsttosaythat.”


continuedonp.60

managers are extracting fees (the industry standard is a 2-percent

management fee and a 20-percent incentive fee). An individual

hedge fund can certainly provide an outperforming investment,

but the deck is stacked against the investor when multiple funds

are involved, even if they are all profitable.

Kroijer is actually quick to defend hedge funds — more accu-

rately, the potential value of any individual hedge fund. But aside

from the fee issue, part of the problem, he notes, is the percep-

tion that hedge funds are a monochromatic asset class — for

example, “U.S. biotech stocks” — when they actually represent

diverse, distinct products. Then there is the PR problem hedge

funds have faced (more so in Europe than in the U.S.) in the

aftermath of the 2008 financial crisis.

“The media sometimes makes it sound like this $2 trillion ‘dark

menace,’ where everyone gets together in a back alley and decides

what to do,” Kroijer says. “It’s not at all like that. It’s 10,000 indi-

vidual firms that are doing completely [different] things, and they

often don’t know the first thing about what the others are doing.”

Lumping all hedge funds together is like comparing apples to

oranges to bananas.

“You’re investing in a firm and person,” Kroijer explains. “I’m

often in the position of speaking about hedge funds as being un-

der one umbrella — in my 30-second slot, I don’t get to differen-

tiate — but I don’t know anything about fixed-income arbitrage,

black-box investing, or silver vs. gold. But they’re all the basis of

hedge funds.”

And that, he adds, is the raison d’etre of funds of funds.

“There are many people who, for whatever reason, want to or

have to invest in hedge funds, but they don’t know what the next

step is, so they go to the funds of funds,” he says.

Kroijer notes that’s what pension funds did, after decades of

avoiding hedge funds. He describes the situation of a hypotheti-

cal pension-fund manager: “He’s sitting there thinking, ‘Oh, we

can’t be the only pension fund in town without a hedge-fund

allocation, but I still don’t know whether gold is better than silver

or what fixed-income arbitrage is.’ But there’s this very nice per-

son at a big fund of funds with lots of snazzy presentations show-

ing they can create uncorrelated positive returns. That sounds

good. So he buys that — it’s cheap at 1 percent per year.”

Kroijer’s sentiments about the industry are ultimately belied by

his use of the words “us” and “we” when discussing hedge funds.

“Don’t make us the villain for everything that happened, be-

cause we’re not,” he says. “That always annoys me — the sugges-

tion that somehow hedge funds caused the [2008] crash. First, I

don’t think they did, and second, it’s a little too easy for some of

the politicians to place blame there. We’re an easy villain because

we’re opaque, the successful ones everyone hears about make

staggering amounts of money, and we frankly don’t do a good job

of defending ourselves. If you’re a politician, that’s great. Except

that there’s never been a taxpayer dollar, pound, or Euro that’s

gone to bail out a hedge fund.”

the futureKroijer fully acknowledges the pre-2008 hedge-fund environment

“Themediasometimesmakeshedge

fundssoundlikethis$2trillion‘dark

menace,’whereeveryonegetstogether

inabackalleyanddecideswhattodo.”

“LarsKroijer:Behindthehedge-fundcurtain”ActiveTrader,February2011Part1ofourinterviewwithLarsKroijer.

MoneyMavericks:ConfessionsofaHedgeFundManager(2010,FinancialTimesPrenticeHall)

Related reading


Active trader interview

was something of a bubble — too much money in too many

funds doing too much of the same thing — but he also points

out market forces ultimately went to work on the industry:

“Something like 2000 hedge funds went out of business in 2008

and 2009,” he notes. “That’s a healthy sign. If you don’t do a good

job, you go out of business.”

Are the 2000-2007 days gone for good? The world has un-

doubtedly been transformed since Kroijer ran his fund, but even

though he thinks the hedge-fund industry’s challenges are large,

he says they are not insurmountable.

“I think the industry will have to prove its worth,” he says.

“And that’s a fee question, as well as answering why the industry

wasn’t as protected in 2008 as everyone thought it was. If it can

do that, there’s no reason growth can’t continue.” However, he

adds: “But it’s a pretty high bar to clear.”

As he notes, it’s not as if investing itself has died, just that a

certain model may have fallen out of favor.

“There will always be investing, it might just be other sectors

— whether it’s renewables, commodities, or whatever,” he says.

“It might not be called market-neutral special situations hedge

funds (the focus of his former fund),” he says, laughing. “There’s

been massive growth in hedge funds, but at the same time, as big

as people say the industry is, we’re not [as big as] banks, after

all.”

Kroijer recounts taking part in a recent panel discussion about

banks. Among the participants were representatives of UK-based

banks, each of which Kroijer says had balance sheets comparable

to the total world-wide assets of the hedge fund industry.

“Just think about that,” he says. “There is room for growth.”

creating your own alternative investmentAfter illustrating how difficult it is for end investors to outper-

form in a fund-of-funds situation, Kroijer concluded his book

with thoughts on how to create a long-term investment portfolio

with the potential to outperform the market while avoiding nasty

episodes such as 2008-2009.

“It’s more as hobby, really,” he says of the portfolio model. “I

followed up and did a great deal more work on it. But it’s slowly

taking on a life of its own. Lots of people say they optimize port-

folios, obviously, but in terms of a very cheaply created optimized

product constructed from existing indices, it’s a struggle to find

[information], and it’s certainly not mass distributed. A couple of

the large index providers have been very keen to move the idea

forward.”

The portfolio Kroijer describes consists of globally diversified

equity ETFs (he also suggests adding corporate and government

debt exposure), with downside risk potentially protected by deep

out-of-the-money (OTM) put options.

“For simplicity, I have started with equities only, and the

allocation is driven by correlations — projected standard devia-

tions — and expected returns, which is driven by the standard

deviation,” he explains. “In a more advanced version, you would

clearly include bonds and other asset classes.”

Kroijer says a basic portfolio of this type could be put together

using six or seven indices.

“The number really depends on how accurate you want to be

vs. the hassle of setting it up,” he notes. “The weightings would

be set through the optimization process, although you would

probably have some restrictions to avoid ‘corner solutions’ that

look nothing like the real world — such as Thailand being 98

percent of the equity portfolio.”

Kroijer points out the portfolio should be constructed accord-

ing to an individual investor’s circumstances, with the overriding

goal of acquiring the least-expensive exposure, factoring in taxes

“Youfindanuggetofinformation,an

angleinthemarketyoudon’tthinkother

peoplearedoing,andit’sarealasset.”


and trade fees. For some investors (again, he

is thinking globally), futures may be prefer-

able to ETFs, for example. He also mentions

add-ons investors could use to further tailor

the portfolio, such adjusting for their other

investments — for example, avoiding a par-

ticular country’s stock index if all your other

assets are in that country.

“You should really set up a whole struc-

ture where the exposure is tailored to the

underlying investor,” he says. “Some should

do ETFs, some futures, some index funds,

some individual stocks, etc.”

Kroijer adds the option element is not es-

sential to the model.

“In fact, it’s highly likely you would end

up not using options,” he says. “Statisti-

cally speaking, it rarely makes sense to do it

systematically because it is far too expensive.

The skew is huge and liquidity is not great.

That point was more a theoretical one that

you would love to have protection against

correlations spiking in times of crises.”

But don’t look for Kroijer to run his own

hedge fund any time soon.

“You know, it was just an amazing

experience, but I don’t think I’ve missed it

enough to want to go back to doing it,” he

says. “I think it’s one of those things that you

have to want as much as you’ve ever wanted

anything, and put your whole heart into it. I

can see how that might perhaps change one

day, but for now, no. That’s why it’s worked

out really well to be on the boards of some

hedge funds — it’s not quite the same, but I

do get some of the buzz.” ◆

Kroijerdescribeshisformerhedgefund,HolteCapital,asamarket-neutralspecial-situationsfund.Hefocusedonfindingtradeopportunitiesthroughdetailedanalysisofcompanyfundamentalsmosttradersnevergetwithinamileofuncovering,letaloneunderstanding.

“Wedidamixofthings:afairamountofmergerarbitrageandintercatalyzationtrades(tradingdifferentshareclassesorholdingstructures),aswellasrestructuringsituations—debtrestructuring,legalcases,orothertransformativeevents.Anotherareawedevelopedwasmultiplepairtrades[between]industries—shippingandoilrigs,particularly.”

TheapproachreflectedKroijer’sinterestsandstrengths.“Ilovedoingstufflikethat.Youfindanuggetofinformation,ananglein

themarketyoudon’tthinkotherpeoplearedoing,andit’sarealasset.”Thefirm’sruncametoanendin2007,triggereditpartbyabad(but

bynomeansdisastrous)tradethattriggeredamodestdrawdownandaninitiallargeinvestorredemption.Kroijermadethedecisiontopulltheplug.Withinaspanoffivemonths,hehadvoluntarilyreturnedthelastinvestorfunds—earlyin2008beforethefinancialcriseskickedintohighgear.

Theinitialtradelostabout4percent,andseveralothertradesultimatelypushedthedrawdowntoaround10to12percent,whichiswhenthefirstredemptionoccurred.Holtehadbecomeknownasalow-volatilityfund,sothisrelativelytamedrawdownlikelycaughtinvestorsabitoffguard.AlthoughthisepisodeunfoldedafterHoltehadincreaseditsleverage(somethinginvestorshadbeenrequesting“forages”),itwasstillatfairlyconservativelevels,accordingtoKroijer.

“Myfrustrationwasthatwewereessentiallydoingthesamethingwealwayswere,buttowardtheendwerefinally[leveraged]thewayweprobablyshouldhavebeenallalong,”hesays.“Thepointis,itprobablyshouldnothave[caughtourinvestorsoffguard],aswehadbeenpainstakinglycommunicatingthatweweretakingleverageup.Inreality,IthinktheredemptionshadmoretodowiththeirinterpretationthatIdidnothavetheappetitetocontinue—somethingacoupleofthemtoldmeprivatelyafterwards.”

Indeed,aftertheinitialloss,someofhisinvestors,whomhealsoconsideredfriends,tookKroijerasideandaskedhimifhisheartwasstillinit.“There’snodoubtIwasburntout—I’dbethefirsttosaythat—andifyoureadbetweenthelinesthereweresomeissuesathomealsothatweren’tgreat,”hesays.“ThoseallplayedtogethertomakeitagooddecisiontocallitadaywhenIdid—which,Idon’tknow,mighthavebeenfortuitoustiming.”(Asmentionedinthefirstinstallmentoftheinterview,Kroijeractuallyfoundhimselfwishinghewasinthemarketwhenthepanicunfolded,curioustoseehowhisfundwouldhaveheldup.)

The end run of a fund

By RoBeRt A. GReen, CPA

tRADInG Strategies


Handling IRS notices and exams

IfyoufindyourselfconfrontedwithanIRSnotice,

learnhowtoproceedtoavoidtaxtrouble.

tHe BUSIneSS of trading

R ecently, the IRS has been making life more difficult for traders. In 2009, it announced major new tax-exam programs on the upper income. (Upper income is defined as those making more than $250,000 per year.)

Those making more than $1 million per year face even more scrutiny. The IRS also announced closer examination of pass-through entities, C-corps, global businesses (on transfer pricing), and foreign offshore accounts.

I’ve noticed another disturbing trend in IRS exams: the new computer-generated mail exam. In this case, IRS computers flag a taxpayer based on standard averages, and the computer generates an exam notice requesting tax documentation. These scary IRS notices force taxpayers to engage professionals at additional costs.

Filing a tax return correctly with the right bells and whistles and fewer red flags is crucial for your 2010 tax returns.

What can you do? The first tip in dealing with the IRS is to get help before prepar-ing your tax return. Adopt strategies to reduce red flags and explain your trader tax status and treatment in well-written foot-notes accompanying the return. A proper trader tax return filed on time will generally not be questioned, except for those with large net operating loss (NOL) carrybacks, which tend to draw

IRS attention. Large NOLs based on weak trader tax status should be carried forward instead.

In this more challenging IRS environment, I suggest all trad-ers — especially part time, losing, and less-than-hyperactive full-time day traders — form an entity in order to file a separate entity-level tax return (with trader tax status) apart from their individual tax return. The IRS won’t be as skeptical about trader tax status on entity tax returns because W-2 wages are reported on separate individual tax returns.

Traders get the shaft on using tax forms. Business trading ex-penses are reported on Schedule C (Profit or Loss from Business), but trading gains and losses go on different tax forms — Sched-ule D (cash method) or Form 4797 (MTM).

Traders should tie the two tax schedules together with income transfers and explain trader tax status in footnotes. Historically, the IRS has higher audit rates for Schedule C businesses because many cash businesses under-report income. Business traders

Allincomeistaxableandneedstobe

reported,whetherornota

third-partyreportsittothetaxpayer.

should use separate tax-filing entities such as partnerships, LLCs, and S-corps in lieu of Schedule C (sole proprietorships) to reduce this risk.

Another important strategy for individual traders is to transfer trading gains to Schedule C to do away with a tax loss and show a break-even business. Net trading income on Schedule C invites questions on the self-employment (SE) tax.

Some traders err in thinking they don’t have to file taxes, or that they can procrastinate. Perhaps they think their trading loss-es offset their other income, such as consulting fees. They may be counting on using ordinary trading loss treatment — based on qualification for trader tax status and a Section 475 MTM election — but this could present problems. If trader tax status and Sec-tion 475 MTM is denied, traders might only be allowed a $3,000 capital-loss limitation, which may lead to a significant amount of taxes owed. The new IRS rules call for a 100-percent penalty on the tax due. It’s more important than ever to deal with your tax matters on time.

tax exam notices If the IRS or your state’s department of revenue contacts you with questions or a notice of tax due, or to schedule an exam, don’t panic or reply on your own. Consult a trader-tax professional and proceed under this person’s advice, either representing yourself (the inexpensive approach) or by engaging the expert as your tax representative, with power of attorney. Your direction should depend upon your financial resources and the complexity of your case.

If you simply made an error on your tax return but you clearly qualify for trader tax status and elected Section 475 MTM on time, you may be able to fix things quickly with a little expert

advice. On the other hand, if you’re a close call on trader tax status and potentially messed up your MTM election or other matters, engage your trader tax expert to be your formal tax representative. In some cases, a CPA may decline to be your representative if he or she thinks you aren’t entitled to relief — perhaps because you clearly botched the MTM election.

exam reconsideration Traders can reply to the IRS with a “reconsideration” request, ask-ing the IRS to close its exam before it gets under way. If the exam was prompted because a trader filed a Schedule C with a loss even though the trader had trading gains in excess of expenses, the trader should be able to get the exam closed (assuming he or she easily qualifies for trader tax status). Other types of notices or exams can be closed with little work, too.

The solution can be as simple as filing a corrected tax return with the proper tax treatment, i.e., filing Form 4797 rather than filing MTM losses incorrectly on Schedule C, and including a detailed footnote.

IRS notices may include questions about business status. But these agents often use standard questions geared to assess “hobby-loss” treatment. Trader tax status requires the intention to run a business, thereby trumping the hobby-loss rules. Note the hobby-loss rules are part of Section 469 “passive activity loss” rules. Under the “trading rule” exception, a trading business is exempt from Section 469, which means an IRS agent can’t apply the hobby-loss rules to a trading business (with trader tax status).

The reconsideration reply letter should state the exam isn’t necessary because of your facts and circumstances. Next, explain how you qualify for trader tax status. State that your business ex-penses are very low compared to other businesses. Make it clear you have no cash income (which is the IRS’s main focus point on small business exams) and that your 1099-B and supplemental information show all proceeds and many elements of net income. Demonstrate that you have good accounting for your securities transactions and more.

Proceeding improperly can jeopardize ordinary-loss treatment, deny business expenses, and leave you with capital-loss treat-ment, which can increase your tax bill significantly. Inappropriate responses may also lead to stiffer penalties and less opportunity

continuedonp.64


If you’re a “good customer” —

meaningyouhavelargetrading

gainsandpaytaxesonthem—you

cansafelybealittlemoreaggressive

onbusiness-expensetreatment.

the Business of trading

for penalty abatement requests.

exams, appeals, and tax court If you’re faced with an exam, it’s smart to be represented by a trader tax CPA or tax attorney. You should have little to no con-tact with the IRS agents. Don’t meet the IRS agent in person or answer his or her questions directly. This is what a tax expert is for. Help your expert by providing all the information needed in an organized manner.

If you have a difficult agent and supervisor in the exam process who refuse to understand the nuances of trader tax, it’s often wise to “agree to disagree” at the exam level and take your case to the next level — the appeals process. During an appeal, trader tax status and MTM treatment may be realized, provided you elected MTM on time. Sometimes, to negotiate an appeals agreement, it’s wise to accept disallowance of some business expenses so the IRS feels justified in its exam efforts; winning trader tax status and MTM is much more important. Appeals officers often focus on the big picture, such as trader tax status, and they may skip over expense items.

The last resort is tax court — often an expensive and more grueling process than a tax exam. If you go to tax court, you must show you acted in one manner or another contemporaneously and that you didn’t change your position in hindsight, which costs the IRS a lot of money.

A common example of this mistake is skipping a timely MTM election because of capital-loss carryovers, and later stating you elected MTM on time. The IRS will disallow MTM on technical grounds and easily win in tax court on this issue.

There’s a legal procedure to file a MTM extension within six months of the original election due date. But this procedure is expensive and unlikely to win MTM. It involves the private letter

ruling process, and to win you must demonstrate no hindsight or prejudice to the government and unusual and compelling circumstances. The IRS recently published streamlined methods for obtaining advanced approval on tax positions that may prove helpful.

Don’t be intimidated Yes, the IRS is a heavyweight, but don’t be intimidated. Traders are small businesses but they are non-cash businesses with few dollars in expenses, so you certainly shouldn’t be scared if you have a strong case for trader tax status.

If you’re a “good customer” — meaning you have large trading gains and pay taxes on them — you can safely be a little more aggressive on business-expense treatment.

Conversely, if you’re a “bad customer” — for example, a peren-nial money-losing or part-time trader — it’s wise to be more conservative, since the IRS may be more prone to deny your trader tax status. In this case, consider skipping a NOL carryback refund return. Rather, carry the NOL forward instead, when it will cause much less attention from the IRS. Or, try to absorb your ordinary loss with a Roth IRA conversion.

If necessary, you may also consider other less attractive, but useful alternatives to trader tax status, such as trading in your retirement plans and deducting reasonable trading expenses within them.

Don’t let the IRS file your return If you trade securities, the IRS receives a 1099-B that shows only proceeds, and it will surely send a tax notice claiming all or most proceeds are income. That tax notice will have tens or hundreds of thousands of dollars in back taxes, plus interest and a full as-sortment of nasty penalties.

Contact the IRS before it contacts you, enhancing your chances of reduced penalties. Interest is statutory and it can never be abated. File your late tax returns as soon as possible, reporting your capital losses correctly, thereby making your tax notice bal-ance due disappear. Plus, you can then carry over capital losses to subsequent tax years, which isn’t possible unless you file the prior year tax returns. Don’t wait more than three years or it will be too late to apply these capital-loss carryovers.


TheIRSwantstoraisetaxrevenue

byfindingmoreunreportedincome,

ratherthanhavingtorelyonCongress

toraisetaxratesordenydeductions.

If you can’t pay your taxes on time, at least file on time and request an installment plan. You can make corrections later. Fail-ing to file a tax extension (calculated in good faith) is a mistake because the “late filing” penalties are much higher than the “late payment” penalties.

Be honest and forthright with the IRS; don’t ignore it. Forget about cheating on your taxes with offshore and tax-free state schemes. Remember, all foreign bank accounts over $10,000 at some point during a year also must be reported annually on Form TDF 90-22.1 due by June 30 of the following year. The IRS has a major program under way to catch offshore tax cheats.

Also, keep in mind the penalty for not filing an income tax return has increased to the smaller of $135 or 100 percent of the unpaid tax.

Avoid bad advice The sad reality is a large percentage of active traders don’t handle their tax affairs properly, or they’re underserved by trusted “pro-fessionals.” A part-time accountant working in a locally branded tax storefront may not be qualified to deliver trader tax services. We have seen many cases where traders have gotten into tax trouble using a general tax store. Some of these firms offer audit guarantees, but they don’t pay back taxes or for a new CPA to fix things. That’s a hollow guarantee.

The IRS recently proposed new standards for tax preparers to address what it perceives as too much bad advice coming from tax preparers who don’t have sufficient education or experience. The proposed tax preparers’ requirements include registration, competency tests, continued professional training, and comply-ing with a set of ethical standards. CPAs are exempt because they already reach and exceed these standards, but most storefronts

and many enrolled agents don’t. In the end, far too many active traders miss out on trader tax

benefits — they don’t deduct allowable business expenses or elect and use ordinary-loss treatment on time. They overpay their taxes and don’t receive the tax refunds they’re entitled to. Even when they do most things right, they file a return with a red flag, caus-ing an IRS and/or state exam. You need an experienced trader tax expert in your corner from day one to handle this challenging IRS environment. ◆ Forinformationontheauthor,seep.8.


Behonestandforthrightwiththe

IRS;don’tignoreit.Forgetabout

cheatingonyourtaxeswithoffshore

andtax-freestateschemes.

Whiletheoldrulesstillapplytothe2010tax-filingyear,newlegislationrequiresbrokeragefirmstobeefupreportingonForm1099-Bsforsecuritiestraders(whichcurrentlyonlyreportproceeds)in2011.Thenew1099-Brulesrequireadditionalreport-

ingofaveragecostbasisandshort-termvs.long-termtreatmentonsecurities.Asaresult,theIRSwillbeabletodoublechecknettradinggainorlossreportingmoreeasily.This1099-Brulechangemayactuallyhelptrad-

ers.Intheeventofnoncompliance,theIRSnor-mallymailsjeopardytaxbillstotraders,discount-ingallmissingcostbasisinformationon1099-Bs.These1099-Brulechangesarepartofamajor

newIRSinitiativetoclosethetaxgap.Itwantstofindmoreunreportedincome,therebyraisingtaxrevenue,withoutrelyingonCongresstoraisetaxratesordenydeductions.Thetax-compliancegapinthiscountryistoohigh;tocloseit,theIRSiscompellingagentstoreportmoreincomeinformationonForm1099s.TheIRScanthenmatch1099-B(andothertaxinformationdocu-mentssuchasW-2,K-1,andmore)totaxreturns,therebyfindingtaxcheatsorinadvertenterrors.Also,the2010health-carelegislationincluded

acontroversialnewrulerequiring1099sforallbusinesspaymentsmorethan$600.Thatcouldbereversedin2011,beforeitseffectivedatein2013.

What’s new?

U.S. economic briefing


THE Economy

Q32010markedthefifthstraightmonthofeconomicgrowthsincetheeconomicdownturn,whichbeganin2008.Source:BureauofEconomicAnalysis

FigUrE 1: QUArTErLY gDP PErFOrMANCE

Non-farmpayrollsincreasedataslower-than-expectedrate,butunemploymentdropped.Source:BureauofLaborStatisticsSeasonallyadjusted

FigUrE 2: PAYrOLLS VS. UNEMPLOYMENT rATE

Pricelevelsremainedmostlyunchangedyear-over-year,exceptforPPI,whichdropped0.8percentto3.5percent.Source:BureauofLaborStatisticsNotseasonallyadjusted

FigUrE 3: OVErALL VS. “COrE” iNFLATiON

FED LEAVES rATES UNCHANgED

Minutes: Federal Open Market Committee

Date and time: Dec. 14 at 2:15 p.m.

Summary: While the FOMC stated the economic recovery had continued through its December meeting, there was little else positive noted. The current environment is still hampered by high unemployment, which constrains household spending, and tight credit. “Employers remain reluctant to add to payrolls,” the committee said in its statement. “The housing sector continues to be depressed. Longer-term inflation expectations have remained stable, but measures of underlying inflation have continued to trend downward.”

The committee announced it would once again hold the target range for the federal funds rate at zero to 0.25 percent.

The following tables compare the S&P 500’s daily and weekly responses to economic re-leases as well as historical behavior since 1997 (or earlier). The S&P rallied only slightly after the FOMC’s announcement, but gained 0.53 percent over the following five days.

rATE CHANgES

S&P 500 reaction

Historical moves since

1994

Report day 0.09% 0.35%

Five days later

0.53% 0.44%

gDP grOWTH CONTiNUES iN Q3

ReportGross domestic product for Q3 2010 (Third)

Date/time Dec. 22 at 8:30 a.m.

Actual 2.6%

Previous 2.5%

Consensus 2.7%

S&P 500 reaction


1994


Five days later

0.41% 0.34%

Despitefallingslightlyoverthesummermonths,manufacturingsentimentremainedhighin2010.Source:InstituteofSupplyManagementSeasonallyadjusted

FigUrE 4: iSM MANUFACTUriNg iNDEX


PPi MAKES UNEXPECTED JUMPReport Consumer Price Index (CPI)


Actual 0.1% (core 0.1%)

Previous 0.2% (core 0.0%)

Consensus 0.2% (core 0.1%)

CPI S&P 500 reaction

Historical moves since ‘80

Report day -0.51% 0.08%

Five days later 1.05% 0.14%

Report Producer Price Index (PPI)


Actual 0.8% (core 0.3%)

Previous 0.4% (core -0.6%)

Consensus 0.5% (core 0.2%)

PPI S&P 500 reaction




iSM ENDS STrONg iN 2010Report ISM manufacturing index

Date/time Jan. 3 at 10 a.m.

Actual 57.0

Previous 56.6

Consensus 57.3

S&P 500 reaction


1997



EMPLOYMENT rECOVErY SHOWS SLOW PACEReport Employment

Date/time Jan. 7 at 8:30 a.m.

Non-farm payrolls

Actual 113K

Previous 79K

Consensus 162K

Unemployment rate

Actual 9.4

Previous 9.8

Consensus 9.7

S&P 500 reaction


Report day -0.18% 0.13%

Five days later 0.78% -0.08%

TheS&Pgainedjustover1percentonthereleaseoftheISMreport,duringthefirsttradingdayof2011.

FigUrE 6: MArKET rEACTiON TO ECONOMiC rEPOrTS

FigUrE 5: S&P 500

AfteranerraticNovember,theS&PgainedthroughoutmuchofDecemberandintothenewyear.Source:eSignal


STOCKS Snapshot

STOCK SymbOl VOlume 1-year reTurn

10-day mOVe / ranK

20-day mOVe / ranK

60-day mOVe / ranK

VOlaTiliTy raTiO / ranK

Positive one-year performanceLas Vegas Sands LVS 31.64M 158.00% 0.53%/33% -2.63%/5% 27.96%/35% .13/13%Apple AAPL 12.18M 57.32% 2.82%/85% 3.48%/33% 12.66%/39% .10/23%HeclaMining HL 13.70M 57.12% -3.23%/100% -4.81%/100% 56.65%/56% .14/20%FordMotor F 55.55M 49.06% 3.15%/84% 4.38%/24% 27.23%/62% .11/23%MGMResortsInternational MGM 27.43M 42.04% 6.97%/30% 15.60%/69% 13.13%/18% .14/7%FifthThirdBancorp FITB 12.60M 32.94% 4.03%/25% 13.13%/80% 18.98%/82% .19/0%Comcast CMCSA 15.35M 32.25% 2.34%/26% 8.93%/67% 24.75%/99% .09/2%EMC EMC 14.02M 31.55% 1.27%/30% 5.05%/67% 16.26%/89% .06/2%Oracle ORCL 27.29M 29.12% -0.62%/100% 9.56%/61% 12.43%/28% .05/0%eBay EBAY 11.50M 22.56% -3.75%/36% -3.44%/62% 15.68%/30% .08/0%HalliburtonCompany HAL 10.82M 21.77% -1.49%/63% -3.11%/27% 13.88%/28% .12/18%AltriaGroup MO 10.90M 21.59% -3.10%/100% 1.41%/13% -0.49%/50% .30/85%TheHomeDepot HD 11.25M 19.06% -1.51%/100% 3.99%/35% 8.72%/23% .09/13%Verizon Communications VZ 15.33M 17.11% 6.97%/90% 12.98%/100% 13.19%/81% .36/87%Vale VALE 15.85M 14.99% 6.42%/80% 4.55%/55% 11.31%/34% .29/82%GeneralElectric GE 55.11M 14.52% 5.14%/40% 11.44%/72% 8.70%/56% .19/8%TaiwanSemiconductor TSM 11.33M 13.68% 2.43%/21% 6.22%/41% 21.91%/90% .14/3%WeatherfordIntlLtd. WFT 11.88M 12.56% -0.49%/50% 1.10%/6% 25.44%/67% .12/2%USBancorp USB 11.28M 10.72% 2.37%/0% 8.56%/56% 19.95%/80% .10/0%AT&T T 20.51M 9.45% 2.57%/72% 5.58%/100% 5.88%/39% .30/83%Wells Fargo WFC 27.66M 8.65% 5.15%/50% 10.12%/69% 21.97%/88% .13/2%ExxonMobil XOM 18.95M 7.31% 3.71%/80% 5.03%/37% 16.34%/56% .14/23%News Corp. NWSA 10.62M 7.07% 3.88%/80% 5.40%/76% 8.00%/55% .26/43%QUALCOMM QCOM 11.48M 4.06% 3.09%/74% 5.48%/58% 13.87%/40% .11/45%Lowe's LOW 13.72M 3.89% -3.91%/100% -1.05%/16% 8.19%/40% .20/27%Intel INTC 43.38M 2.67% -0.38%/0% -2.53%/70% 8.35%/21% .09/0%Wal-Mart WMT 11.29M 2.18% 1.86%/100% 0.51%/18% 0.66%/10% .33/100%Negative one-year performanceBancoSantander STD 10.81M -37.87% 0.95%/0% -1.57%/3% -18.54%/89% .13/0%PetroleoBrasileiroSA PBR 16.45M -23.28% 8.99%/82% 6.82%/71% 6.63%/84% 1.04/97%Nokia NOK 16.47M -18.47% 9.70%/100% 9.37%/69% 0.28%/1% .32/67%SeagateTechnology STX 10.41M -18.07% 0.61%/8% -0.47%/12% 21.15%/20% .08/0%Hewlett-Packard HPQ 17.79M -16.42% 4.15%/100% 1.82%/19% 6.03%/41% .36/90%CiscoSystems CSCO 62.25M -16.35% 4.59%/94% 5.62%/40% -8.72%/58% .23/55%BankofAmerica BAC 185.93M -15.89% 12.84%/84% 22.34%/100% 8.04%/100% .49/83%NVIDIA NVDA 12.77M -14.80% 10.20%/93% 8.66%/37% 45.21%/96% .18/22%MarvellTechnologyGroup MRVL 10.50M -14.20% -4.88%/65% -10.46%/100% 8.06%/35% .18/13%MorganStanley MS 11.64M -13.52% 8.42%/89% 11.47%/97% 12.44%/98% .46/50%ResearchInMotion RIMM 11.02M -9.49% 1.06%/0% -6.68%/89% 19.73%/45% .06/2%ChesapeakeEnergyCorp. CHK 11.66M -8.70% 3.39%/11% 16.27%/81% 13.75%/88% .24/0%Microsoft MSFT 49.16M -7.76% 1.00%/11% 4.65%/47% 14.32%/91% .09/0%Dell DELL 18.30M -7.01% 2.45%/70% -0.09%/0% -0.02%/0% .11/3%Merck MRK 13.91M -3.63% -0.41%/17% 3.12%/62% -1.52%/34% .12/0%Pfizer PFE 37.45M -2.92% 4.77%/85% 7.01%/97% 3.03%/19% .29/80%Corning GLW 11.24M -2.55% 0.79%/10% 2.03%/24% 3.81%/18% .10/0%JPMorganChase JPM 30.65M -1.41% 10.54%/100% 10.66%/86% 12.34%/100% .46/25%Johnson&Johnson JNJ 10.14M -1.00% 1.38%/88% 1.85%/39% 0.19%/0% .23/78%Yahoo YHOO 13.35M -0.65% 1.90%/42% 1.60%/23% 14.50%/21% .08/0%Alcoa AA 22.53M -0.54% 11.85%/100% 16.05%/95% 28.16%/87% .29/50%AnnalyCapitalManagement NLY 13.04M -0.34% -4.98%/100% -4.51%/100% -2.03%/71% .85/100%AppliedMaterials AMAT 10.67M -0.29% 2.72%/0% 7.30%/62% 18.19%/56% .07/0%

All Snapshots are as of Jan. 4. Active Trader’s Snapshot tables summarize the trading activity in the most actively traded stocks, ETFs, and futures. The informa-tion does NOT constitute trade signals. It is intended only to provide a synopsis of each market’s liquidity, direction, and levels of momentum and volatility.


eTF Snapshot

Leverage: “2x”=doubleleverage;“3x”=triple leverage.Volume:30-dayaveragedailyvolume.1-year return:Thepercentagepricemovefromthecloseoneyearago(250tradingdays)totoday’sclose.10-day move:Thepercentagepricemovefromtheclose10daysagototoday’sclose.20-day move: Thepercentagepricemovefromtheclose20daysagototoday’sclose.60-day move: Thepercentagepricemovefromtheclose60daysagototoday’sclose.The “Rank” fieldsforeachtimewindow(10-daymoves,20-daymoves,etc.)show

thepercentilerankofthemostrecentmovetoacertainnumberofthepreviousmovesofthesamesizeandinthesamedirec-tion.Forexample,the“Rank”for10-daymoveshowshowthemostrecent10-daymovecomparestothepasttwenty10-daymoves;forthe20-daymove,the“Rank”fieldshowshowthemostrecent20-daymovecomparestothepastsixty20-daymoves;forthe60-daymove,the“Rank”fieldshowshowthemostrecent60-daymovecomparestothepastone-hundred-twenty60-daymoves.Areadingof100percentmeansthecurrentreadingislarger

thanallthepastreadings,whileareadingof0percentmeansthecurrentreadingissmallerthanallpreviousreadings.Thesefigures provide perspective for determin-inghowrelativelylargeorsmallthemostrecent price move is compared to past price moves.Volatility ratio/rank:Theratioistheshort-termvolatility(10-daystandarddevia-tionofprices)dividedbythelong-termvolatility(100-daystandarddeviationofprices).Therankisthepercentilerankofthevolatilityratiooverthepast60days.

eTF SymbOl leVer-age inVerSe VOl. 1-year

reTurn10-day

mOVe / ranK20-day

mOVe / ranK60-day

mOVe / ranKVOlaTiliTy

raTiO / ranK

Positive one-year performance

iSharesSilverTrust SLV 27.05M 62.55% 1.29%/11% -1.46%/100% 27.94%/40% .16/20%SmallCapBull3xShares TNA 3x 7.97M 56.80% 1.54%/0% 10.48%/20% 43.83%/45% .08/0%UltraQQQProShares QLD 2x 3.72M 38.59% 2.43%/25% 5.64%/34% 23.35%/38% .08/7%S&PSelectRetailSPDRFund XRT 8.19M 30.60% -0.21%/0% -0.50%/100% 11.60%/10% .08/7%S&PSelectCons.Disc.SPDR XLY 5.36M 23.82% 0.16%/0% 0.48%/2% 9.55%/19% .06/13%iSharesRussell2000IndexTrust IWM 42.82M 22.21% 0.12%/0% 3.00%/10% 13.20%/45% .06/2%ProSharesUltraS&P500 SSO 2x 10.01M 21.98% 3.80%/35% 8.00%/63% 19.25%/55% .10/0%S&PSelectIndustrialSPDRFund XLI 9.46M 21.81% 1.56%/35% 3.09%/43% 8.93%/40% .05/0%SPDRGoldTrust GLD 14.08M 21.59% -0.27%/0% -3.13%/100% 2.35%/17% .25/43%iSharesMSCIHongKongIndex EWH 4.96M 21.53% 5.22%/100% 2.81%/30% 4.99%/11% .24/77%iSharesDJUSRealEstateIndex IYR 8.04M 20.54% 1.81%/50% 0.85%/5% 2.76%/16% .28/42%MarketVectorsGoldMinersETF GDX 7.96M 20.20% -2.56%/60% -7.49%/100% 3.00%/10% .23/28%PowerSharesQQQTrust QQQQ 52.44M 19.70% 1.29%/32% 2.64%/34% 11.09%/36% .07/15%iSharesMSCITaiwanIndex EWT 10.54M 17.65% 2.85%/45% 4.64%/59% 13.92%/78% .28/65%SemiconductorHOLDRS SMH 5.67M 16.99% 1.02%/38% 0.31%/3% 15.46%/42% .03/0%VanguardEmergingMktsETF VWO 15.67M 15.04% 3.70%/75% 2.13%/31% 3.98%/8% .28/68%S&PSelectEnergySPDRFund XLE 11.93M 13.79% 2.79%/45% 3.23%/2% 16.81%/57% .11/10%SPDRKBWBank KBE 6.34M 12.87% 5.69%/50% 11.11%/81% 12.29%/87% .24/10%iSharesMSCIEmergingMarket EEM 51.75M 12.74% 4.62%/93% 2.68%/39% 4.52%/10% .28/68%S&PSelectTech.SPDRFund XLK 6.71M 11.71% 1.87%/65% 3.06%/27% 9.70%/52% .08/17%S&PSelectMaterialsSPDRFund XLB 7.44M 11.67% 2.07%/10% 3.75%/41% 12.32%/62% .09/0%S&PDepositoryReceipts SPY 135.48M 11.20% 1.91%/45% 3.44%/45% 8.96%/53% .09/2%iSharesMSCIJapanIndexFund EWJ 20.94M 10.20% 2.70%/75% 3.14%/58% 7.72%/64% .24/38%DiamondsTrust DIA 5.93M 10.10% 1.65%/65% 2.55%/46% 5.88%/43% .09/13%S&PSelectCon.StaplesSPDR XLP 4.84M 9.79% -0.20%/50% 1.84%/33% 3.83%/24% .06/3%S&PSelectHomebuildersSPDR XHB 4.57M 7.29% -0.19%/100% 2.59%/33% 8.91%/47% .12/7%S&PSelectFinancialsSPDR XLF 64.67M 6.30% 4.73%/65% 7.39%/85% 10.71%/95% .23/10%iSharesMSCIBrazilIndexFund EWZ 13.20M 5.29% 8.10%/100% 4.26%/67% 2.49%/7% .47/100%iSharesBarclays20+YrT-Bond TLT 12.22M 4.69% 0.41%/20% -2.82%/29% -10.27%/63% .13/0%iSharesMSCIEAFEIndexTrust EFA 16.75M 3.03% 1.42%/50% 2.40%/25% 2.90%/6% .14/28%S&PSelectUtilitiesSPDRFund XLU 4.97M 2.88% 1.43%/79% 1.43%/66% -0.68%/35% .28/55%FinancialBull3xShares FAS 3x 27.09M 1.75% 12.72%/70% 19.75%/82% 29.14%/90% .27/12%iSharesFTSE/XinhuaChina25 FXI 13.90M 0.94% 4.49%/100% 1.01%/0% -0.26%/6% .27/53%S&PSelectHealthCareSPDR XLV 5.20M 0.50% 0.73%/13% 3.24%/75% 3.64%/26% .11/12%

Negative one-year performance

SmallCapBear3XShares TZA 3x yes 16.17M -65.72% -2.39%/0% -10.76%/12% -35.23%/47% .03/0%UltraShortRuss.2000ProShares TWM 2x yes 3.93M -47.61% -1.50%/0% -7.29%/15% -24.70%/48% .03/0%FinancialBear3xShares FAZ 3x yes 25.64M -46.03% -12.19%/65% -18.08%/86% -28.58%/93% .13/7%LargeCapBear3xShares BGZ 3x yes 4.39M -45.96% -5.41%/30% -10.83%/47% -26.33%/57% .05/0%ProShrsUltraProShortS&P500 SPXU 3x yes 4.18M -44.06% -5.65%/35% -11.16%/53% -25.56%/56% .05/0%UltraShortQQQProShares QID 2x yes 9.49M -39.68% -2.76%/35% -5.76%/37% -20.69%/38% .05/8%UltraShortS&P500ProShares SDS 2x yes 20.77M -30.04% -3.71%/35% -7.64%/56% -17.56%/56% .06/2%UltraShort20+YrTr.ProShares TBT 2x yes 16.69M -26.07% -1.94%/57% 3.88%/25% 18.11%/58% .21/15%United States Oil Fund USO 6.79M -6.48% 0.08%/0% -0.37%/14% 5.34%/45% .17/12%PowerShrsDBUSDIndxBullish UUP 4.37M -0.52% -1.55%/50% -0.48%/7% 2.14%/93% .32/88%


FuTureS Snapshot

marKeT SymbOl exChange VOlume Open inTereST

10-day mOVe / ranK

20-day mOVe / ranK

60-day mOVe / ranK

VOlaTiliTy raTiO / ranK

E-MiniS&P500 ES CME 1.49M 2.38M 1.93%/40% 3.54%/52% 9.03%/54% .08/0%10-yr.T-note TY CME 960.1 1.26M 0.06%/0% -2.44%/56% -5.51%/97% .16/10%5-yr.T-note FV CME 484.1 946.4 0.02%/0% -1.68%/47% -3.29%/96% .18/20%EUR/USD EC CME 302.6 162.3 1.43%/57% -0.14%/6% -4.34%/91% .24/70%30-yr.T-bond US CME 265.3 518.5 0.72%/25% -3.18%/52% -9.69%/88% .15/7%Crude oil CL CME 270.2 279.0 0.01%/0% 0.00%/0% 8.13%/41% .13/8%Eurodollar* ED CME 247.4 801.6 0.06%/29% -0.13%/41% -0.20%/83% .53/95%E-MiniNasdaq100 NQ CME 192.5 335.0 1.14%/21% 2.51%/32% 11.12%/36% .07/5%2-yr.T-note TU CME 206.4 612.8 0.03%/40% -0.05%/13% -0.13%/67% .44/68%Corn C CME 127.2 644.3 1.50%/0% 7.11%/10% 15.18%/26% .13/18%Gold100oz. GC CME 132.8 323.5 -0.53%/29% -2.63%/100% 2.49%/20% .27/52%E-MiniRussell2000 TF CME 91.7 308.1 0.62%/0% 3.15%/17% 13.14%/41% .06/0%Natural gas NG CME 117.2 140.0 10.20%/91% 4.03%/24% 27.88%/98% .71/100%JPY/USD JY CME 102.5 108.2 2.15%/67% 0.80%/3% 0.10%/2% .60/95%MiniDow YM CME 79.6 76.8 1.89%/75% 2.34%/39% 6.14%/44% .09/5%GBP/USD BP CME 88.8 77.5 0.50%/40% -0.92%/14% -2.31%/68% .34/47%AUD/USD AD CME 79.2 110.2 1.29%/56% 0.66%/18% 1.82%/2% .24/65%Soybeans S CME 86.3 194.5 4.12%/37% 6.29%/31% 20.65%/72% .19/18%CAD/USD CD CME 69.8 96.3 1.86%/87% 0.34%/23% 1.36%/23% .52/63%Silver5,000oz. SI CME 58.1 71.2 0.52%/0% -0.76%/0% 27.71%/41% .18/23%Wheat W CME 40.8 202.2 2.57%/20% -0.48%/0% 9.73%/25% .24/42%Sugar SB ICE 41.0 235.3 -4.62%/100% 5.08%/0% 23.21%/10% .29/60%Soybeanoil BO CME 44.8 88.5 3.40%/40% 6.18%/30% 21.94%/50% .14/8%CHF/USD SF CME 38.9 41.1 1.69%/30% 3.42%/45% 1.46%/3% .41/95%RBOBgasoline RB CME 38.2 58.9 1.52%/11% 3.09%/13% 11.48%/37% .10/0%Heating oil HO CME 40.6 68.0 0.68%/11% 1.24%/7% 9.84%/42% .11/8%Copper HG CME 27.7 98.7 3.88%/15% 9.01%/69% 15.75%/40% .22/43%Soybeanmeal SM CME 25.5 48.2 4.64%/53% 6.15%/44% 16.32%/88% .29/40%U.S. dollar index DX ICE 18.0 25.9 -1.57%/50% 0.13%/0% 2.62%/78% .33/90%MXN/USD MP CME 25.7 122.1 1.47%/100% 0.59%/13% 1.50%/19% .20/17%E-MiniS&PMidCap400 ME CME 20.6 95.0 0.52%/0% 2.90%/10% 12.55%/50% .05/2%S&P500index SP CME 24.4 277.7 1.94%/40% 3.53%/52% 9.02%/54% .08/0%Live cattle LC CME 9.2 51.7 3.31%/50% 2.71%/41% 11.12%/94% .59/85%Leanhogs LH CME 9.8 57.9 1.61%/0% 13.09%/91% 3.72%/56% .24/43%Coffee KC ICE 8.6 88.8 4.28%/13% 14.72%/83% 35.46%/93% .25/18%Nikkei225index NK CME 8.9 39.9 1.21%/50% 2.36%/33% 8.14%/58% .14/17%Cocoa CC ICE 8.4 70.0 -0.64%/25% -0.10%/0% 7.01%/70% .43/53%Crudeoile-miNY QM CME 7.3 4.1 0.00%/0% 0.00%/0% 8.14%/43% .13/8%NZD/USD NE CME 6.8 26.0 3.48%/57% 0.22%/0% 1.84%/17% .59/90%Mini-sizedgold YG CME 4.6 3.6 -0.35%/14% -3.14%/100% 1.90%/18% .26/47%E-MiniEUR/USD ZE CME 5.0 4.3 1.43%/57% -0.14%/6% -4.34%/91% .24/70%Mini-sizedsilver YI CME 4.3 3.2 1.51%/11% -1.23%/100% 28.03%/40% .16/22%Fed Funds** FF CME 2.5 36.8 0.00%/0% -0.01%/55% -0.03%/88% .00/0%Nasdaq100 ND CME 1.8 15.6 1.14%/21% 2.51%/32% 11.12%/36% .07/5%Naturalgase-miNY QG CME 2.1 4.7 10.27%/91% 4.01%/24% 27.95%/98% .71/100%Feeder cattle FC CME 2.0 11.6 0.23%/0% 2.11%/24% 12.32%/100% .10/0%DowJonesInd.Avg. DJ CME 0.5 5.8 1.89%/75% 2.34%/38% 6.14%/44% .09/3%

Note: Average volume and open-interest data includes both pit and side-by-side electronic contracts (where applicable). Price activity for CME futures is based on pit-traded contracts. Volume figures are for the most-active contract month in a particular market and may not reflect total volume for all contract months. *Average volume and open interest based on highest-volume contract (December 2011). **Average volume and open interest based on highest-volume contract (March 2011).

This information is for educational purposes only. Active Trader provides this data in good faith, but it cannot guarantee its accuracy or timeliness. Active Trader assumes no responsibility for the use of this information. Active Trader does not recommend buying or selling any market, nor does it solicit orders to buy or sell any market. There is a high level of risk in trading, especially for traders who use leverage. The reader assumes all responsibility for his or her actions in the market.

NinjaTrader, LLC has released the seventh major version of its Nin-jaTrader trading platform, which includes more than 300 Nin-jaTrader 7.0 enhancements, including: improved system perfor-mance; expanded charting features; Kinetick market data service, which includes free end-of-data; enhanced NinjaScript develop-ment environment, including an improved strategy development/back-testing workflow, limitless strategy order submission flex-ibility, draw-object enhancements, and improved multi-color plot handling; a strategy back-testing functionality with more ways to verify a trading system, including genetic optimization, data series optimization and Monte Carlo analysis; and a new hot-key manager, which includes the ability for users to define and assign hot keys for global and local window functions. Visit the Ninja-Trader website (www.ninjatrader.com/ninjatrader7-features) for a complete listing of enhancements and upgrades.

FXstreet.com has introduced a new design and an updated navigation to its website. The site has been restructured to a two-column layout, and darker text and more spacing have been added to make it easier to read. A system improvement designed to optimize the speed at which the pages are loaded has been enacted, and the “Latest Forex News” (www.fxstreet.com/news/forex-news/) page allows filtering by categories, currencies, and

news providers.

Interactive Data Corporation has released eSignal 11, a redesigned version of the core eSignal software. The new version features an improved intuitive interface that allows users to focus entirely on market analysis and trading and offers a range of customiza-tion options. Users can choose from among a variety of colors and default settings for menus and toolbars, or create or import their own themes. Tabbed, multi-page functionality allows users to move between the data sets essential to trading style. Users worldwide can access support in their native languages. Com-pany profiles, financials, earnings estimates, analyst ratings and other key information can be viewed in a single window. New ca-pabilities enable viewing, sorting, and scanning for opportunities while in a Watch List, as well as displaying technical indicators, and pre-built and customized studies from the eSignal Formula Script (EFS) library. The new Trade Manager allows users to view current market depth and enables single-click trading to place or modify orders. Users can develop multi-level money management strategies with customized combinations of profit and protective stop orders, including break-even and trailing stops. For a com-plete list of eSignal features, please visit www.esignal.com/esignal or call 510-723-1765. ◆


Momentum (or “price momentum”): A generic term used to de-scribe the rate at which price changes, as well as the name of a specific calculation. Rate of change (ROC) is simply an alternate version of this basic indicator. The implications and interpreta-tions of these two studies are identical. Momentum/ROC are similar to oscillators, such as the relative strength index (RSI) and stochastics, in that they are generally intended to highlight shorter-term price momentum extremes (overbought or oversold points). The most common calculation for momentum is simply today’s price (typically the closing price) minus the price n days ago: (Ptoday – Pn days ago). The most basic ROC formula is today’s price divided by the price n days ago: (Ptoday/Pn days ago). Alternate calculations for rate of change are 100*(Ptoday/Pn

days ago) or (Ptoday – Pn days ago)/Pn days ago. Except for scaling, the resulting momentum and ROC indicators are the same; momen-tum simply expresses price change as the difference between two prices, while ROC expresses price change as a percentage or ratio.

Sharpe ratio: Average return divided by standard deviation of returns (annualized).

Variance and standard deviation: Variance measures how spread out a group of values are — in other words, how much they vary. Mathematically, variance is the average squared “deviation” (or difference) of each number in the group from the group’s mean value, divided by the number of elements in the group. For example, for the numbers 8, 9, and 10, the mean is 9 and the variance is: {(8-9)2 + (9-9)2 + (10-9)2}/3 = (1 + 0 + 1)/3 = 0.667

Now look at the variance of a more widely distributed set of numbers: 2, 9, and 16: {(2-9)2 + (9-9)2 + (16-9)2}/3 = (49 + 0 + 49)/3 = 32.67

The more varied the prices, the higher their variance — the more widely distributed they will be. The more varied a market’s price changes from day to day (or week to week, etc.), the more volatile that market is. A common application of variance in trading is standard devia-tion, which is the square root of variance. The standard deviation of 8, 9, and 10 is: sq. rt. 0.667 = .82; the standard deviation of 2, 9, and 16 is: sq. rt. 32.67 = 5.72. ◆

KEY Concepts

NEW Products & Services


TRADER’S Bookshelf

Diary of a Profes-sional Commodity Trader: Lessons from 21 Weeks of Real TradingPeter L. BrandtHardcover, 304 pagesJohn Wiley & Sons

Using a diary format, Brandt provides a

play-by-play of 21 weeks of his 2009 trad-ing, revealing what the experience was like and “communicating the uncertainty that surrounds every trade and the discipline required to make tough decisions in the face of losing money.” The author also touches upon his philosophy of specula-tion, market analysis, trade identification and selection, risk management, and the methods and rules he has used to trade successfully. Each trade includes charts, an analysis of the trade, and a detailed ac-count of how it unfolded.

Crapshoot Invest-ing: How Tech-Savvy Traders and Clueless Regulators Turned the Stock Market into a Casino Jim McTagueHardcover, 264 pagesFT Press

This book starts with the premise that “eq-uity markets are now high-speed casinos rigged against individual investors.” The author, Barron’s Washington editor Jim McTague, writes about the “twin causes”: high-frequency traders and blundering regulators. The book dissects why the Flash Crash happened, and why it will happen again, and explores “rational strat-egies for profiting in this terrifying new environment.”

Alpha Trading: Profitable Strategies That Remove Directional RiskPerry J. KaufmanHardcover, 320 pagesJohn Wiley & Sons

How do you make profitable trades when there are no

obvious trends? This book addresses the realities of trading “when markets make no sense, when price shocks cause diversification to fail, and when it seems impossible to hedge[.]” Author and trad-ing system developer Perry Kaufman presents strategies and systems for profit-ably trading in directionless markets, as well as those experiencing constant price shocks. Among its topics, the book details how to exploit new highs and lows, hedge primary risk components, find robustness, and craft a diversification program.

TradeStation Made Easy: Using EasyLan-guage to Build Profits with the World’s Most Popular Trading SoftwareSunny J. HarrisPaperback, 744 pagesJohn Wiley & Sons

Endorsed by TradeStation Technologies, the book’s goal is to cover the essence of programming in TradeStation’s EasyLan-guage and provide an easily understood guide to TradeStation that also provides tips for the user in designing a personal-ized trading system. Noting that TradeSta-tion’s computer language can be “confus-ing, especially for the novice,” the author focuses on a consistent set of data and an elementary system throughout. Putting the basics of EasyLanguage in perspec-tive, and accessible even to those with little computer experience, the book is designed to enable users to write simple and intermediate programs “that will ac-curately express your theories and ideas about whatever market interests you.”

Attacking Currency Trends: How to Anticipate and Trade Big Moves in the Forex MarketGreg MichalowskiHardcover, 304 pagesJohn Wiley & Sons

A guide for reading long-term trends in the foreign currency market, the book argues that to thrive in the marketplace, traders must “anticipate, enter, and stay with trends in the foreign exchange market.” The author explains the attributes of successful traders and discusses the tools and techniques traders need to read the markets and identify when a market is in a trend. Trade entry, position management, and exit techniques are also explored. Technical tools dis-cussed include moving averages, trend-lines, and Fibonacci levels.

Technical Analysis For Dummies, 2nd EditionBarbara RockefellerPaperback, 360 pagesJohn Wiley & Sons

Since the publication of the first edition of Technical Analysis

For Dummies, readers have been faced with many changes to the investment landscape, such as new interest rates, looming bank crises, and adjusting market climates. This updated edition includes information on the new indicators, hands-on applications for real-world situations, as well as practical examples to help investors make better trading decisions. Rockefeller goes beyond the fundamentals and helps readers spot investment trends and turning points, determine how mar-kets are performing and make decisions using real data, and improve profits and portfolio performance. ◆

Trader’s Bookshelf is a forum to announce new trading and financial books. Listings are adapted from company press releases and are not endorsements or recommendations from the Active Trader Magazine Group. E-mail press releases to: [email protected]. Publication is not guaranteed.


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TRADING Calendar


LEGEND

CME:ChicagoMercantile

Exchange

CPI:Consumerpriceindex

ECI:Employmentcostindex

FDD (first delivery day): Thefirstdayonwhichdeliveryof

acommodityinfulfillmentofa

futurescontractcantakeplace.

FND (first notice day): Alsoknownasfirstintentday,

thisisthefirstdayonwhicha

clearinghousecangivenotice

toabuyerofafuturescontract

thatitintendstodelivera

commodityinfulfillment

ofafuturescontract.The

clearinghousealsoinformsthe

seller.

FOMC:FederalOpenMarket

Committee

GDP: Grossdomesticproduct

ISM:InstituteforSupplyManagement

LTD (last trading day): Thefinaldaytradingcantakeplace

inafuturesoroptionscontract.

PMI:Purchasingmanagers

index

PPI: Producerpriceindex

Quadruple witching Friday: Adaywhereequityoptions,

equityfutures,indexoptions,

andindexfuturesallexpire.

March

1

Januaryconstructionspending FebruaryISMmanufacturingreport FND:Marchorangejuicefutures(ICE) FDD:Marchcrudeoil,naturalgas,gold,silver,copper,platinum,palladium,corn,wheat,soybeans,soybeanproducts,oats,roughrice,andT-bondsfutures(CME);Marchsugar,cotton,cocoa,andcoffeefutures(ICE)

2 FND:MarchheatingoilandRBOBgasolinefutures(CME)

3 Q4productivityandcosts FebruaryISMnon-manufacturingreport

4Februaryemploymentreport LTD:Marchforexoptions;AprilcocoaoptionsandMarchU.S.dollarindexoptions(ICE)

56

7 Januaryconsumercredit FND:Marchporkbelliesfutures(CME)

8 FDD:Marchheatingoil,RBOBgasoline,andporkbelliesfutures(CME);Marchorangejuicefutures(ICE)

9 Januarywholesaleinventories LTD:Marchcottonfutures(ICE)

10 Januarytradebalance

11Januarybusinessinventories Februaryretailsales LTD:Marchorangejuicefutures(ICE);Aprilcoffeeoptions(ICE)

1213

14 LTD:Marchcorn,wheat,soybeans,soybeanproducts,oats,androughricefutures(CME);Marchforexfutures

15FOMCinterest-rateannouncement FND:MarchU.S.dollarindexfutures(ICE) LTD:Marchlumberfutures(CME)

16FebruaryPPIandhousingstarts FND:Marchlumberfutures(CME) FDD:Marchlumberfutures(CME);Marchforexfutures LTD:Aprilplatinumoptions(CME);Marchcocoafutures(ICE)

17

FebruaryCPI,productionandcapacityutilization,andleadingindicators MarchPhiladelphiafedsurvey LTD:Aprilcrudeoiloptions(CME);Marchindexfutures(CME);Marchindexandequityoptions

18 LTD:Aprilorangejuiceoptions(ICE);Marchsinglestockfutures(OC)


RepoRT TImes

Economic release Release time (ET)

GDP 8:30a.m.

CPI 8:30a.m.

ECI 8:30a.m.

PPI 8:30a.m.

Productivityandcosts 8:30a.m.

Employment 8:30a.m.

Personalincome 8:30a.m.

Businessinventories 8:30a.m.

Durablegoods 8:30a.m.

Retailsales 8:30a.m.

Tradebalance 8:30a.m.

Housingstarts 8:30a.m.

ChicagoFednationalactivityindex

8:30a.m.

Production&capacityutilization

9:15a.m.

Leadingindicators 10a.m.

Consumerconfidence 10a.m.

UniversityofMichiganconsumersentiment

10a.m.

Wholesaleinventories 10a.m.

PhiladelphiaFedsurvey 10a.m.

Existinghomesales 10a.m.

Constructionspending 10a.m.

ChicagoPMIreport 10a.m.

ISMreportonbusiness 10a.m.

ISMnon-manufacturingreportonbusiness

10a.m.

Newhomesales 10a.m.

Factoryorders 10a.m.

Federalbudget 2p.m.

Consumercredit 3p.m.

Theinformationonthispageissubjecttochange.ActiveTraderisnotresponsiblefortheaccuracyofcalendardatesbeyondpresstime.

1920

21 Februaryexistinghomesales LTD:Marchcoffeefutures(ICE)

22 LTD:AprilcrudeoilandT-bondsfutures(CME)

23 Februarynewhomesales

24 Februarydurablegoods FND:Aprilcrudeoilfutures(CME)

25 Q4GDP(third) MarchUniversityofMichiganconsumersentiment

2627

28Februarypersonalincome LTD:Marchporkbelliesfutures(CME);Aprilnaturalgas,heatingoil,RBOBgasoline,gold,andcopperoptions(CME)

29Marchconsumerconfidence LTD:AprilnaturalgasandMarchgold,silver,copper,platinum,andpalladiumfutures(CME)

30 FND:Aprilnaturalgasfutures(CME)

31Februaryfactoryorders MarchChicagoPMI FND:Aprilgoldandplatinumfutures(CME) LTD:AprilheatingoilandRBOBgasolinefutures(CME)

April

1MarchemploymentreportandISMmanufacturingreport Februaryconstructionspending FDD:Aprilcrudeoil,naturalgas,gold,andplatinumfutures(CME) LTD:Aprillivecattleoptions(CME);Marchcocoaoptions(ICE)

234 FND:Aprilheatingoil,RBOBgasoline,andlivecattlefutures(CME)

5 MarchISMnon-manufacturingreport

67 Februaryconsumercredit

8Februarywholesaleinventories FDD: AprilheatingoilandRBOBgasolinefutures(CME) LTD:Maysugarfutures(ICE);MaycoffeeandcottonoptionsandAprilU.S.dollarindexoptions(ICE)

TRADE Diary


Goinglongafterabearish

weekinthecrudeoilmarket.

TRADE

Date: Friday, Jan. 7, 2010.

Entry: Long March crude oil futures (CLH11) at 89.22.

Reason for trade/setup: This trade was based on a weekly pattern reflecting the market’s condi-tion at the close of the week ending Jan. 7: a lower weekly close and low with a high above the highest high of the previous four weeks. This seemingly mundane (and at first glance, bearish) pattern has appeared only 14 times over the past 10 years, but it was followed by fairly consistent bullish price action over the following 12 weeks: the market was higher at least 61 percent of the time after seven weeks, and the odds of a higher close after two weeks was better than 75 percent. The trade intended to capture this initial thrust.

A contributing factor is the market’s proximity to $100 — a conspicuous round-number price the market is likely to at least test. (Most analysts see low probabilities for extended or sig-nificant follow-through above $100 — see “Oil flirts with triple digits in new year” on p. 16.)

However, the trade does fly in the face of the market’s overall loftiness (it’s at its highest levels in more than two years) and the possibility of downside follow-through after a bearish week. The position was established on the Jan. 7 close. (Note: This was a paper trade.)

Initial stop: 87.74, below the established support around 88 and the Jan. 7 low of 88.45.

Initial target: 91.78. Take partial profits and raise stop. Secondary target: 93.

REsulT

Profit/loss: +2.56 (half position).

Outcome: In its first stage at least, this was one of those rare trades that couldn’t have worked out much better.

The market opened higher the Monday (Jan. 10) after the trade was entered, and the position was never in the red. The rally con-tinued the next day, and early in the morning of Jan. 11, the mar-ket rallied to 91.69 — just shy of the initial target — then pulled back slightly. Since this effectively constituted a fulfillment of the conditions for raising the stop-loss, the stop order was raised to 89.33 (a little above breakeven). When the market actually hit the target and traded up to 92 about an hour later, the stop was raised again to 90.06, locking in a profit on trade. ◆Go to www.activetradermag.com (Web only > Article follow-ups) after Feb. 7 to see the outcome of the second half of this trade.

Note: Initial targets for trades are typically based on things such as the

historical performance of a price pattern or trading system signal. However,

individual trades are a function of immediate market behavior; initial price

targets are flexible and are most often used as points at which a portion

of the trade is liquidated to reduce the position’s open risk. As a result,

the initial (pre-trade) reward-risk ratios are conjectural by nature.

Source:TradeStation

TRADE summARy

Date FuturesEntry price

Initial stop

Initial target

IRR Exit DateP/L

(point)P/L (%) LOP LOL

Trade length

Jan. 7 CLH11 89.22 87.74 91.78 1.73 91.78 Jan.11 2.56 2.87% 3.06 - 2days

IRR:initialreward/riskratio(initialtargetamount/initialstopamount).LOP:largestopenprofit(maximumavailableprofitduringlifetimeoftrade).LOL:largestopenloss(maximumpotentiallossduringlifeoftrade).

at-0311

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