Automated Trading Systems - The Technical Analyst · 2016. 11. 23. · in futures, stocks, forex...

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.technicalanalyst.co.uk wwwThe publication for trading and investment professionals

Automated Trading Systems

Institutional Fund Flows InterviewJohn Bollinger discusses his

bands and the markets

Drummond Geometry A powerful tool for

trend analysis Institutional investors adopt

defensive strategy

First steps in model buildingMinimising drawdowns Algorithmic execution

This advertisement is intended for institutional investors who subscribe to The Technical Analyst magazine. It is directed at persons having professional experience in matters relatingto investments, and it relates to investments which are only available to, and will only be engaged in with, such investment professionals. Persons who do not have professionalexperience in matters relating to investments should not rely on this advertisement. This advertisement has been issued by Barclays Global Investors Limited (“BGI”), which is authorised andregulated by the Financial Services Authority in the United Kingdom (“FSA”). iShares plc and The Exchange Traded Fund Company plc (the “Companies”) are investment companies with variable capitalincorporated in Ireland and are authorised by the Financial Regulator in Ireland. The iShares funds are authorised by the Financial Regulator in Ireland. Any application for shares in any fund is on theterms of the relevant prospectus. The iShares funds may not be registered in your jurisdiction. In particular, none of the shares has been or will be registered under the United States Securities Act of1933, or as an investment company under the 1940 Act, or the laws of any of the states of the United States, and, therefore, may not be offered or sold, directly or indirectly, in the United States or toor for the account of any U.S. Person, as defined by the 1933 Act, except pursuant to an exemption form, or in a transaction not subject to, the regulatory requirements of the 1933 Act, the 1940 Actand any applicable state security laws. In addition, the Companies have not been, nor will they be, qualified for distribution to the public in Canada as no prospectus for the Companies has been filedwith any securities commission or regulatory authority in Canada or any province or territory thereof. This document is not, and under no circumstances is to be construed, as an advertisement, or anyother step in furtherance of a public offering of shares in Canada. No person resident in Canada for the purposes of the Income Tax Act (Canada) may purchase or accept a transfer of shares in theCompanies unless he or she is eligible to do so under applicable Canadian or provincial laws. This advertisement is not intended to constitute an offer to sell or a solicitation of an offer to buy shares ofany fund, nor shall any such shares be offered or sold to any person in any jurisdiction in which an offer, solicitation, purchase or sale would be unlawful under the securities laws of such jurisdiction.BGI and/or its affiliated companies and/or their employees may, from time to time, hold shares in the funds included in this publication or any underlying shares heldwithin the funds, and may as principal or agent buy or sell the funds or securities. Copies of the relevant prospectus can be obtained from www.iShares.net or by calling+44 (0)20 7668 8007. “iShares” is a trademark owned by Barclays Global Investors N.A. © 2006 Barclays Global Investors Limited. All rights reserved.

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CONTENTS 1 FEATURES

NEW section on trading models and algorithmic execution.

Drummond GeometryAn original trend following technique

developed by legendary trader, Charles Drummond.

InterviewJohn Bollinger

"If someone comes up with a new indicator, there's no point in concealing the maths behind it"

SEPT/OCT

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WELCOMEIn this issue we are proud to launch a new section devoted to automated trading

systems. Our aim is to bring to our readers the latest research and market developments in all areas of automated trading, from model building and testing

through to algorithmic execution strategies. Technical analysis often plays an important role in the development of trading models and automated strategies,

and so we believe these new pages will be an exciting addition to the publication.

We hope you enjoy this issue of the magazine.

Matthew Clements, Editor

September/October 2006 THE TECHNICAL ANALYST 1

www.tradingtechnologies.com

“At least 50% of the electronic volume on the world’s top four futures exchanges goes through TT’s X

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order-entry platform. From a trader’s viewpoint, that speaks for itself.”

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Editor: Matthew ClementsManaging Editor: Jim BissAdvertising & subscriptions:Louiza Charalambous Marketing: Vanessa GreenEvents: Adam CooleDesign & Production: Paul Simpson

The Technical Analyst is published byClements Biss Economic Publications LtdUnit 201, Panther House,38 Mount Pleasant, London WC1X 0AN

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PRODUCTION

Art, design and typesetting by all-Perception Ltd.Printed by The Friary Press

ISSN(1742-8718)

INDUSTRY NEWS

MARKET VIEWS EUR/USD: Further gains aheadUS Stocks: Brighter outlook for medium term

EXCHANGE FEATUREJohannesburg Stock Exchange

TECHNIQUES Drummond Geometry & trend analysisInstitutional fund flows: A different approach to volumeDirectors' deals: Early signals for the stock marketWyckoff method confirms 14,400 target for DJIAA technical approach to pairs trading

INTERVIEWJohn Bollinger of Bollinger Capital Management

SOFTWAREUpdata Technical Analyst for Bloomberg

BOOK REVIEWThe Investor's Guide to Active Asset Allocationby Martin Pring

AUTOMATED TRADING SYSTEMSBuilding a trading model: First stepsTrading models: Minimising drawdownsAlgorithmic execution: Technology is key

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CONTENTS 2 REGULARS>

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Do company directors make smartinvestors?

"80% of the total value traded in SingleStock Futures is institutional"Allan Thomson, JSE director of trading


4 THE TECHNICAL ANALYST September/October 2006

Industry News

ASPEN GRAPHICS NOW USING BLOOMBERG DATA

Aspen Research Group, the USbased technical analysis softwareprovider, is now offering its AspenGraphics charting package in a for-mat that can be powered byBloomberg Data. This means thatany Bloomberg field that has histori-cal data can be integrated into anAspen formula to chart or quote thatfield's value. Aspen are also offeringup to 299 separate buy/sell alerts viaan audible alarm, pop up window,text window or text message

New indicator for CBOT's Market ProfileA professor from Western IllinoisUniversity has developed a tradingsystem based on the CBOT's MarketProfile. Professor Thomas Drinka,who was the first - and remains theonly - academic to offer courses inMarket Profile as part of a curricu-lum, and who is supported by theCBOT, believes he has an importantnew set of indicators to add to thetechnical analysis toolkit.

The Profile Directional Index,which he developed with one of hisstudents, consists of two algorithms

- the Buying-and-Selling Index andthe Price Index. Together they areused to generate risk-accounted trad-ing signals. Of the 40 agriculturalfutures that were included in betatesting, Professor Drinka says thattrading signals were over 70% accu-rate for 37 futures and in the case of17 futures, 100% accurate. ProfessorDrinka is seeking a business partnerto help in commercial development.

Email: [email protected] fortest results and further details.

US based FX trading platform,Interbank FX, has launched its newautomated trading platform, ExpertAdvisors. The company claims itsplatform is one of the few in theworld that offer the ability for clientsto automate their trades by program-ming their own algorithms into thesystem. Expert Advisor notifies theusers of buy and sell opportunities,backtests trading strategies and canalso execute orders automatically.Written in MetaQuotes Language II,the company say little or no pro-gramming experience is required touse the platform. A step-by-stepguide is provided in the MQLIIusers manual.

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“Elliott wave forecasting has enabled Prechter to make some remarkably accurate calls. In January of last year, for example, he predicted gold would soon peak at just over $500 an ounce. It hit $511 on Feb. 15 and within two weeks fell to $408.”- Money Magazine

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Market Views

EUR/USDFURTHER GAINS AHEAD by Thomas Anthonj

Short term outlookFollowing a classic 3-step A-B-C con-solidation pattern from the last majortop at 1.2980 in June down to the lastmajor bottom at 1.2460 in July, we seethe odds clearly in favour of a resump-tion of the bigger up-trend for the euro(see Figure 1). This will require decisivebreaks above the last Fibonacci resist-ances (76.4 %) at 1.3045 and at 1.3185to eliminate the head-and-shouldersformation. A trend line break at 1.2705however, would delay a straight attackon the last 1.2980 top and would callfor a slightly deeper setback to 1.2640or 1.2570 (61.8/76.4 % of the last

advance) before a resumption of theup-trend. Only a break below 1.2570would offer significant downwardspotential towards a massive supportzone that stretches from 1.2405 (inter-nal 50%) to 1.2325/1.2265 (potentialwave (1) top/internal 61.8%), to trendline support at 1.2205. If this fails thenwe'd only have the last Fibonacci sup-ports (76.4%) at 1.2100 and 1.1955 toprevent a complete meltdown. Such abreak would confirm that a bigger C-leg down (in blue) is unfolding, whichwould target around 1.1000. The oddsare still in favour of a straight resump-tion of the bigger EUR up-trend as

long as short term support between1.2705 and 1.2570 stands firm.

Long term outlookThe fact that the market bottomed outat the 38.2 % retracement of 1.1635(calculated from the 0.8350 low) andwent on to form a series of sub-countson the way up to 1.2980 raised somedoubts as to whether this was the rightshoulder of a head-and-shoulders pat-tern (Figure 2). The double-top thatformed at the potential left shoulder at1.2930 means the bigger pictureremains unclear. However, we see apositive bias prevailing as long as

Figure 1.

→→


Market Views

Figure 2

an internal 50 % retracement at 1.2405and an internal wave (1) top at 1.2325are not broken. Below 1.2325, onlytrend line support at 1.2170 and the lastFibonacci-support at 1.1955 could pre-vent the resumption of the bigger con-solidation targeting 1.1010 to 1.0765

(50% of old bottom) in a corrective C-leg down (in blue). On the upside, wesee Fibonacci projections at 1.3715 and1.4210 although it would require stabi-lization above 1.3185 (76.4% of the1.3665-1.1640 decline) to eliminate thelast doubts that this is not just a count-

er-trend rally within a bigger down-consolidation or within a new down-trend.

Thomas Anthonj is a technical ana-lyst at ABN Amro.

“IF THE TREND LINE SUPPORT AT 1.2205 FAILS THEN WE'D ONLY HAVE THE LAST

FIBONACCI SUPPORTS AT 1.2100 AND 1.1955 TO PREVENT A COMPLETE MELTDOWN.”


Market Views

US STOCKSBRIGHTER MEDIUM TERM OUTLOOK by Riccardo Ronco

Short term viewThe S&P500 is challenging its Mayresistances in the 1,300-1,320 area(Figure 1). While prices have been ableto climb back to their respective 50 and200 day moving averages, they havedone so on lower volume from the 2billion shares peak seen in mid July.Higher prices on lower volume are notusually good in technical analysis: suchpatterns indicate investors are less andless keen to pay higher prices and this isa leading indicator of weakness.

The NASDAQ Composite has ralliednicely off its 2,025 relative low but it isnow facing its 200 day moving averageat 2,225. Volume has declined witheach passing week since July for thismarket as well. The contraction in vol-ume has affected both the advancingand declining 10-day volume indicatorscalculated for the NYSE and NAS-DAQ Composite. The good news isthat this rally has not generated a spike

in optimism and our short-term indica-tors are not overbought.

Several internal indicators like theVIX in the 12-13 area are quite com-pressed to allow further upside in thestock market in the short-term.

Put/call ratiosThe 10-day S&P100 put/call ratio isanother indicator that we have found tobe very useful when trying to under-stand what the smart money is doing.The S&P100 put/call ratio is a contrar-ian indicator in a similar way to the"Equity only" put/call ratio: the differ-ence is in whom is trading what.S&P100 (OEX) options are mostlytraded by large investors to hedge theirportfolios while retail investors tend tospeculate on single stocks. Higherprices in the stock market are usuallyassociated with lower put/call ratiosand vice versa. Sometimes this perfectinverted correlation breaks down for

the S&P100, specifically near 2-3month tops in the market. Since lateJuly the S&P100 put/call ratio has ral-lied together with prices, suggesting thechances of a medium-term top arehigh. Recent examples were seen inMay this year and September 2005.

When considering sentiment indica-tors like the American Association ofIndividual Investors data, any beneficialeffects of a double spike in pessimism(as seen in the AAII weekly figures inmid June and mid July) have run theircourse (4-6 weeks upside is the averagerally). The conclusion in the short-termis for a gentle pullback into a lateralcongestion phase: I would look for aretracement to the 1,280-1,260 rangeon the S&P500 and 2,140 - 2,100 onthe NASDAQ Composite.

Medium term viewThe medium term outlook is moreoptimistic for the following reasons:

The NYSE Advance/Decline line isstill strong while the NASDAQ linecontinues to be weak because of thetech-aversion that is still palpableamongst investors

Since early August the number ofstocks making fresh 52-week newhighs has been consistently higherthan those making 52-week newlows

Liquidity in US mutual funds(according to the most recentInvestment Company Institutedata) has risen in the last two monthrally. Hence there are resources tosupport the market in case of adecline and we are far fromFigure 1.

1.

2.

3.

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Market Views

those worrying levels of low cash asseen in early 2000.

The stock market also remains cheapwhen a comparsion is made betweenthe S&P500 yield and the 10-year T-note yield (Figure 2). Crashes usuallyoccur either when valuations are over-stretched (as in 1987) or when investorsare throwing in the towel following oneor two years of declining prices. We arenot in any of the above two situations.The nearest parallel we can find is late1994 to early 1995. Then higher pricesin equities were followed by an evenhigher level of cheapness in our spreaddue to the fact that prices were not ableto keep up with the pace seen in earn-ings. A lateral consolidation followedand the same should happen this time.A stronger bond market is going tosupport the market and not vice versa.

Meanwhile, a more traditional techni-cal indicator like the Moving Average

Divergence/Converge (MACD) calcu-lated on the monthly S&P 500 trig-gered a sell signal at the end of August.However we have a flat move on thisindicator that could lead to a lateralconsolidation rather than to a sharpcorrection into the usual seasonalSeptember-October lows. Another pos-itive element is the extremely oversoldcondition of tech stocks vs. the NYSEComposite: our weekly momentumindicator in the above chart is flashing apositive signal, as was seen in October

2004 and May 2005, suggesting a mar-ket more resilient than we imagine.

Riccardo Ronco is technical analystat Friedman Billings Ramsey.

The views and opinions expressed above maybe subject to change at any given time.Individuals are advised to seek professionalguidance prior to making any investments.The value of investment may fluctuate. Pastperformance is not an indication of futureperformance.

“SINCE EARLY AUGUST THE NUMBER OFSTOCKS MAKING FRESH 52-WEEK HIGHS IS CONSISTENTLY HIGHER THAN THOSE MAKING 52-WEEK

NEW LOWS.”

Figure 2.

GET QUALIFIED IN TECHNICAL ANALYSIS

For more information on how to join and what is involved in passing

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The Society of Technical Analysts (STA) represents and accredits professional and private Technical Analysts operating in the UK

Originally established in the 1960s, the STA provides its members:• Education Monthly lectures and regular teaching courses in technical analysis

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in Technical Analysis


Exchange Feature

MC: What are the recent developmentsat the exchange?

AT: In the past few years we have seenthe assimilation of the South AfricanFutures Exchange (SAFEX) within theJSE in 2001, and in 2005, the launch ofour interest rate market, Yield-X, andde-mutualisation with the subsequentlisting of the exchange on its mainboard this June. The exchange is cur-rently engaged in a significant projectto revamp most of its IT systemsincluding new trading and clearing sys-tems for all JSE markets. Last but notleast is the continued growth in singlestock futures (SSFs) trading.

MC: How has the market for SSFsgrown in recent years?

AT: The growth of the market has seenvolumes rise from almost nothing fiveyears ago to 8,000,000 contracts amonth by mid 2006. We are now thethird largest market globally for singlestock futures after Eurex and India.Having started with 4 shares in 1999,we now have 249 listed contracts worthR64bn in 2005. As yet, we don't havedata for 2006 but it will show a signifi-cant increase on this figure. However,we know that SSFs are now approxi-mately 30% of total JSE trade. Finally,we mustn't forget that the market forSSFs is also growing globally with newlistings on the Spanish MEFF, UK's

SOUTH AFRICA'S JSEby Matthew Clements

Just prior to the Technical Analyst's recent Johannesburg conference, I paid a visitto the Johannesburg Stock Exchange at it's impressive new building in the heart ofJohannesburg's financial district to meet with their director of trading, AllanThomson. He explains how the South African market is now seeing spectaculargrowth in the market for single stock futures, a development spearheaded by theexchange.

Allan Thomson


Exchange Feature

LIFFE and One Chicago.

MC: What has been the impetus forthe market growth?

AT: The growth of single stock futuresmarket in South Africa is the result ofseveral factors: a healthy privateinvestor market, a well developmentfund management and capital marketssector plus effective product promo-tion by the JSE. We have spent the pastseveral years actively developing thedomestic market for single stockfutures and SSFs are now well estab-lished in the retail market. This reflectsnot only the work the exchange hasdone to develop the market but also thedepth and sophistication of the SouthAfrican equity markets.

MC: What are the specific benefits oftrading SSFS?

AT: The major benefits of exchangetraded SSFs is that they can be shortedand there is no counterparty risk. Also,users can enjoy greater exposure via thegearing offered by the futures andlower costs than trading the underlyingshares.

MC: Who are the primary users ofSSFs, the retail or institutional markets?

AT: Through the JSE's marketingefforts, SSFs were launched very muchwith the retail and private investor mar-ket in mind, but the institutional side ofthe business now dominates by far.Although 80% of volume traded is onthe retail side, 80% of the total valuetraded in SSFs is institutional. Unittrusts are now using SSFs extensivelyalthough legislative changes whereneeded here first before that could hap-pen.

MC: Who are the major players in themarket?

AT: The major domestic players areNedbank who started as the marketmaker for SSFs. All banks now trade

the futures although Standard Banknow has its own online trading facility.Other big players include Investec fromthe wholesale side and RMB who mar-ket make exclusively to fund managersand other members.

MC: How are SSFs commonly used?For hedging or speculation?

AT: That's very difficult to ascertainbecause we don't ask our customerswhat they use them for. Institutionalusers include equity traders, asset man-agers and hedge funds and their appli-cation of SSFs is probably split 50:50between the two. Unit trusts, for exam-ple, use them both as a hedging tooland for yield enhancement. The retailmarket is more speculative but there isa hedging use in this sector as well.From a hedging perspective, SSFs allowrisk reduction by protecting a shareportfolio against movements in theunderlying market. Speculators, on theother hand, have no intention of everdelivering the underlying and simplylook to exploit movements in thefutures price although this, of course, isbased on movements in the underlying.

MC: Are there any specific trading

strategies that can be used when tradingSSFs?

AT: From a technical analysis perspec-tive, it goes without saying that whentrading a highly geared product such asSSFs on a short-term basis, technicalanalysis is a tool which many tradersuse. Technical analysts usually use thedata of the underlying share in order todraw their trading conclusions. Theythen use the SSF to obtain their expo-sure in that share. Liquidity can be spo-radic which does have some implica-tions for how they are traded. The top40 SSFs are liquid contracts but we nowlist 249 futures and a lot of the tradesat the lower end of the liquidity spec-trum are structured transactions.However, if there is insufficient liquid-ity in the future then you can look atthe underlying share to analyse the mar-ket.

MC: How far out do the contracts go?

AT: The contracts go out as far as any-body wants them to. We have contractsgoing out to 2010 but obviously mostof the liquidity is in the near contractswhich are rolled over as expiryapproaches. →→


Exchange Feature

MC: What competition is therebetween the market for SSFs andexchange traded funds (ETFs) whichyou also offer?

AT: There is definitely competition, aswell as from CFDs. There are impor-tant differences though. From a specu-lative point of view, SSFs can offermore flexibility than exchange tradedfunds, because you can go short. SSFsoffer you gearing and exposure. ETFsare basically long only instruments.

MC: What is the JSE approach to elec-tronic trading?

AT: All five of the JSE's Markets (MainEquity Market, AltX, EquityDerivatives, Agricultural Derivativesand Yield-X) all operate on central elec-tronic order books. The exchangebelieves in ensuring maximum trans-

parency with efficient price formation.Members have access to the market andmay also offer their clients accessthrough DMA (Direct Market Access)type facilities. The equities market andAltX use the London Stock Exchangeplatform run, and operated, out ofLondon on behalf of the JSE.

MC: What is the state of platform con-nectivity to the exchange?

AT: Members mainly connect via dedi-cated lines into the JSE in South Africa.As indicated, all the trading systems arebeing replaced during 2007. The equi-ties will be replaced with the LSE's newplatform and the derivatives and Yield-X markets will also be replaced usingthe existing local supplier.

MC: How has the JSE adjusted to thegrowth of electronic and automated

trading in recent years?

AT: A lot of automated trading is com-ing through the exchange and the highvolume associated with such tradinghas caused some problems for us, as ithas for many other exchange platforms.This is simply because of insufficientbandwidth. We need to publish real-time single stock futures prices on ourscreens as the underlying price changesand this is very demanding on our sys-tems. However, the platform and ITsystems are currently being upgradedand this process will be completed overthe next few months. This will be amajor development for the exchangeand a big advantage for our customers.It also sets us up for the future as trad-ing volumes grow and the SouthAfrican markets continue to develop.

The new JSE building in Sandton


Techniques


Techniques

A London based fund manager, run-ning a North American fixed incomeportfolio says, "I have been usingDrummond for around 14 years andthere is no question that it is profitablefor me. Having tested moving averages,Elliott Waves and such like, thesehaven't worked as well although that'spartly a matter of trading style compat-ibility. Drummond works well at spot-ting market turns and has a consistencythat's hard to match whether you aretrading on a daily, weekly or monthlybasis. The backtesting that I have doneshows around a 65 percent reliabilityfor the studies."

The key elements of DrummondGeometry include a combination ofthe following three basic categories oftrading tools and techniques:

A series of short-term moving averages (PLdot)Short-term trend lines Multiple time-period overlays

The PLdot (Price Line dot) can beapplied to any commodity, future orstock and is a short-term moving aver-age based on three bars of data whichcaptures the trend/non-trend activityof the time frame being charted. The

PLdot from the last three bars is plot-ted as a dot or line on the next bar toappear. PLdot is calculated from theaverage of the high, low, and close ofthe last three bars.

The PLdotThe PLdot plots successive dots onprice bars forming a series of pointswhich describe the consensus of mar-ket activity for the three latest bars (ortime periods). The PLdot moves in astraight line when the market is in atrend, but moves horizontally acrossthe page in congestions. Its sensitivityto markets trends means it is very quickto register the change of a market outof congestion into trend as well as to atrend that is ending.

Figure 1 shows the weekly S&P 500

with the PLdot moving in a relativelystraight line horizontally across thepage on bars 3, 4, 5, 6, 7 and 8. Then wesee a short down trend and followingthat the dots move in a straight lineupward for the last 5 bars of the chart.The tendency of the PLdot to move ina straight line can be helpful in moni-toring a trend.

A basic strategy to use for PLdot is totrade with the trend if the market is onone side of the dot. In Figure 1 we seethe close of the bar on alternating sidesof the PLdot in bars 4, 5 and 6. Thisindicates the market is in congestion. Inbars 6, 7, 8 and 9, we see closes belowthe PLdot indicating trending activityto the downside. In bars 10 through 14we see each bar close above the PLdot,indicating a trend to the upside.

Figure 1. S&P 500

Drummond Geometry(DG) is a form of mar-ket analysis developed by

Canadian trader CharlesDrummond. It is both a trend-fol-lowing and a congestion-actionmethodology using projectedcharts to map future market activ-ity.

DRUMMOND GEOMETRY:AN ALTERNATIVE APPROACH TO TREND ANALYSIS

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Techniques


Trend reversalsFigure 2 shows the daily T-Bondfutures with two trend reversals. Frombars 3 and 4 we saw the market in adown-trend and the PLdots were abovethe close of each bar. The trading strat-egy would be to sell resistance. But bybar 5 we saw the market close abovethe PLdot and this marked the end ofthe down-trend. As the market movedinto the up-trend, the PLdot switchedsides; we do not see a close on theunder side of the dot until bar 12 whenthe close moved decisively under thePLdot and the trend is over. From bars5 to 12 the strategy is to buy support.Note that the dots move in a straightline until the trend is over.

As Figure 2 illustrates, prices oftenmove away from the PLdot, but thencome back to it. The pattern in Figure3 is called the "Return to the PLdot"and is a very simple, tradable pattern.The trick is to know exactly whenprices are actually far from the dot. Onthis chart we see a number of barsmarked with the "Return to the PLdot"yellow marker. When prices move faraway from the dot, the trader would bealert to signs that the market will turnand return to the PLdot. Thus in thefourth full bar we see that the market isfar away from the PLdot, but in thenext nine bars we see good examples of

this tendency for price to return to thevicinity of the PLdot. In each of thesesituations the trader would take a posi-tion against the trend by going short atthe apex of the bar.

The PLdot pushAnother observation based on the

PLdot is the "PLdot Push." In this pat-tern, when a trend is underway, the

PLdots seem to be pushing the bars inthe direction of the trend, eitherupwards or downwards, depending onthe direction of the move. If the dotspush strongly, they create a very strongtrend; if they sometimes lose energy,the trend weakens.

Figure 4 is a quarterly chart of theS&P500 where we see the "PLdotPush" pattern at work in a strong up-trend. The PLdot gives traders a greatdeal of support in trending markets.When an up-trending market retracesto the area of the PLdot the trader goeslong or adds to his long position. Whenin a down-trending market the tradergoes short or adds to his short position.When the market moves to a positionfar away from the dots, the trader takespartial profits or reverses position,depending on his or her trading style.Thus in Figure 4 we can see that thetrader could initiate or add to a longposition at any time that the marketretraced to the PLdot. The concept alsoholds for the "live dot" as well, asshown in the last two bars on the chart.(The "Live dot" is an advanced conceptin Drummond Geometry that indicatesthe point on the current bar where thePLdot for the next bar is forming.)

Short term trend linesThe second element of DG is the useof short-term, two-bar trend lines. Likethe PLdot these short-term trend linesare projected into the future where theyindicate points of interest on the firstupcoming bar - the future bar that hasyet to trade. The "Drummond Lines"indicate areas of energy terminationwhere the market it likely to stop itsmovement. Figure 5 shows five pricebars for the DJIA. The trend is definedand supported by the PLdots while theDrummond termination lines forecastthe extremes of the bars. The greenareas above and below bar five showthe support and resistance zones. Thesezones are defined by the DrummondLines (marked in turquoise).

Although it is obviously very helpfulto know where support and resistancewill form in the upcoming bar, this

Figure 2. T-Bond future

“THE KEY IS TAKING THE LOW

TIME FRAMES FORSMALL RISK AND

THEN IDENTIFYINGWHEN A TREND

BEGINS ON AHIGHER

TIME FRAME ONTHE DAILYCHARTS.”

SHAUN DOWNEY, CQG


Techniques

information alone is not enough totrade successfully. As with any othertrading techniques, the key question is,will the support or resistance hold orbreak? The coordination of supportand resistance in different timeframes isthe third major tool of DG. ShaunDowney, chief technical analyst atcharting provider, CQG, lectures onDrummond Geometry and comments,"The key is taking the low time framesfor small risk and then identifying whena trend begins on a higher timeframeon the daily charts. Normally themonthly highs and lows are made earlyin the month in a trend and getting thatnailed is one of the key moments.There really shouldn't be any timewhen you don't identify a trend andthen be able to ride it". This will be thesubject of a future article.

There are over 200 DrummondGeometry studies available onTradeStation. For additional infor-mation please contact Ted Hearneat www.tedtick.com. All Tedtickinformation is subject to copy-right.

Figure 3. Return to the PLdot

Figure 4. The PLdot push

Figure 5.

“I HAVE BEENUSING

DRUMMOND FOR14 YEARS ANDTHERE IS NO

QUESTION THAT ITIS PROFITABLE

FOR ME.”

A LONDON BASED PORTFOLIO MANAGER

Techniques


Many traders and analystsincorporate some form ofvolume analysis in their deci-

sion-making. Volume takes variousforms, but one that is as yet still littleused but is rapidly coming to the fore isinstitutional fund flows. This articlelooks at how one particluar flows indi-cator, published by State Street, can beused to help anticipate market move-ments in global equity markets.

Flow analysis: the underlyingideaAs the term indicates, institutional fundflows are the volumes that are traded byinvestment managers, such as assetmanagers and pension funds. In manycases, the large asset managers are thedriving force behind share price move-ments since they hold huge positionsand may take time to get into a particu-lar sector or stock. In other words, ifthe institutional investors head in a par-ticular direction, this is likely to havethe effect of driving up share prices onaccount of the large volumes tradedover an extended period of time. Thequestion that arises however is, howcan we know what the large institutionsare buying and selling?

In order to answer this question weneed to turn to the stockbrokers. Theyact for the institutional investors andsettle a high proportion of all institu-tional equity transactions. Such brokersinclude The Bank of New York andState Street. State Street is the world-wide administrator of over 11 trilliondollars, representing 15% of the totalvolume of tradable securities.Therefore, they are eminently wellplaced to measure the flows generatedby asset managers.

Every month, State Street GlobalMarkets research draws up a reportwith a detailed analysis of institutionalplayers' equity flows. State StreetGlobal Markets measures the aggregatevolume by calculating the balance ofpurchases minus sales in each equitysector (see Figure 1). This is termed theEquity Flow Indicator (EFI), or"flows" for short. The EFI showswhether institutional investors are infact making purchases or sales with theflows being subdivided into countries,sectors and regions. This makes it pos-sible to respond to the sectoral choicesmade by institutional investors in cer-tain regions.

Do flows have predictive value?The question naturally arises as towhether the flows have predictivevalue. Over the past ten years, StateStreet Global Markets has analysed theflows of institutional investors. If theflows were to be random, the expecta-tion would be for an average flow (pur-chasing or selling) to last two months(see Figure 1). In fact, the flows lastmuch longer on average, thus suggest-ing that they have an effect on the mar-ket.

The ability to identify a trend reversalin the cumulative flows in the sectors atan early stage can be highly profitable.An example of the cumulative flows inthe Telecom sector is shown in Figure2. The pale line shows the cumulativeflows: institutional investors are clearlymaking net sales in telecom sectorshares. The dark line shows the relativeperformance of the sector in relationto the world index. A reversal in theflow trend is often associated with aturnaround in relative performance.

This is exceptionally useful forinvestors in a position to make use ofsector rotation. Tim Viner, at StateStreet Global Markets adds, "We makeportfolio recommendations using theEFI indicator. For example, if we see aflow change then we consult other fac-tors such as valuation, earningsmomentum and technicals. If they sup-port the message from flows then weadjust our position. It is essentially atop down approach".

What are the flows saying atthis point?We now know that flows can have pre-dictive value, which begs the questionas to what the flows are saying at thispoint. In order to obtain more insightinto the flows, State Street GlobalMarkets publishes daily "Tornado"charts (see Figure 3). This chart showsthe flows over three periods: the lastweek, the last month and the last sixmonths. In this way, the analyst obtainsan insight into the flows and it is possi-ble to respond in good time to a flowturnaround. The flows for the energysector, for example, are declining for allthree time periods. This indicates thatinstitutional investors are making heavysales in energy shares, although this isnot yet reflected in the relative per-formance of the energy sector, which isstill positive.

Apart from the notable outflow in theenergy sector, the Tornado chart alsoindicates that institutional investors arebuying shares in the consumer staples,telecom and utilities sectors. Theseflows clearly indicate that institutionalinvestors are engaged in risk-aversepositioning. This picture is further con-firmed by the large flows out of

INSTITUTIONAL FUND FLOWS:A DIFFERENT APPROACH TO VOLUME by Rob Brand

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the Consumer Discretionary and infor-mation technology sectors, bothnotably cyclical sectors that are expect-ed to do well when the economy isstrong. It is therefore clear from theflows that institutional investors areswitching out of cyclical sectors intomore defensive ones. As noted, threesectors stand out: consumer staples,telecommunications and utilities. Thecumulative flows in these three sectorsare depicted in Figure 4. The stronginflows into these three sectors clearly

indicates that the Institutions havebecome less confident about the econ-omy.

Needless to say, State Street GlobalMarkets also breaks the flows down byregion. This can provide a particularadvantage for investors seeking to takeadvantage of regional effects. Theflows within the regions are interestingin themselves: positive for Europe andnegative for the US, (see Figure 5). Thisis consistent with the relative perform-ance of the two regions in recent

months: underperformance by the USand outperformance by Europe. Whatdoes stand out is the strong outflowfrom emerging markets, one of theregions in the State Street GlobalMarkets model. This outflow is howev-er limited to the most recent week andmonth so that it remains to be seenwhether the six-monthly indicator willalso be negative. A fall in emergingmarkets is also often associated with aweaker economic climate, which wouldbe consistent with the other flow sig-nals.

Regime analysisIn order to give the analysis furthersubstance, State Street Global Marketsalso conducts a regime analysis. Thisanalyses the relationship between theflows and a number of fundamentalfactors such as dividend yield, beta,earnings growth expectations and rela-tive valuation. The advantage of thisadditional analysis is that apart from thesignals we obtain from the flows, wealso derive an impression of the kindsof shares being bought and sold byinstitutions. This increases the insightinto the strategy behind the sectoraland regional allocation and can ulti-mately tell us something about the mar-ket in general. A good example of afundamental factor is the beta. Thismeasures the sensitivity of a share orsector in relation to the market.Investors are prepared to buy high betashares if they have positive expecta-tions of the market. Investors thereforeseek to position themselves cyclically inorder to benefit from their positive out-look. The flows have already allowedus to establish that Institutions are buy-ing shares in the consumer staples, tele-com and utilities sectors. That in itselfalready tells us that they are positioningthemselves more defensively. It is nowof interest to examine whether theregime analysis provides the same pic-ture.

The regime analysis of the flows indi-cates that investors are selling shareswith strong earnings growth expecta-tions and a high beta. Additionally, the

Figure 1. Average monthly flow per sector (Source: State Street Global Markets, MSCI)

Figure 2. Cumulative flows and relative performance in the Telecom sector (Source: State StreetGlobal Markets, MSCI)


Technique

flows also reveal that shares with a highdividend yield and a low relative valua-tion are being bought the most heavily.Is this logical? The answer is anemphatic yes, for the more defensivepositioning of equity portfolios byinstitutional investors is often associat-ed with the buying of shares with a(safe) dividend yield and a low valua-tion. The former factor may be clear,but the latter (valuation) is noteworthy- not so much because a value strategyin times of uncertainty is not a smartone, but particularly because this valuestrategy is something that has beenaround for a long time in equity mar-kets. Since the end of 2002, a valuestrategy (i.e. low PE) has generated ahigher return than a growth strategy(high PE). Analysts expected this trendto come to an end this year; the flowstherefore suggest the contrary.

ConclusionInstitutional fund flows offer a differ-ent and useful angle on volume. Theflows are able to provide us with atimely warning of a possible trendreversal in the different sectors. In thecase of an investor pursuing active poli-cies in respect of regions and sectors,the flows are an excellent aid to makingsuch allocation decisions. The flows aretelling us at the present time to be cau-tious about the equity market and toadopt a defensive portfolio allocation.

Rob Brand is a Chartered MarketTechnician (CMT) and employed asportfolio manager at ABN Amro

Figure 3. Tornado chart (Source: State Street Global Markets, MSCI)

Figure 4. Cumulative flows for the Staples (Source: State Street Global Markets, MSCI)

Figure 5. Tornado chart (Source: State Street Global Markets, MSCI)


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Techniques

Some institutional investors are scep-tical so few use the data systematicallyas part of their investment process. Inthe case of director buying, most fundmanagers will take a cursory look atheadline trading activity (such as shownin Figure 1) and may use it to hardentheir attitude to a particular stock butrelatively few use it to instigate a tradeor even as a trigger for further analysis.However, attitudes appear to be chang-ing.

Citigroup recently produced aground-breaking research article whichposed the questions; 'Are UK DirectorsSmart Investors?' As one of theauthors, Andy Moniz says, "Companydirectors are excellent market timers;they purchase shares on short-termweakness and sell on strength.Purchases potentially convey privateinformation to the market that hasn'talready been discounted."

Most attention tends to focus ondirector buying since, to put it crudely,it is the job of fund managers to findstocks that will outperform rather thanthe converse. A common belief is thatdirector selling takes place for a multi-tude of reasons rather than a firm con-viction than the shares are likely to per-form badly. As a result selling activity isperceived as a poor indicator. However,Andy Moniz disagrees. "While compa-nies with directors' sales, on average, do

not under-perform, we find the shareprices subsequently drift with the mar-ket." Khuram Chaudhry at MerrillLynch monitors aggregate directortrades as a bellwether of market senti-ment. He puts it more plainly. "Historyshows company directors have a goodtrack record of buying low and sellinghigh."

Using selective criteriaOur analysis of UK trading activitysince 1999 bears out both views andproves that following director tradingactivity has intrinsic value. The resultsshow that selling is less indicative thanbuying but both can lead to out-per-formance. However, these results areonly achieved by excluding the majorityof trades and focussing on those thatmeet certain criteria.

The move to more quantitativeinvestment strategies over recent yearshas opened the door to the inclusion ofdirector trading activity as a commonlyused measure in its own right. Forexample, stockbroker Martin Currieuses it as one of a number of factors intheir Dynamic Stock MatrixTM (DSM).The proprietary DSM is primarily ameans of measuring stocks using moretraditional quantitative factors such asPrice/Earnings ratios and other funda-mentals. Each factor carries a weightingwhich feeds into an overall stock scorewhich is used for screening. Thereafter,more traditional methods are used fordeeper analysis; this will include closerscrutiny of director trading activity if itshows up as a significant factor.

Quantitative methods such as this relyheavily on the quality of the data fedinto them which is why a rigorousreporting method is essential. For

example, an acquisition of shares by adirector may be for a multitude of rea-sons even if the issuer describes it as abuy. Directors buy due to contractualcommitments, reinvestment of divi-dends, vesting of options, or a sub-scription under a rights issue. Theseacquisitions should not carry the sameweight as a discretionary purchasemade on the market.

Even where a buy shows up as discre-tionary, there are sometimes mitigatingcircumstances. An incoming directorfor example is more likely to be buyingto demonstrate commitment to thefirm rather than because he has someinsight that the stock is particularlyundervalued at the time. A more obvi-ous secondary factor is the size of thetrade, the more money risked thestronger the conviction. However, ourevidence suggests that this is a less reli-able measure of the significance of atrade than the percentage change inholding.

For example, here are two trades fromthis month at Aim-listed stock:

1st September John Corre (Chairman)bought 100,000 at 8p bringing his holding

to 100,000.

5th September Foo Katan (Chief Executive)bought 126,000 at 12p bringing his holding

to 19million.

Significance ratingThough the trade by John Corre wasworth only £8,000, we gave it a signifi-cance rating of 70 on a 0 to 100 scale.This is because the change in holding(infinite) was much higher than it wasin the subsequent trade (1%). We ratedthe second trade at 40 even though

Common sense tells us thatthere is nobody betterplaced to value a company

than the people who run it. So,can tracking the trades of direc-tors lead to greater investmentreturns?

DIRECTORS’ DEALS:EARLY SIGNALS FOR THE STOCK MARKET by Michael Tindale

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Techniques


the amount of money being investedwas almost double. Corre has been onthe board for over two years so histrade cannot be excluded as a debutpurchase following his appointment. Inthis case, his trade apparently movedthe market albeit in a somewhat illiquidloss-making stock.

Composite measures, such as the sig-nificance score above can be used as ascreening tool in any quantitativemodel. Though it may be outweighedby other factors, Martin Currie's DSMwould increase the director dealing ele-ment of the rating if there was morethan one director buying. Multiplebuys at a company can be taken as astronger signal than any individualtransaction. Individual trades may bemotivated by all sorts of factors relatedto the circumstances of that director,but multiple trades are far less likely tobe.

Inevitably some directors are better attrading than others. Analysing the trad-ing history of a director can providevaluable context to a newly announcedtrade (see Figure 2). Many directors willbe, or have been, on the board of othercompanies as well.

Investing historyStuart Rose has proved to be one ofthe canniest investors in Marks andSpencer shares, investing large sums inthe once struggling retail monolithsince he took the helm. However, healso traded successfully at LandSecurities, Arcadia, and Big FoodGroup before that. He scores wellamong directors but not as well as hisnamesake Sidney Rose, Chairman ofWhittard of Chelsea who bought theshares all the way up from 28p to 100pin the two years to February 2003. Hesold them at 200p in May 2004. Some

of these companies may have disap-peared from screens but the tradinghistory of the directors is just as valid.Our analysis of director trading historymeasures the subsequent share pricemovement and accounts for the per-formance of the market. Thereafter,we aggregate not only each individual'strading history at a company, but theirtrades at other companies as well. Thisnot only gives results that are more sta-tistically robust, but it can temper theeffects of one market-beating-play.This data can be used to inform whichdirectors are worth following.

For example, Lord Burns who wasrecently appointed Chairman at Marks& Spencer and holds or has held posi-tions at Abbey, British land, Legal &General, and Pearson has a score of 23which puts him in the bottom quartileof UK directors. Along with most ofthe board, he made a profitable trade inMarks & Spencer last November hav-ing joined as Deputy Chairman the pre-vious month. However, this was onetrade among fifteen buys he has madeover the last eight years. He has madelittle aggregate profit in Pearson sharesand a substantial loss in Legal &General even accounting for the per-formance of the market since he lastbought in April 2000.

The Marks and Spencer trade has yetto stand the test of long term analysisbut in this case we would have dis-counted it because he had only justjoined the board and had a poor tradingrecord. However, other directors suchas his predecessor Paul Myners andChief Executive Stuart Rose were trad-ing at the same time. Both of thesemen have a better trading pedigreewhich puts them in the third quartile.

In addition to the trading history of adirector, we consider the timing of atrade as a further secondary factor for anumber of reasons. Investors at anylevel will first reach for a historic shareprice chart to put the price paid intocontext. Examples of directors callingthe low on a stock are two-a-penny;even Marks and Spencer fits the bill.However, we believe that the timing rel-ative to results announcements is

Figure 1.

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of equal importance.A large proportion of trading activity

takes place on the day results areannounced. One reason - which isexclusive to buy activity - is that direc-tors know that the trade will be morewidely reported at the same time as themedia is focussing on the company'sresults. The other is that when theresults are announced the two monthtrading embargo known as a ClosePeriod is lifted.

Close periodsIn our view, Close Periods offer someinsight into the timing of a trade butnot where the trade occurs at the end ofa Close Period. Unlike trades whichcoincide with results, when a directortrades in the days leading up to theClose Period the trade is less likely to bewidely reported because of an absenceof media focus. Though harder to spot,these trades are often more indicativethan those made when results are

announced since they are more low keyand are more likely to be made forpurely investment reasons.

Not surprisingly, directors are awarethat their trading creates interest andthose at smaller companies have beenknown to trade in unison in a vainattempt to get some headlines. We fre-quently get calls from financial PRcompanies seeking to ensure that thefull facts are reported.

Impact of legislationRecent legislative changes have also hadan affect. In the last year issuers havehad to report trades among seniormanagers as well as directors. At pres-ent, we exclude this from analysis sincethe data is too young. Furthermore, theEuropean dimension has started to takehold thanks to implementation of theEU 'Market Abuse Directive'. Thougheach market is going at its own pace inits own way, the data is available andhas become the focus of our efforts.

This dimension makes director dealingdata more accessible to funds with aPan-European focus.

The common perception among fundmanagers that sell trades are not indica-tive is erroneous although it is fair tosay that they are less indicative thanbuys. As with buys, the trick is to knowwhich trades to follow and which todiscount since there are around fiftytrades reported each day. In truth, veryfew of these are indicative.

Quantitative methods which are rou-tinely used on traditional stock assess-ment criteria can easily be deployed todirector trading data with a view tohighlighting indicative trades. However,as with other methods, quantitativeassessment alone is not enough. Thereare other factors which need to betaken into account to uncover a trulyindicative trade or series of trades.

Michael Tindale is manager atDirectors Deals.

Figure 2.


Techniques

In the February 2004 issue of theTechnical Analyst, I wrote an arti-cle, "A Test of Wyckoff", in which

was presented a point-and-figure chartshowing a price projection of the DowJones (DJIA) to 14,400.

This projection was based upon theWyckoff Law of Cause and Effect.This incorporates a procedure for usinghorizontal measurements or countswithin an accumulation formation tomake projections as to the probableextent of the subsequent price move.Those estimations of future pricepotential are invaluable in assisting thetrader in making reward-to-risk calcula-

tions.The 14,400 projection, to be proven

or disproved by subsequent action, wasto serve as a test of the Wyckoff Lawof Cause and Effect. Box 1 recaps thislaw and Figure 1 models the idealizedWyckoff stages, including the phase ofaccumulation followed by a phase ofre-accumulation. A detailed descrip-tion of Wyckoff's approach to figure-chart projections is in my count guidefor accumulation and re-accumulationphases (available from the TechnicalAnalyst). This article constitutes thesecond installment in the "Test ofWyckoff".

An interim market testWhen the DJIA broke above the top ofits 8-month trading range in November2005, a unique and powerful market-timing principle was at work. TheWyckoff Method's concept of the"Stepping Stone Confirming Count"states that when a sufficient point-and-figure count has been collected during alateral consolidation pattern to projectan upward price target equal to whathad been generated during the originalbase of accumulation, then an immedi-ate resumption of the upward bull mar-ket trend would begin. Both the baseof accumulation and the re-accumula-tion counts are measured horizontallyon point-and-figure charts.

The behavior of the DJIA during2005 was a case study in support of theWyckoff Method's "Stepping StoneConfirming Count" concept. Duringthe sideways market from March toNovember 2005, the DJIA was creatinga substantial figure chart count. Then,just when this re-accumulation countbecame sufficient to confirm the origi-nal upward price objective of 14,400,taken from the 2002-03 inverse-head-and-shoulders bottom, the bull marketuptrend resumed. (See Figure 1)

The "Stepping Stone ConfirmingCount" price projection to DJIA14,000 -14,450 is shown on the 50-point figure chart of the DJIA, shownin Figure 2. The counting of this re-accumulation started at the Wyckoff"Last Point of Support Following aSign of Strength" which occurred atthe 10,500 price level in November2005. Counting backward from right toleft along the 10,500 level until thebeginning of the rectangular price →→Figure 1.

WYCKOFF METHOD:14,400 TARGET FOR DJIA CONFIRMED by Hank Pruden


Techniques

formation in March 2005 revealed anaccumulation of 79 boxes. Thus 79 at50 points per box produced a totalcount of 3,950 points potential. Whenthis re-accumulation build up of 3,950points was added to the bottom of therectangular consolidation (DJIA10,050) and added to the count lineitself (DJIA 10,500) an upward pricetarget zone of 14,000-14,450 ensued.

Since the original 2002-03 base ofaccumulation had an upside projectionto DJIA 14,400, this zone of re-accu-mulation was the stepping count con-firming count. The year 2005 zone ofre-accumulation was also a market tim-ing indicator. When the point-and-fig-ure count build up during the sidewaystrading range reached a spot inNovember 2005 where the points col-lected during 2005 created a projection(14,450) this matched and confirmedthe original upward objective of14,400. Then suddenly in a unique andalmost mysterious fashion, the DJIAadhered to the confirming count's tim-ing rule by immediately breakingupward out of the trading range.

DiscussionThis article is the second installment inthe "Test of Wyckoff" in which we

look at a refinement of the basicWyckoff Law of Cause and Effect - theStepping Stone Confirming Count.This refinement says that the zone ofconsolidation or re-accumulation dur-ing the markup stage of a bull market isboth an effect of the previous phase ofadvance as well as the cause for thenext phase in the markup and, as such,can be used to make projections as tothe probable extent of the subsequentprice move.

The Stepping Stone ConfirmingCount also contains an intriguing tim-ing mechanism. In our DJIA test, thiswas demonstrated when the sidewaysmovement between March andNovember 2005 generated a totalpoint-and-figure count that was suffi-cient to project a future advance to theoriginal price-level target of 14,400. Atthat point the DJIA immediatelyresumed its bull market advance.

The coincidence of the SteppingStone Confirming Count projectionand the original base projection (at14,400) together with the immediateresumption of the uptrend constitutedthe successful passage of an interimtest for the Wyckoff Law of Cause andEffect. A final examination of the suc-cess or failure of these "Wyckoff

Tests" will come when the DJIA even-tually rolls over and a bear market is inplace. For the moment, however, thepoint-and-figure data for 2002-03 andagain in 2005 argue for a continuationof the DJIA bull market until the pricelevel of 14,400, ±5%, is reached.

ImplicationsTraders should not be tempted to over-look a phase of re-accumulation out ofimpatience since the resumption of anuptrend in not a foregone conclusionwhen a market enters a sideways trad-ing range, even if higher price targetsare still outstanding. The trading rangereflects a contest of survival betweenthe forces of supply and demand andan awareness of the Wyckoff Law ofCause and Effect can help traders toevaluate sideways struggles with greaterhistorical understanding and can helpin the formation of effective tradingstrategies.

Henry (Hank) Pruden, Ph.D. isNagel T. Miner Professor ofBusiness and Executive Director ofthe Institute for Technical MarketAnalysis at the Golden GateUniversity, San Francisco, US.

Box 1.

The Wyckoff law ofprice and effect The law of cause and effect providesan insight into the magnitude of thecoming move up or down. The lawpostulates that in order to have aneffect you must first have a cause, andthat the effect will be in proportion tothe cause. This law's operation can beseen working as the force of accumu-lation or distribution within a tradingrange works itself out in the subse-quent move out of that trading range.Point-and-figure chart counts can beused to measure this cause and projectthe extent of its effect.

Figure 2.


Techniques

The strategy achieves profits by buy-ing the undervalued instrument andselling the other with the belief that therelationship will move back to its his-torical average. The underlying belief isthat the price relationship between tworelated instruments tends to fluctuatearound its average in the short-term,while remaining stable over the long-term. It goes beyond other similarstrategies, however, because rather thanbuilding baskets of securities in both along and short portfolio, pairs tradinglimits its analysis to the relationshipbetween two stocks whose relationshipforms the basis of a trade.

Under a technical approach to pairstrading, the bulk of the analysis is per-formed on the pair as a whole ratherthan to the individual stocks; the pair iscreated as a price ratio - the new trad-ing entity - and then individual indica-tors are applied. The implication here isthat stocks must be paired before theanalysis is undertaken. This feature ofpairs trading illustrates the importanceof correlation analysis to the tradingprocess, as it is the primary vehicle bywhich stocks are paired. The higher thecorrelation between a pair of stocks,the more likely the pair is to follow theexpected mean reversion pattern.Some traders may wish to include otherfactors in the matching process thatthey believe strengthen the underlyingrelationship they are trying to exploit.

Regardless of the specific factorsselected, the goal of the matchingprocess within the equity universe is toensure that the resulting pairs are high-ly related to one another and are likelycandidates to revert to the historicalrelationship in cases where they havetemporarily diverged.

Before technical indicators can beapplied to highly correlated pairs ofstocks, the technical trader must firstchart and analyse each prospective pair.Figure 1. shows the charts of theDiamonds Trust (DIA) - The DowJones Industrial Average ETF - and theS&P Depository Receipts (SPY) -

A TECHNICAL APPROACH TO PAIRS TRADING by Douglas Ehrman

Figure 1.

Figure 2.

Pairs trading is a non-direc-tional strategy that identifiestwo stocks (or futures con-

tracts) with similar characteristicswhose price relationship is aboveor below its historical range.

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the S&P 500 ETF - respectively overthe same time period. Even a casualobserver can identify some degree ofsimilarity between the charts. From thegraph alone, however, it is impossibleto quantify the relationship between

these price movements. Without fur-ther analysis, a trader might decide thatthese stocks are likely to have a highstatistical correlation to each other, buthe has no basis upon which to turn thisassumption into a potentially profitabletrading opportunity. A simple correla-tion analysis will provide support forthis assumption, but provides littleadditional information about the pair.

In Figure 2, the relative performance

for the two ETFs for the same timeperiod are plotted on the same graph.This information is more usefulbecause it makes clear that the prices ofthese two instruments go through peri-ods of relative over or under perform-ance, but this information still does notprovide a concrete rule by which a trad-er can construct profitable trades.Furthermore, the specific time periodsof perceived divergence are directlytied to the starting date of the chart.

In order to gain useful informationabout the likely behavior of the pricerelationship, the trader must considerthe pair from a market-neutral point ofview. By graphing the price ratiobetween the two ETFs (DIA / SPY),the trader is considering the priceaction of the relationship from a dollar-neutral perspective. Figure 3 representsthe chart of the dollar-neutral priceaction over a specified period of time.Once the relationship is consideredfrom this perspective, one sees quicklythat employing this type of market neu-trality makes trading this pair a far easi-er proposition. The chart in Figure 3displays a price relationship that movesin a definite range over the period oftime being considered. This is usefulfor the trader because he can now pre-dict not only the likely direction thatthe pair will move, but also the degreeto which the relationship is likely tochange. The pair has become a single

trading vehicle to which technicalanalysis may be applied.

Applying IndicatorsThe most common indicators used inthis approach can be broken into threegroups: moving average indicators,market strength indicators, and volumeas an indicator. While there are literallyhundreds of indicators that may beapplied to a pair, this article will onlyconsider one to illustrate its applicationto a pair rather than an individual stock,futures contract, or other type of secu-rity. The Relative Strength Index is aninteresting indicator because it does notmeasure relative strength in the classicsense. Usually, when a trader refers tothe relative strength of a position, he isreferring to the strength of that posi-tion relative to the strength of an indexor benchmark. In the case of RSI, theindicator is measuring the relative inter-nal strength of the position relative toitself. While this seems counterintuitive,consideration of the equation and theappropriate use of its output shouldclarify this problem.

The RSI formula is as follows:RSI = 100 - (100 / [1 + RS])

Where:RS = Average for net up closing changes for

N days / Average of net down closingchanges for N days.

The trader selects the number of daysto be used: 5, 9 and 14 are standardsused by most traders and are includedin most commercial software programs.

The RSI will range from just above 0to just under 100, but it is extremelyrare to see a number close to either ofthese extremes. Most commonly, RSIreading will fluctuate between readingsof 30 and 70. At extremes, it will moveunder 30 or above 70. Many tradersprefer to use 20 and 80 to indicate over-sold and overbought conditions, butthe level selected is an individual prefer-ence.

An RSI value that is approaching anextreme theoretically indicates that a

Figure 3. (DIA / SPY)

“CORRELATIONANALYSIS IS THE

PRIMARY VEHICLE BY WHICH

STOCKS AREPAIRED.”


Techniques

reversal can be expected to occur in theimmediate future. Figure D depicts thechart of a stock's price action and thecorresponding RSI reading.Considering the chart, one can see thatextreme RSI readings (at, or above 70and at or below 30) often are associat-ed with price reversals in the security orpair under consideration. These rever-sals tend to occur at or shortly after theextreme reading is taken, so the tradershould not consider such a reading tobe an immediate trading catalyst.

RSI measurements can be a usefultool in analyzing pairs of stocks andcan give the technical trader a signifi-cant edge. The specifics of RSI for aprice relationship are similar to thosefor an individual stock, but they may beeven more pronounced. One of theways to use RSI is to look for a diver-gence between the chart of the stock

and RSI readings. When a divergence isdetected, it may indicate a major trendreversal rather than a regular fluctua-tion.No single indicator is either withoutflaws or sufficient as a rule for all trad-ing decisions, and none are appropriatefor all traders. Each individual mustachieve a certain level of comfort witha series on indicators for them to besuccessful.

ConclusionBy using a well-grounded understand-ing of the relationship between twospecific stocks, a technical trader is ableto apply those indicators with which heis most familiar and comfortable. Usedwithin the context of a market-neutralstrategy like pairs trading, these toolscan form the basis of a disciplined andconsistent approach that can benefit

both novice and professional tradersalike. Furthermore, as the strategy gainsin popularity, the tools available to thepairs trader have increased (TheAlchemy Report for institutionaltraders and PairTrader.com for retailtraders). Generally, understanding pairstrading can be a benefit to all traders byeither expanding one's knowledge baseof trading, or by providing an alterna-tive approach.

Douglas Ehrman is recognized asone of the US's leading experts inthe field of statistical arbitrage andmarket neutral strategies. He is cur-rently president of the ExperityGroup and is editor ofPairTrader.com. He is also theauthor of "The Pairs TradingHandbook" (J Wiley).

Figure 4.

“TECHNICAL TOOLS CAN FORM THE BASIS OF A DISCIPLINED AND CONSISTENT

APPROACH TO MARKET-NEUTRAL STRATEGIES LIKE PAIRS TRADING.”


Interview

TA: What kind of fund do you manage?

JB: It's a quantitative type hedge fund that we run out of ouroffice here in Manhattan Beach, California. There are four ofus in total working on the fund and we trade mostly US equi-ties and the more liquid exchange traded funds.

TA: What strategies does the fund employ?

JB: Despite being a strong proponent of technical analysis,fundamentals also play an important role in my trading andresearch. They can't be ignored. Anyway, technical analysis isprimarily concerned with information that is generated in themarketplace such as price, volume and trader information. Ifyou just expand the concept of the marketplace and addsome mathematics you become more quantitative. If Idescribe my fund as quantitative then money supply data is asimportant as an RSI indicator. I'm a technical analyst usingfundamentals. Just to expand on this point: equally, a tradi-tional fundamentalist can add value using technical analysisby using it as a market timing tool to decide exactly when toenter and exit the market. This is perhaps the approachemployed by many fund and portfolio managers. The twoapproaches are then very complimentary. Finally, in my fund,I use both as part of an automated strategy that generatesbuy and sell signals although it doesn't execute orders auto-matically. Of course, Bollinger Bands come into play on thetechnical side.

TA: Obviously, you are best known for your Bollinger Bands.Why have they proved to be so enduring?

JB: I believe that they were the right tool at the right time. Atthe time they were created, many people were looking at tak-ing trading bands and making them adaptive. The great ben-efit of Bollinger Bands is that they respond to market condi-tions by expanding and contracting. This was a relatively newidea that a lot of people were interested in and up until then,much of the technical analysis using envelopes, bands andsuch like had to be done by hand. Also, I made them imme-diately available in the public domain so they became widely

used very quickly. I was working as chief technical analyst onthe Financial News Network in the US and an awful lot ofnew technical ideas got aired via this medium and I had theopportunity to discuss the bands on television which wasexcellent publicity for them. The bands then appeared onCQG and Bloomberg in the 1980s. Furthermore, I attachedno copyright to them so, in the end, the bands become avail-able on all software packages. I also made no secret of howthe bands were calculated. If someone comes up with a newindicator, there's no point in concealing the maths behind itand I was very open about this from the beginning.

TA: How do you use Bollinger Bands yourself ?

THE TECHNICAL ANALYST TALKS TO...

John Bollinger is renowned for his famous Bollinger Bands, one of themost popular charting methods used by traders around the world. Healso runs a California based fund, Bollinger Capital Management.


Interview

JB: I use them to systematically generate buy and sell signalsas they work especially well for that. However, in the fund Ialso use the bands to place stops, and in the actual portfoliomanagement process, in analysing the components of theportfolio. I also use a derivative of Bollinger Bands calledBollinger Envelopes that have no moving average. We aredeveloping new ideas all the time and I am always increasingthe suite of Bollinger indicators. The basic bands themselvesare a very small part of the work I have done.

TA: Do you think that the use of the bands changed in anyway from your original design?

JB: Speaking for myself, I mostly use the standard bands; 20period moving averages and 2 standard deviations. We alsouse 50-day Bollinger Bands and apply the bands not only toprice charts but also to indicators such as the RSI in order toreplace the traditional 30-70 oversold and overbought levels.I have always advocated changing the parameters to suit anindividual trading style. Any backtesting that is undertakenmay reveal that for some markets, a derivative of the standardparameters may work better. I have been told about someblack box systems developed by hedge funds that useBollinger Bands and they are often using their own propri-etary version. When it comes to hedge funds, it's very diffi-cult to know exactly what they are doing.

TA: Which indicators do you recommend using with yourbands?

JB: Like most techniques, Bollinger Bands work best in con-junction with other indicators and I'm a great admirer ofother studies such as DeMark. Whilst the TD sequentialtends to be used in isolation, there are many other DeMarkstudies that work well with other techniques includingBollinger Bands. I'm also a big fan of volume indicators. Thisis because using a suite of three or four non-correlated indi-cators, based on price and volume, is more effective thanusing just price indicators alone.

TA: We have heard several traders mention how BollingerBands work particularly well with candlesticks. Why is this?

JB: In my presentation at the Technical Analyst conferencein London this year, I spoke about a combination of candle-stick and bar charts that I have developed that I call BollingerBars. These are just a way of colour coding candlesticks andremoving the changing width of the candlestick while retain-ing the visual display of the information. The main attractionof candlesticks, of course, is the patterns and the signals thatthey generate.

TA: What's your outlook for US stocks at the moment?

JB: I'm not bearish or bullish at the moment; we are in a

long-term period of consolidation. In that sense the marketis going to disappoint going ahead. This doesn't mean themarket won't cover a lot of ground but we won't see the startof a new secular bull market until at the least the end of thedecade. For the S&P500, we peaked in 1998 at 1190 so ineight years we have gained around 100 points but 1200 willremain the focal point of that market.

TA: There is a lot of news at the moment discussing the cur-rent strength of US corporate profits. Shouldn't this, at least,support a more bullish outlook for stocks?

JB: Traditionally after you see a bubble burst as we did in2000, you see a period of extreme undervaluation. Just nowwe are beginning to approach average valuation but the postbubble adjustment has some way to go. This means thatstocks will be considered cheap in the not too distant future.Continued earnings growth will then support the market.

TA: What about the dollar?

JB: The dollar outlook is interesting at the moment. From atechnical perspective it looks like it is trying to strengthenversus the euro. It's fashionable to be bearish on the dollarnow.

TA: Didn't this happen a couple of years ago when the con-sensus was for a dollar rate of 1.40 and above against theeuro that didn't happen in the end?

JB: That was a good example of a contrary position oppor-tunity. When opinion is so far in one direction, it rarely hap-pens. There are times when the FX market is monolithic.Everything rises against the dollar or falls against the euro,for example. At the moment, each currency seems to be trad-ing on its own dynamic so there's a lot of differentiationbetween the currencies which presents more opportunities tothe active trader. The same goes for the US stock market withsome stock sectors showing greater independence and assuch we have seen a lot of rotation this year.

TA: Are there any new Bollinger books in the offing?

JB: Nothing at the moment. Writing books is exhausting andI've done more than my fair share!

“I MOSTLY USE THE STANDARD BANDS; 20 PERIODMOVING AVERAGES AND 2 STANDARD

DEVIATIONS. I ALSO APPLY THE BANDS NOT ONLYTO PRICE CHARTS BUT TO INDICATORS SUCH AS

THE RSI IN ORDER TO REPLACE THE TRADITIONAL 30-70 OVERSOLD AND OVERBOUGHT LEVELS.”


Software

UPDATA TECHNICAL ANALYST FOR BLOOMBERG

Since the launch of "UpdataTechnical Analyst forBloomberg" in 2004, charting

software provider, Updata, has addedan impressive list of global financialinstitutions to its client list.

The real power we see in this systemis its ability to use Bloomberg's vastdatabase with a greater technical analy-sis capability combined with powerfulscanning and complex criteria alerting.Updata covers all the TA bases onewould expect and is particularly strongin a number of disciplines such asFibonacci, Ichimoku, Market BreadthAnalysis, Point and Figure andOptimised Stoplosses.

The company cites the main reasonswhy market professionals use the sys-tem as:

Familiar Bloomberg ticker entryScanning for multiple technicalcriteriaReal time alerting of any technical eventReport writing and flexible chartsizing and labellingScanning and charting ofBloomberg CIX Indexes Custom Indicator coding and system testing

David Linton, Updata's CEO sums upthe company's approach, "Although wehave a great deal of experience in thefield of charting , much of our devel-opment is now driven by our customersand they are always impressed at howquickly we can integrate their require-ments and ideas." He believes the sys-tem's success comes down to experi-enced technical analysts managing ateam of programmers for the needs oftechnical traders and analysts. Lintonsays, "We always set out to understand

exactly what it is that each client is try-ing to achieve and work with them tohone their ideas and reach their goals.The result is a flexible system everyonecan benefit from."

ChartingUpdata has the standard array of chartsand tools, as well as some interestingproprietary indicators. The systemoperates with keystrokes as well as but-tons and dropdown menus. The exten-sive user manual stresses that click-min-imisation is their goal. The charts arehigh quality, the background of whichcan be set to any colour which isimportant for publishing. Copying toclipboard or emailing is just one clickaway and charts may even be sized tothe exact size required before copying.The desktop management allows up tonine separate desktops containingcharts, quote screens and heatmaps.

ScanningScanning is often a neglected part ofmany technical analysis systems in themarket but it's one of Updata's corestrengths. Most analysts have an ideaof what it is they want to scan for butwhen they sit down and try and articu-late the mathematics they realise thatturning subjective chart eyeballing intocode can be a challenge. Updata'sHighlighter reduces the complexity sig-nificantly through a series of dropdown menus and checkboxes keepingthe end user away from code. The sys-tem comes with a series of pre-writtenHighlighters, but simple ones are fairlyeasy to write and Updata's supportteam offer assistance for the moreambitious user. The Highlighter claimsto have endless possibilities with nolimit on the number of conditions youcan add to a scan. Once set up, the

highlighters can be scheduled to runwhenever required, ready for chartswith all the criteria to be scrolled orsent automatically to a pdf documentor printer with a defined number ofcharts per page. Most clients have theirscans scheduled to run overnight sothey arrive to a set of printed chartsand reports in the morning. Typicallyusers will be scanning large global stockuniverses for the handful of charts thatmeet their criteria. It even caters forcurrency adjusted price relative scans,as well as pattern searches and specificsignals and risk reward ratios.

Real time alertingThe real time alerting module, UpdataMarketHawk, lets users load theirHighlighters so as to alert them whenany instrument in their universe meetstheir conditions as it actually happens.Spotting things retrospectively is some-thing many analysts and traders cite as acommon problem and even though youmay have the scans there is nothingquite like being informed that some-thing has just met your criteria thatmoment. MarketHawk lets the userdecide on the alert type: sounds, onscreen pop-ups, chart pop-ups or evenan SMS text message or email withchart attached (viewable onBlackberry). Normally, real time alert-ing programs are fairly simplistic.

Figure 1. Technical Analyst is easy to usewith the same tickers. If you know the code inBloomberg, it's the same in TA

••

•

•

•••


Software

Updata's, on the other hand, handlestrailing stoplosses as well as complexmultiple technical analysis conditions.

Report writing & chart labelling Updata Technical Analyst also comeswith a Report Writer which generatesall the saved chart images for producingand reproducing reports. All your pre-vious analysis and annotations arereloaded on charts that are up to dateand in the same order as in your previ-ous report. You can step through the

charts and edit and remove any as youdesire. Another area where Updatascores highly for Bloomberg users isthe ability to format and annotatecharts in almost any way you want. Youcan add you own logos, contact detailsand colour schemes on every chart youproduce, and define a series of customchart sizes which is ideal for publishingand presentations.

OptimisationUpdata's Optimiser works much thesame way as their scanner, through aseries of drop down menus and checkboxes. It effectively runs a series ofbacktests, varying periodicity and signallevels to arrive at the best period andlevel to read an indicator; a sort of'best' backtest. Indeed, Updata went onto add Optimised Stoplosses from asignal key press as a result of it consis-tently coming top of the results list forthe best exit strategy.

Custom Indicators & systemtestingRecently Updata has entered the area ofa custom programming language and

system testing. This may sound a littledaunting for a non programmer, but itsin line with its Highlighter andOptimiser, as much of the work is donewith prewritten commands and expres-sions that the user can string together.For instance, if you want an RSI as partof your custom indicator you just usethe RSI command instead of codingRSI. There are tool tips on syntax aswell. Updata reckons that there is nolimit to writing any indicator you needand will normally assist users in this.Unusually, custom indictors can also beloaded into the highlighter and alertingas well.

In fact, this is one of the more pow-erful aspects of the Updata system; theinteroperability between customising,scanning, alerting, optimising and test-ing. If you want to system test a high-lighter, you just load it into the testingscreen. If you want to scan for criteriameeting your custom indicator signal,you just load it into the Highlighter.Updata is working with a number offirms on full blown portfolio testingwhereby it will be possible to teststrategies across universes of instru-ments over time as well.

SummaryUpdata Technical Analyst's big advan-tage is the way it seamlessly integrateswith Bloomberg. The online help andprinted documentation is impressive.There are lots of unique capabilities inUpdata Technical Analyst forBloomberg as well, with tools such asRisk Reward Ratios, automated trendlines, MarketMaps and Biorhythms.Most of all there is barely a technicaltrader or analyst with a Bloomberg whowill not find something of value fromthe system. The company offers freetrials to anyone with a BloombergTerminal, so it's probably worth a try!

Updata Technical Analyst V4Standard Version - £100 per monthAdvanced - £200 per monthUpdata Plc - Tel: +44 20 8874 4747Email: [email protected] a free trial go to: www.updata.co.ukBloomberg code: IDOC UPDATA <GO>

Figure 2. Market Maps let you tag yourinstruments in a list. You can see the day'scandle and current position at a glance

Figure 3. Chart labelling can all be easily created and saved on charts. You can even click toemail or transfer your chart with analysis and labels to other users via Updata Instant Messenger

The Investor’s Guide to ActiveAsset Allocation

Using Intermarket TechnicalAnalysis and ETFs to Trade theMarkets

By Martin Pring

ISBN 0-07-146685-1$49.95

The Investor’s Guide to ActiveAsset Allocation can be pur-chased from the TechnicalAnalysis bookshop. To order please call 01730 233870and quote "The Technical AnalystMagazine".

Martin Pring is probably best known for his book, "Technical AnalysisExplained", one of the standard texts for anyone getting into the sub-ject for the first time. Whilst his previous works has centred on what

may be termed traditional technical analysis, his latest book focuses on what hecalls intermarket technical analysis. This is best defined as the relationshipbetween the business cycle and the performance of the various sectors, stocks,bonds and commodities etc, during the cycle.

This is a book about investing rather than trading. The distinction betweenthem is one of time scales and techniques. Pring argues that the basic 4 yearbusiness cycle, the Kitchin Cycle, presents optimal periods for when to invest instocks, bonds and commodities as the cycle progresses. Most of the book there-fore is given over to analysis of the business cycle and the investment opportu-nities it presents. There is very little traditional technical analysis as such.However, the analysis and use of cycles is one of those rare subjects that can fallequally into both the fundamental and technical analysis camps and this is wherethe value of the book really lies.

Pring's emphasis is on tactical asset allocation; this is simply portfolio assetadjustment in response to changing economic and market conditions. Historicalanalysis of last century's business cycles reveals what parts of the business cyclepresent the best investment opportunity for each asset class. The trick then is toaccurately ascertain where the economy may be in the business cycle at any onepoint in time. For this, several quantitative methods can be employed includingvarious momentum and rate of change studies along with best leading, coinci-dental and lagging indicators. In order to identify trend reversals and the direc-tion of a secular trend, Pring relies on moving averages, momentum, trendlines,relative strength (between sectors and indices; not the RSI) and his own KSTindicator. This is as far as he goes with the application of conventional TA meth-ods.

The second half of the book looks at exchange traded funds (ETFs) as thebest vehicle for undertaking sector rotation in the asset classes he discusses.Equity based ETFs, for example, are listed instruments that contain a basket ofstocks that replicate the movement of a given index. The most popular areSPDRS and QQQ that track the S&P500 and Nasdaq respectively. Pring sug-gests that individual stock picking is time consuming and prone to error. If youare interested in moving in or out of a particular sector then the best instrumentto use is one that tracks an index of that sector. Whilst the ETF market in theUK is less developed than that in the US, it is expanding quickly and the rangeof funds available is increasing rapidly.

Martin Pring's new book is not only a valuable guide to longer term investingbut a fascinating read. Moreover, the author has managed the feat of bringingtogether various technical and fundamental analysis techniques into a practicaland systematic investment strategy using a new and exciting instrument, ETFs.

THE INVESTOR’S GUIDE TO ACTIVE ASSET ALLOCATION


Book Review

presents

Two premier events for trading and investment professionals

Automated Trading Systems 20061 Wimpole Street, London W1 - 12 October 2006Strategies for building an automated trading system

www.ta-conferences.com +44 (0)20 7833 1441

[email protected]

Topics Covered:

+ Developing a mechanical trading system + Backtesting strategies + High frequency trading + Systematic FX strategies + Systematic arbitrage strategies

Who should attend:

+ Proprietry Traders+ Hedge Fund managers+ Fund managers+ Quantitative analysts+ Technical analysts & strategists

Speakers include:

James BinneyABN Amro

Raspal SohanRathbones

Rami HabibKytegroup

Jessica JamesCitigroup

Gerben de ZwartRobeco

Doug EhrmanPairTrader

Dario CirakiInsightful

Also booking...

The 2nd TA European ConferenceHilton Docklands, London E147 February 2007Technical Trading Strategies

Delegate fee: £395 + VAT


TA: Why should a trader consider usingan automated trading system?

SF: The difference between successfultraders and unsuccessful traders is thatsuccessful traders have a simple set ofrules which allow them to control risksand to have the discipline to trade amodel for a long time without anychanges. This is exactly the area whereautomated trading systems are a bighelp.

TA: You are directly involved in help-ing traders to create automated tradingsystems. What do you tell a tradershould be his/her starting point?

SF: A good place to start is to tryautomating what you already do.Automating your trading doesn't neces-sarily mean a complete change in thestyle of your trading and starting fromscratch. The biggest benefit of automa-tion is that if you develop a systembased on a trading style you have usedbefore then you are able to find errorsin your system. You have to think verysystematically and in terms of rules tocreate a successful model.

TA: Is an automated trading systemmore suitable to any particular type ofinvestor/trader, e.g. short vs. longterm?

SF: No, I don't think so. It is good forevery kind of trader. The reason to

start automating your trading is toavoid the emotional errors that usuallycreep in when trading intuitively. Thatis obviously true for everytrader/investor but particularly so fortraders who operate in very short timeframes. In such cases, it is a big advan-tage to have an automated set of rulesbecause you have to make your tradingdecisions in a much shorter time.

TA: What guidelines do you offer fordetermining which variables/buildingblocks to use when creating a tradingmodel? Are mathematically based tech-nical indicators, such as RSI andBollinger Bands, any better suited thanother forms of analyses?

SF: In my opinion it is a matter of per-sonal experience because you have tobe very confident when you are tradingwith an automated system. This is a keyfactor! You have to have the disciplineto follow your rules all the time everysingle day. One trader may love usingBollinger Bands for example, the otherone trades breakouts and the next onewill use chart patterns. My guideline isto start with some questions like 'whatis my trading style?', e.g. trend followingvs. swing trading.

TA: Is it possible to automate tradingthat is based on more judgementalforms of technical analysis, such aschart patterns and Elliott Waves?

SF: Yes absolutely, that is possible.Chart Patterns for example could bewell defined within an automated sys-tem. With Elliot Waves it is more diffi-cult to automate but still possible. I per-sonally don't like things like "neuronalnets" because the created signals withthose kinds of rules are a black box. Asa trader you don't have any idea whyyour system is going long or short. Ifyou have a series of losses then it's veryfrustrating for the trader and at the endyou may stop trading the signals justbefore the big winning trade occurs.

TA: How easy is it to create a modelthat combines technicals, fundamen-tals, flow information and/or news?Are there any limits to such modeldevelopment, whether in theory orpractice?

SF: With the "IQ-Trader" - the toolwhich I use to develop, backtest andtrade my models - creating a model isvery simple. We (the developers and I)have simplified much of the very com-plex tasks. For example, the first step isto choose the input variables like indi-cators, patterns, breakout levels. Thenext step is to interpret every indicatoraccording to whether a specific readingis a buy or a sell. The result is one indi-cator (a "Sentimentor") that rangesbetween 0 and 100 which contains theweighted buy and sell information ofall inputs.

The benefit of the IQ-Trader

BUILDING A TRADING MODEL: FIRST STEPS

We speak to Stefan Fröhlich, consultant withFipertec GmbH and an expert in the process ofdeveloping automated trading systems. Stefan ismost closely associated with IQ-Trader, an automat-ed trading plaform developed by Fipertec andoffered by trading system providers and brokerssuch as Patsystems and Berkeley Futures.


approach is that it allows a trader tocombine all kinds of information intotheir trading model as soon they havetranslated the information into a senti-ment range between 0 and 100.

TA: Is there an optimum number ofvariables in a typical model?

SF: No, the number of variablesdepends on the trading style, the aggre-gation of the used data and your per-sonal ideas. The limit is in my opinionto keep a model as simple as possible. Acomplex model isn't better than a sim-ple one.

TA: What is the typical life of a tradingmodel? Does profitability tend to fallover time or remain stable?

SF: Unfortunately profitability formost models with fixed parameterstends to fall over time. That means youhave to create models with dynamicvariables, which is a real challenge. Butthere are ways and tools which can bevery helpful in the process to create andtrade those kinds of models. The "IQ-Trader" has some of those features likesensitivity analysis and a walk forwardtest. There is no typical life cycle of atrading model because there is a big dif-ference if you have a model based ondaily data and one based on intradaydata.

TA: In your experience, what is the rel-ative importance of "entry" versus"exit" strategies in determining the per-formance of your model? Would youagree that traders should give morethought to optimising exits?

SF: Yes in my experience exits aremuch more important than the entries.For example if you fail to close a tradewith a stop and the market is movinginto the wrong direction you are losingmoney and your account balance isgoing down. Here we have a direct rela-tionship between the "signal" and yourtrading capital which isn't true for fail-ing to get into the market. In that caseyou will have a second chance. I think it

is a good idea to test and optimize sev-eral combinations of exits and stops.Ideally you can do this seperately,which is possible with "IQ-Trader".

TA: What do you think are the mostimportant measures to use when back-testing a trading model? What risk-adjusted performance measures do yourecommend?

SF: That answer is easy for me becausefor this reason, and to help traders toread backtesting reports in the rightway, I have created the "Fröhlich-Factor" (the translation is "Happiness-Factor"). This figure adds the mostimportant figures of back testing likeNet Performance, Profit Factor, aver-age wins/average loss ratio, drawdown,biggest win and biggest loss togetherinto one figure. So it is a risk adjustedmeasure. You can use the "FröhlichFactor" for risk and moneyManagement and to find the right auto-mated model for trading.

TA: Are there, in your opinion, anygolden rules for backtesting? For exam-ple, should day traders test their strate-gies on at least 6 months, one year, ortwo years worth of data etc? Andshould they use data from the mostimmediate recent history or be lookingto identify periods of "similar" marketconditions, e.g. bull or bear markets.

SF: I think it is more important to lookat "similar" periods in terms of marketconditions and/or volatility than tolook at the most immediate history.There is one golden rule for the lengthof the data in the backtest: It isn't afixed number like 6 months, becausethe time and history data correlateswith the number of trades of yourbacktest. The more trades you have thebetter it is. The reason is that if youhave a significant number of trades(tries) then the standard deviation ofthe backtesting results is much smaller.This suggests that the model will bemuch more stable in the future.Unfortunately I can't give you the idealnumber of trades - the relationships of

all variables aren't linear!

TA: How can you avoid the pitfalls ofoverfitting?

SF: First, do not believe too much inthe results of backtesting. Second,trade the model with data that wasn'tused during optimization and third notrader really knows what will happen inthe future which means good results inbacktesting are no guarantee how themodel will perform in the future. But itwill help you identify under which mar-ket conditions you are making yourprofits and therefore gives you confi-dence.

TA: How can you be certain that yourmodel will accurately account for slip-page during periods of extreme volatil-ity, where a disproportionate amount ofa system's profit or loss may be gener-ated.

SF: A backtest is simply a simulationfor how your trading model performedin history. But it isn't an accurate reflec-tion of the real world. For that reasonyou have to add costs and slippage toevery trade. During periods of extremevolatility it would be ideal to increasethe slippage and during periods of lowvolatility to decease it. By using a fixedpercentage of the Average True Range(ATR) by Welles Wilder, you will getmore realistic levels of slippage. That isthe reason why you can use a percent-age of the ATR for slippage whenbacktesting with "IQ-Trader".

TA: Assuming you have developed amodel that looks like it performs well,what other factors should you considerbefore adopting the model?

SF: Risk and money management. Youhave to answer the questions 'howmuch will you risk on every singletrade?' and 'how many contracts willyou trade on every signal?'

For more about IQ-Trader call MarcQuinn on 020 7758 4777 orwww.bfl.co.uk for a free demo.


TRADING MODELS: MINIMISING DRAWDOWNS by Alan Crary

Any serious trader knows they are responsible notonly for profits, but also the minimisation of draw-down, i.e. trading consistency

The first thing I think of when I think of consistency istimeframe. I want to be consistently profitable over x time-frame. The x could be each day, a week, a month, a year, 10trades, 50 trades, etc. Each person needs to decide the time-frame that they need to be consistently profitable. It's pret-ty common to hear comments like I want to be a day trad-er and make y dollars per-day every day. That trader hasdecided that their timeframe is one day for consistent prof-itability.

Make a decison on a timeframe over which you want tobe consistently profitable. In this article I'll show you sometools to help reach your goal and show what it takes toreach it.

Before I go any further I want to make sure everyoneknows these two concepts.

Expectation of a trade = (PW * AW) - (PL * AL)Expectation of profit factor = (PW * AW) / (PL * AL)

wherePW = probability of a winning tradeAW = average size of winning tradePL = probability of a lossAL = average size of a loss

Just about everyone is familiar with the expectation of atrade or just plain "expectation". I've not seen anyone evertalk about the expectation of the profit factor so I'm men-tioning it here. This will be useful going forward.

Ok, now you have a timeframe for being consistentlyprofitable. Now what does it take to achieve it? One moredecision has to be made before continuing. What level ofconfidence do I need for consistent profitability? Some willbe happy with 90%, others 95%, and some like me require99%. So, to put it together in my case I require consistentprofitability on a monthly basis with a 99% level of confi-dence. So in other words it's ok for me to have a losingmonth once every 8+ years.

One series of studies I did was to find out what were theimportant factors in consistency. I did tests on size ofexpectation, % wins, profit factor, number of trades

Model name daytrade# of trades in series 10 % of trades that are winners 70 Mean of winning trades 500 Std. Dev. of winning trades 0 Mean of losing trades 500 Std. Dev. of losing trades 0 Outcome Profit Factor Max DD 1% level 5,000.00 10.00 0 5% level 4,000.00 9.00 -50010% level 4,000.00 9.00 -50020% level 3,000.00 4.00 -50030% level 3,000.00 4.00 -50040% level 2,000.00 2.33 -50050% level 2,000.00 2.33 -1,00060% level 2,000.00 2.33 -1,00070% level 1,000.00 1.50 -1,00080% level 1,000.00 1.50 -1,00090% level 0.00 1.00 -1,50095% level -1,000.00 0.67 -2,00099% level -2,000.00 0.43 -2,500

Expected outcome 1,950.00 Expectancy 200

Model name daytrade# of trades in series 10 % of trades that are winners 70 Mean of winning trades 1000 Std. Dev. of winning trades 0 Mean of losing trades 1000 Std. Dev. of losing trades 0 Outcome Profit Factor Max DD 1% level 10,000.00 10.00 0 5% level 8,000.00 9.00 -1,00010% level 8,000.00 9.00 -1,00020% level 6,000.00 4.00 -1,00030% level 6,000.00 4.00 -1,00040% level 4,000.00 2.33 -1,00050% level 4,000.00 2.33 -1,00060% level 4,000.00 2.33 -2,00070% level 2,000.00 1.50 -2,00080% level 2,000.00 1.50 -2,00090% level 0.00 1.00 -3,00095% level 0.00 1.00 -4,00099% level -4,000.00 0.43 -5,000


Table 2.→→

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within a timeframe, and the effect of dispersion of trades(std. deviation) has on the results. For instance, Table 1 is arun for a day trader that does 10 trades a day with 70% winsand makes $500 on each win and loses $500 on each loss.As you can see this is quite profitable at the 50% level (theaverage over time). However you can also see that after the80% level the trader actually loses money. So for a day trad-er with these numbers they only have an 80% chance ofachieving their goal of consistent profitability on a dailybasis. If that level of confidence is ok, then they have anexample to use going forward.

Now what happens if that day trader decides he wants95% level of confidence so that he'll accept one losing dayper month. What changes would he make? If he doubleshis expectation does that help? As you can see from Table2, he still only has about 80% confidence level with doublethe expectancy on each trade.

How about if he increases the winning percent to 80%and keeps the expectancy at $400, so that each win nowbecomes $600 and each loss now becomes $400 (Table 3).

Obviously after the last test this day trader would knowthat with him winning 80% of the time and having a high-er win size than loss size he'd be rich in record time. He'dnow know that he has more than a 99% chance of makinga profit each and every day he trades. What do think hispsychology might be like? How about ..."time to trade can'twait to see how much I make today".

Notice the expectancy didn't change from this test to thelast one. I did this to show that expectancy really isn't a crit-ical component of being consistently profitable. Rememberat the beginning of this article I mentioned the expectedprofit factor. In this case it worked out as:

Epf = (PW * AW)/(PL * AL)Epf = (.8 * 600)/(.2 * 400)Epf = (480)/(80)Epf = 6 or the 50% level described in the test

Now that we've seen the expectancy didn't improve thelikelihood of achieving consistency, what effect did chang-ing the expected profit factor have. We can use the equationto keep the same win % and win size to solve for the oldPF of 2.33 at the 50% level as in the previous test.

2.33 = (.8 * 500) / (.2 * AL)2.33 = 400/.2AL2.33*.2AL = 400.2AL = 400/2.33 or 171.67AL = 171.67 / .2 or 858.35

When we plug in the new test of 80% winners, $500 winfor each winner and 858.35 for each loser (to keep the prof-it factor at 2.33) we get the results shown in Table 4.

From this last test we can see that if we kept the profitfactor the same but changed the win % and expectancy,we'd have the same confidence level as we started with,80%. From this we can tell the win % and expectancy arenot critical to consistency. One of the important key fac-tors is the expected profit factor. The higher the profit fac-tor, the more likely we are to achieve consistent profitabili-ty.

What would have happened if instead of changing thewin % we just changed from 10 trades per day to 20 tradesper day? Then our day trader would have a win% of 70%,win of $500, loss of $500 and twice as many opportunitiesper-day. Table 5 shows the results of that test.

As you can see from this last test (Table 5) by increasing

Model name daytrade# of trades in series 10 % of trades that are winners 80 Mean of winning trades 600 Std. Dev. of winning trades 0 Mean of losing trades 400 Std. Dev. of losing trades 0 Outcome Profit Factor Max DD 1% level 6,000.00 13.50 0 5% level 6,000.00 13.50 010% level 6,000.00 13.50 020% level 5,000.00 13.50 -40030% level 5,000.00 10.00 -40040% level 4,000.00 6.00 -40050% level 4,000.00 6.00 -40060% level 4,000.00 6.00 -40070% level 3,000.00 3.50 -40080% level 3,000.00 3.50 -80090% level 2,000.00 2.25 -80095% level 2,000.00 2.25 -1,20099% level 1,000.00 1.50 -1,400


Table 3.

Model name daytrade# of trades in series 10 % of trades that are winners 80 Mean of winning trades 500 Std. Dev. of winning trades 0 Mean of losing trades 858.35 Std. Dev. of losing trades 0 Outcome Profit Factor Max DD 1% level 5,000.00 10.00 0 5% level 5,000.00 10.00 010% level 5,000.00 10.00 020% level 3,641.65 5.24 -85830% level 3,641.65 5.24 -85840% level 2,283.30 2.33 -85850% level 2,283.30 2.33 -85860% level 2,283.30 2.33 -1,21770% level 924.95 1.36 -1,21780% level 924.95 1.36 -1,71790% level -433.40 0.87 -2,07595% level -433.40 0.87 -2,57599% level -1,791.75 0.58 -3,433

Expected outcome 2,283.30 Expectancy 228.33

Table 4.


the number of trades from 10 to 20 and keeping the prof-it factor, win %, and expectancy the same we've improvedthe confidence level to above 95%. So if our day traderwanted to be 95% confident that he'd make money everyday he could have also increased the number of trades per-day to achieve his goal. Now we have two variables thathave an impact on consistent profitability (profit factor andfrequency of trades).

If our day trader wasn't using strict targets and let theprofits fluctuate and used a trailing stop in addition to theinitial stop we'd increase the dispersion of the trades (std.deviation). For this example I'm using our 20 trades, 70%winners, $500 win, $500 loss, and letting the std. deviationof winners grow to $500 (100% of average) and std. devi-ation of losers grow to $250 (50% of average). This will letyou see the effect of dispersion of outcomes on consisten-cy. As you can see in Table 6, by letting the winners ride alittle and dragging a stop loss behind, the trade effect of thedisperison of the trades on the overall results was there butnot very important in impacting the consistency we're look-ing for.

ConclusionThe main idea of this article was to show what is importantin moving toward a consistent winning trading model. Bychoosing a timeframe and then working on both the profitfactor and number of trades you can move toward the goalof consistent profitability.

Here's some rough estimates of the relationship betweentrade frequency and needed profit factor to achieve a 95%level of confidence that you'll be profitable within a time-frame for a single method.

# trades......profit factor needed10............4.0020............2.5030............2.0040............1.7560............1.50

So, if you wanted to be profitable every week at the 95%confidence level (you'd still have about 3 losing weeks per-year), and all your method could produce was a 1.50 profitfactor, then you'd need 60 trades out of it to achieve yourgoal.

From this you can tell that to achieve consistent prof-itability on a daily basis, either you've got some miracle sys-tem or you trade like a madman.

One of the ways of increasing consistency is to use mul-tiple systems or to use the same system on multiple non-correlated instruments, which is a topic for discussion in afuture article."

Note: Probability calculations are derived from MonteCarlo Var Analysis. For these big picture type of tests I usea normal distribution curve for the results. I have anotherversion that I use to simulate fat tails (which is slightly morerepresentative of actual trading).

Alan Crary is a regular contributor to Elite Trader(www.elitetrader.com), a web-based forum for traders.

Article extracted from the thread "System Development with acrary" with per-mission from Elite Trader.

Model name daytrade# of trades in series 20 % of trades that are winners 70 Mean of winning trades 500 Std. Dev. of winning trades 0 Mean of losing trades 500 Std. Dev. of losing trades 0 Outcome Profit Factor Max DD 1% level 8,000.00 9.00 -500 5% level 7,000.00 5.67 -50010% level 7,000.00 5.67 -50020% level 6,000.00 4.00 -50030% level 5,000.00 3.00 -1,00040% level 5,000.00 3.00 -1,00050% level 4,000.00 2.33 -1,00060% level 4,000.00 2.33 -1,00070% level 3,000.00 1.86 -1,50080% level 2,000.00 1.50 -1,50090% level 1,000.00 1.22 -2,00095% level 1,000.00 1.22 -2,50099% level -1,000.00 0.82 -3,000


Table 5.

Model name daytrade# of trades in series 20 % of trades that are winners 70 Mean of winning trades 500 Std. Dev. of winning trades 500 Mean of losing trades 500 Std. Dev. of losing trades 250 Outcome Profit Factor Max DD 1 % level 10,721.00 15.22 -397 5% level 9,021.75 7.95 -59510% level 8,031.75 5.83 -69320% level 6,854.50 4.31 -84430% level 6,004.75 3.52 -98140% level 5,247.25 2.97 -1,12950% level 4,542.25 2.55 -1,27660% level 3,848.75 2.22 -1,44470% level 3,118.25 1.90 -1,64180% level 2,240.25 1.59 -1,91190% level 1,113.50 1.26 -2,37495% level 49.00 1.01 -2,83599% level -1,781.50 0.68 -3,814


Table 6.


ALGORITHMIC EXECUTION: TECHNOLOGY IS KEY

Automated trading and algorithmic execution areplaying an increasing role in buy-side trading strate-gies. While this is nothing new and the motivation

behind automated trading remains the same - minimisingyour market impact whilst maximising your alpha return -the development of new strategies and technology contin-ues as buy-side players look to get ahead of, rather thansimply keep up with, the competition.

Portware is one of several developers of broker neutral,multi-asset automated trading platforms providing multi-broker and proprietary algorithms to the buy-side market.Portware's European head, Stuart Adams, spends much ofhis time discussing with traders, fund managers and hedgefunds their requirements for automated trading. So whatare the important factors to consider in deciding whether toautomate? "It depends on the individual trader, the desk,how much automation you want; there are many variables",he explains.

"The important question is whether your technology canallow you automate. Technology really is the impetus here.As they originally discovered in the US, the pools of liquid-ity represented by the various ECNs such as Archipelagoand the like couldn't be accessed at one time using the tele-phone so the appropriate technology had to be employedto achieve this. This is now happening in the UK and else-where. Moreover, the buy-side is more transparent abouthow they trade and achieve best execution. The technologyhas now become a selling point for asset managers to theirinvestors".

Degree of automationThe question for a buy-side house looking to automate isdeciding to what extent to do so. According to Adams,

every house is different and there is now an increasingtrend for pre-trade analytics. As he explains, "If a portfoliomanager has 100 names he wants to deal in today, how dowe know as traders how to buy and sell those stocks? Thebrokers such as Citigroup, Credit Suisse, Merrill Lynch andmany others have all got pre-trade tools. Whereas previous-ly the buy-side dealer might send his 100 names to threedifferent brokers and get three different sets of numbersback on three different platforms, technology now exists tointegrate these multiple pre-trade numbers into the samescreen".

Adams continues, "For example, one broker says theimpact for the pharmaceutical sector will be six basispoints, one says seven basis points and another six. If theyare all within the same benchmark then normal rules apply;they will come back with suggestions for how to executeyour trade into the marketplace. On the other hand, if thethree brokers come back and say the impact will be six, 23and the other 40, then clearly there is sufficient uncertaintyto be careful about those names. This is perhaps because acompany announcement is due or for some other funda-mental reason. At that point the buy-side dealer decides thestrategy to best employee, be it TWAP, VWAP or others. Soall of these strategies then become part of what you canuse, as a trader, to add value."

The question then for the dealer is: which algorithm pack-age do you employ? Portware offers three options: off-the-shelf broker algorithms, Portware algorithms, or thePortware architecture allows the client to develop and runcustomized client algorithms within their server. Whatoption a client goes for depends where they are in theprocess of automation. "The majority of clients opt forthe broker algorithm", says Adams, "but hedge funds, for

Stuart Adams of Portware discussesthe advance of automated and algorithmic trading in London andthe choices now available to the buy-side community.


example, are increasingly able to develop their own propri-etary algorithms in-house instead of simply using a brokeralgorithm if it makes more sense for them. It also dependson the resources available to the client".

StrategiesThe most discussed algorithmic strategy is VWAP -Volume Weighted Average Price. But different strategiesmay be more appropriate than others for different clients."It really comes down to two things", says Adams, "Itsimportant to have a strategy that listens for events whereyou are picking up micro changes in market conditions thatyou may miss if you were using normal means. Also, if youare a traditional buy-side dealing desk, how many trades canyou physically handle? You have to use the automatedprocess so you can get the trades into a strategy and off thedesk so they are slicing into the marketplace minimisingyour impact and allowing you more time to concentrate onthe names where you can add more value."

However he adds, "It's not just fire and forget. It really isabout sending it off using a broker or proprietary algorithmthat is listening for every bit of information that's comingback from the marketplace. Using a benchmark, you wantto let that trade run but be told immediately if anythinglooks like it's going out of line."

A plethora of algorithms Portware currently offers more than 30 different sets ofbroker algorithms. With all of the major banks now incor-porated into their platform and each of these firms offer-ing between five and twelve algorithms in addition toPortware's own, that's a lot of choice. While all offer theVWAP algorithm, the main difference between them prob-ably comes down to the client-broker confidence factor.However, any mathematical difference between the brokerVWAP strategies, for example, will probably lie in the his-torical volume data it is based on. This may depend onwhere their data comes from and if the broker has addedany additional factors to it in order to calculate VWAP.

Algorithms are now so widely used on the buy and sellside that there is the impetus for firms to develop new pro-prietary algorithms. Brokers and vendors are responding tothis, says Adams. "For instance, with VWAP you can havea simple vanilla strategy just looking at volume, or there's arisk adjusted volume strategy or qualifying volume that willembellish a simple 20-day or 20-day moving average vol-ume figure. This is where the brokers are making the differ-ence. The broker-client relationship is very important ineducating which algorithms you may use".

The next question to ask then is, can you beat its per-formance and will you be told if you're out of line duringexecution. Needless to say, with adopting a passive strategysuch as VWAP, there are risks. "If I'm putting out an orderinto a VWAP strategy then I'm just non-actively participat-ing for a certain period of time. If a large trade comes onto

the market place you have to play catch up. So the risk ifyou aren't using the right technology is that you may not begetting the real-time feedback needed to react to thesechanging conditiosn. With the right technology and multi-ple benchmarks you are able to intervene and have a muchbetter chance at success".

Costs With the application of so much technology, costs are obvi-ously a factor. However, Adams suggests that if houses arenow saying that they are capturing alpha because of elec-tronic trading, then they may pay for it themselves if notpaid for by a broker. "The cost has to be balanced againstthe return", he explains, "I have recently visited a tradition-al London buy-side house that has a lot of alternativestrategies using algorithmic trading. The performance feethere is shared with the dealing desk because the perform-ance of that desk has added value to the fund".

The trading community appears to be realising more andmore the value that can be added through the use of algo-rithmic trading. Indeed, a recent independent researchreport by the Tower Group has said that the buy-side nowneeds independent EMS technology. "This is an in-your-face comment that can't really be ignored any more. Notlong ago it was a matter of employing EMS technology togain an execution edge over your competitors, but now it'salmost mandatory just to keep up. The next question is howto best employ this technology to stay a step ahead of thecrowd. This is where the application of strategies and theneed for versatile technology comes in."

The futureApart from a general increase in the adoption of automat-ed trading, how does Adams see things developing over thenext few years? "With the use of black boxes, the propen-sity to trade have become much more sensitive to events,price changes etc. This has increased the likelihood of highfrequency trading which, incidentally, produces greatermarket volatility. Insufficient bandwidth at the exchangesand ECNs is still a problem when it comes to high frequen-cy trading. This should eventually be resolved. I also expectto see greater fragmentation of liquidity as there is a ten-dency for the average trade size to fall".

With there having been traditionally more technology onthe sell-side, Adams thinks this could be a driver to moreautomation as more traders from the sell-side move over tothe buy-side. As he says, "the sell side are then able to bringthe tricks of the trade and their expertise to the buy-side".Furthermore, algorithmic trading has traditionally beenassociated with the equity market, but Adams sees thischanging too. "There will be more use of algorithms in theFX space with them taking direct feeds from FX providers.The technology will bring everything together into a brokerneutral, multi-asset platform that will be the industry stan-dard".

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