Momentum Investing: An Empirical Study

Momentum Investing An Empirical Study

A White Paper by: Q3 Asset Management Adam Quiring Principal Partner Bradford Giaimo Principal Partner Eric Detterman Research & Strategy Development

December, 2012

Momentum Investing: An Empirical Study

Copyright © 2012 Q3 Asset Management

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of the copyright owners.

All brand, company, and product names are used for identification purposes only and may be trademarks that are the sole property of their respective owners.

This white paper may provide general investment information from sources deemed reliable but is in no way a solicitation to buy or sell any security. Past performance is not indicative of future results. There is no assurance that any strategy presented herein will succeed in the future. Data is provided for informational purposes only and should not be construed as investment advice. There is risk of loss with all investment strategies. All data is considered hypothetical. Hypothetical performance results have certain inherent limitations. Unlike an actual performance record, simulated trades do not represent actual trading. Also, since the trades have not actually been executed, the results may have over or under compensated for the impact, if any, of certain market factors such as lack of liquidity. You may have done better or worse than the results portrayed. Hypothetical testing does not involve financial risk and therefore may not necessarily depict an investor’s ability to tolerate such risks. Mutual funds used in the research for this white paper may or may not be available to use in the future. Additionally, such funds may not have always been available on a specific trading platform in the past. Historical data used in testing is provided by Commodity Systems, Inc. (CSI) and Morningstar. Results do not take into consideration any tax consequences that may arise from an active investment approach.


Document No.: 201201

Published by Q3 Asset Management, December 1, 2012

Any comments or questions relating to the material contained in this document may be submitted to:

Q3 Asset Management 2175 Cole Street Birmingham, MI 48009

(248) 566 – 1122

[email protected]

www.q3tactical.com A Wh i t e P ap e r P u b l i s h ed b y Q 3 A s s e t M a n a g e m e n t 2

mailto:[email protected]


Table of Contents

Executive Summary 4

Background 5 Active vs. Passive Investing ............................................................................... 5 Removing Emotion - The Key to Success .......................................................... 6

Momentum Investing 7 Momentum Definition ........................................................................................ 7 Momentum Research .......................................................................................... 7 Momentum Strategy Background ....................................................................... 8 Momentum Strategy ........................................................................................... 8 Momentum Strategy Within Market Environments ......................................... 10

Conclusion 12

About the Authors 13 Eric Detterman ................................................................................................. 13 Adam Quiring ................................................................................................... 13 Bradford Giaimo ............................................................................................... 13

About Q3 Asset Management 13




Executive Summary

For years, investors - both professional and amateur alike, have been attempting to “beat the market.” The efficient market hypothesis asserts that it is impossible to do so with less risk than a buy-and-hold approach. Severe market downturns coupled with emotionally driven investors have led retail investors to underperform. Research shows that during times of stock market duress, retail investors exit their positions and re-enter the equity market as conditions improve, often at higher prices. This research shows that as a result of these actions the average investor underperforms the benchmark.

We present a rule-based momentum investing approach which removes emotion from the investment process. The system is based upon the market phenomenon of trend persistency. The system presented outperforms a value-based system (buying weakness) and passive approach on both an absolute and risk-adjusted basis. We then improve upon the momentum system by analyzing the broad market environment prior to re-allocating. The resulting momentum strategy within market environments presented outperforms a pure momentum system, value-based system and benchmark on an absolute and risk-adjusted basis over the 20+ year test period.

The momentum research described in this paper can be applied in many ways and implemented across numerous investment products.



Background The New York Stock Exchange opened its doors in the late 1700’s and ever since, investors - both professional and amateur alike, have attempted to “beat the market.” Quantitative investment strategists have been on an endless pursuit to identify the “holy grail” of investing. Their objective is to find an approach that consistently delivers risk-adjusted returns that exceed that of a passively managed benchmark. While we believe that there is no such thing as perfection when it comes to consistently beating the market, our research indicates that there are indeed methods of investing that have demonstrated the ability to add value, through improved risk-adjusted returns, over prolonged periods of both bull and bear markets.

This paper will present Momentum Investing as one method to help investors achieve superior risk-adjusted returns across a range of market environments. Both a conceptual example of momentum investing and a completed investment strategy are presented. Active vs. Passive Investing Can you beat the market?

The efficient market hypothesis asserts that it is impossible to outperform the stock market with less risk. The theory states that all public and private information is instantaneously priced into stocks at all times. Those who adhere to the theory are likely to utilize a buy-and-hold approach comprised of a diverse blend of low cost index funds. Most refer to this type of investing as traditional asset allocation or “passive” investing.

There is a huge assumption in this hypothesis - Do “passive” investors perform, over the long haul, at the same level as the benchmark? If not, how does this impact the efficient market theory?

Are investors rational?

A major flaw associated with traditional asset allocation has been demonstrated time and time again over the course of the last two decades - investors allow emotion to dictate their investment decisions at the most inopportune times. Severe market downturns coupled with emotionally driven investors have led the retail investor to dramatically underperform a passively managed benchmark. During times of stock market duress, retail investors exit their positions in the stock market due to fear. Once the market conditions improve, they re-enter the equity market, often at higher (worse) prices. While many claim to be “passive investors,” the fact of the matter is that very few “buy and hold” investors actually exist.

Each year, market research firm Dalbar, Inc. conducts a study to compare the average investor’s return relative to the broader market. For 2011, the average equity fund investor experienced a loss of 5.73% compared to a gain of 2.12% for the S&P 500. The average investor performed 7.85% worse than the benchmarki.

There’s always a bull market somewhere, no

matter what sort of economic conditions

exist. The challenge lies in identifying the sub

sectors within the equity and fixed income markets

that offer the best opportunity for success



Over the course of the last 20 years, the average equity investor averaged 3.49% annually compared to 7.81% for the S&P 500ii. To put that into perspective, a $100,000 initial investment in the benchmark, without any changes over the test period, resulted in the ending balance being $441,950. The average retail investor, who made changes over the test period, resulted in an ending balance of $186,821, or a difference of $255,129.

Average Investor Performance over past 20 years

Performance Impact

Removing Emotion - The Key to Success

The majority of successful investors are methodical in their approach. By removing emotion from the investment process and focusing upon a time-tested rule based methodology, the probability for success increases exponentially. For the remainder of the paper, we present momentum investing as a viable rule based methodology that can be used as the foundation of a diversified portfolio. We compare a momentum based approach to both a value (buying weakness) and buy-and-hold investing approach.

Dalbar’s Quantitative Analysis of Investor

Behavior (QAIB) study has been conducted each

year since 1994. Their research shows that the

average investor has dramatically

underperformed a buy-and hold approach over

the last 20 years.

3.49%

7.81%

-4.32%

Avg. Investor Benchmark Difference

$-

$100,000

$200,000

$300,000

$400,000

$500,000

$600,000

1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

Benchmark Average Investor



Momentum Investing "Perhaps the best known investment paradigm is buy low, sell high. I believe that more money can be made buying high and selling at even higher prices. I try to buy stocks that have already had good price moves, that are often making new highs and that have positive relative strength. These are stocks that are in demand by other investors. What is the risk? Obviously, the risk is that I'm buying near the top. But, I would much rather be invested in a stock that is increasing in price and take the risk that it may begin to decline than invest in a stock that is already in a decline and try to guess when it will turn around."

Richard Driehaus – Driehaus Capital Management

Richard Driehaus is known by many as the “Father of Momentum Investing.” He currently manages over $10 billion using variations of the approach. Other early momentum investors include George Soros and William O’Neil, the founder of Investor’s Business Daily. One of Mr. O’Neil’s associates, David Ryan won the U.S. Investing Championship in 1985 with a 161% return. He came in second in 1986 with 160% return and followed that up with another first place finish and yet another triple digit returnii. When asked how he did it, Ryan replied “To sum it up, I’m looking for the strongest stocks in the market, in terms of both earnings and the technical picture (momentum investing)… The more disciplined you can get, the better you are going to do in the market.”

Momentum Definition

The success of momentum investing hinges upon the market phenomenon of trend persistency. Psychology among stock market participants, more specifically fear and greed, creates a tendency for the strongest performing stock market sectors to continue to outperform over the short-term (3-9 months). In other words, some market participants experience fear that they will miss out on the trend and ultimately invest. Others, who already have invested, allow greed to influence their decision to add to their winning position. Each of these actions further perpetuates the trend. Because momentum investing is contrary to what many investors are taught (“buy low & sell high”) the idea of selling losers and buying winners is difficult for some investors to do.

Momentum Research

Our studies pertaining to momentum investing over the years have centered upon our desire to create a robust, retail-oriented alternative to traditional asset allocation. While outperformance is important, maintaining some level of diversification in an effort to reduce drawdowns and produce compelling risk-adjusted returns has been our goal.

When utilized properly, our research indicates that momentum investing maintains the ability to outperform a passively managed benchmark on a risk-adjusted basis over extended periods of time.

While momentum investing may come in and out of favor, over longer

Research indicates that the investor who follows a systematic approach and removes emotion from the investment process has a

higher probability of success than those that do

not.



periods, research has shown it to be one of the most consistent and reliable forms of investing.

Momentum Strategy Background

While the momentum strategies described below have been tested across different mutual fund universes and platforms with favorable results, in this paper we describe the strategy using Fidelity Sector Funds. There are approximately 40 sector equity funds and 10 income funds available to invest in within our designated universe.

Research Overview

We begin our research test on December 31, 1990, and analyze over 20 years of data. We assume an initial investment amount of $100,000. Further, no cash additions or withdrawals are made during the test period and no management fees or taxes are deducted.

Momentum Strategy

This momentum strategy evaluates a single variable in order to determine an optimal allocation: mutual fund momentum. The strategy invests in the six highest ranked mutual funds, equally weighted, under the premise that they will continue to be strong performers for the next period. The rules to the strategy are outlined below.

Approximately every 45 calendar days:

Step #1: Momentum Algorithm:

Analyze and rank all available mutual funds based on an aggregate view of their 1, 3, 6 and 12 month returns. Our objective is to blend these time frames to come up with an “average” look back of 4 to 5 months.

We then compare this to a common investment approach - value investing (buying weakness). The “value system” presented invests in the six weakest mutual funds, equally weighted, based on the same ranking algorithm as the momentum system previously described.

Test Results

The equity curve and performance metrics presented below demonstrate the potential of a momentum based investing approach. Performance of the momentum strategy (MOMO1) is superior to that of a value-based approach (VALU1) as well as the benchmark (Vanguard S&P 500 Fund) on both an absolute and risk-adjusted basis.

Some of the equity sector funds included in our

analysis:

Biotechnology

Consumer Staples

Financial Services

Natural Resources

Utilities

Energy

Construction & Housing

Natural Gas

Transportation

Retailing

Electronics

Gold

Automotive

Defense & Aerospace

Health Care

Technology

Banking



Momentum Strategy Performance

Annual Results Summary

$-

$500,000

$1,000,000

$1,500,000

$2,000,000

$2,500,000

$3,000,000

$3,500,000

$4,000,000

$4,500,000

$5,000,000

S&P 500 Index VALU1 MOMO1

While the momentum approach performed well for the entire test

period, it did so with above average volatility. Despite the fact that the

model is still trying to recover from a 2011 drawdown, the research

demonstrates just how powerful momentum investing can be.



Momentum Strategy Within Market Environments

Numerous studies have attempted to identify when it is favorable to invest in the stock market and when it is favorable to be out of the market or “on the sidelines.” While there are a variety of methods that can be used in this area, there has been research to suggest that investing in the stock market only when it is in a “positive trend” can reduce risk. A simple way to quantify this is to only invest in the equity leaders when the stock market is trading above an intermediate-term moving average.

This version of the momentum strategy adds another element to the one previously discussed - market environment as a binary strong/weak output. It evaluates two variables in determining the optimal allocation: market environment and fund momentum. The strategy invests in 3-6 mutual funds for a portfolio based on the following.

Approximately every 45 calendar days:

Step #1: Market Environment:

Identify market environment as ‘strong’ or ‘weak’

Step #2: Momentum Algorithm:

Analyze and rank all available mutual funds based on an aggregate view of their 1, 3, 6 and 12 month returns

• If the market environment is ‘weak’ invest in the three highest-ranked income funds.

• If the market environment is ‘strong’ invest in the six highest-ranked equity and income funds.

Once again we compare this to the value investing approach. The “value system” presented in this example invests in the weakest six mutual funds based on the same ranking algorithm as the momentum system previously described.

Test Results

The below equity curve and performance metrics demonstrate the potential of a momentum based investing approach and incorporating a market environment filter. Performance of the momentum strategy (MOMO2) is superior to that of a value-based approach (VALU2) as well as the benchmark on both an absolute and risk-adjusted basis. The addition of the market environment algorithm improves the performance of the momentum strategy (MOMO1) on both an absolute and risk-adjusted basis.

Some of the fixed income funds included in our

analysis:

Investment Grade

Short-Term

Ginnie Mae

Money Market

Inflation Protected

Intermediate Government

Intermediate

Mortgage

Government Income



Momentum Strategy Within Market Environments

Annual Results Summary

The addition of a market environment filter improves both

risk-adjusted and absolute returns of the momentum strategy over the

entire test period. It’s interesting to note, however, that for the first 10

years a momentum approach with no market enviornment analysis is

superior. It makes sense to conclude that through secular bull market

enviornments, eliminating the market enviornment filter produces better

returns; it also makes sense to conclude that through secular bear market enviornments the ability to

play defense is essential.

$-

$1,000,000

$2,000,000

$3,000,000

$4,000,000

$5,000,000

$6,000,000

$7,000,000

S&P 500 Index VALU1 VALU2 MOMO1 MOMO2



Performance Metrics Summary

Conclusion

Since the beginning of the stock market, investors- both professional and amateur alike, have been attempting to “beat the market.” Over the years, severe market downturns coupled with emotionally driven decisions has led retail investors to significantly underperform. Research shows that during times of stock market duress, retail investors exit their positions and re-enter the equity market as conditions improve, often at higher prices. One such study by Dalbar, Inc. shows that over the past twenty years, the average equity investor averaged 3.49% annually compared to 7.81% for the S&P 5001.

In this paper we presented two versions of a rule-based momentum investing approach, each of which removes emotion from the investment process. Both systems are based upon the market phenomenon of trend persistency caused by the fear and greed of market participants. As demonstrated, the first momentum system presented outperforms both a value-based system and benchmark, on an absolute and risk-adjusted basis over the 20+ year test period. While the second, with the addition of a “market environment filter” outperforms a pure momentum system, value-based system and benchmark on an absolute and risk-adjusted basis over the same 20+ year period.

Those that subscribe to the efficient market hypothesis will tell you that it is impossible to outperform the stock market with less risk – we disagree. The research presented in this paper can be implemented across numerous investment products and platforms. Furthermore, the research is simple enough for a retail investor to understand. Such an understanding should provide investors with the confidence needed to stick with a strategy when their emotions might be telling them to do something else.

Performance Metric MOMO1 VALU1 MOMO2 VALU2 Benchmark Annualized Return 18.51% 9.45% 20.63% 10.66% 9.00% Cumulative Return 3978% 618% 5904% 814% 557% Sharpe Ratio 0.77 0.32 1.05 0.66 0.39 Maximum Drawdown (%) 29.0% 61.0% 22.1% 23.5% 51.0% Max. Drawdown Length (Months) 43 73 23 49 74 Alpha 10.75% 0.00% 14.78% 5.18% N/A Beta 0.79 1.08 0.46 0.40 N/A

As the performance metrics demonstrate, using momentum and adjusting exposure within various

market enviornments (shown in bold) proves to be the optimal method. Not only does the approach produce the highest risk-adjusted returns, but the maximum drawdown, both in length

and size, are superior to other methods.



About the Authors

Adam Quiring

Email: [email protected]

Adam is a Principal Partner at Q3 Asset Management. His career started on the floor of the Chicago Board Options Exchange in 1999. He has worked for both traditional and alternative investment firms including Munder Capital Management. Adam graduated with a degree in business from Northern Michigan University. He currently maintains a Series 65 license.

Bradford Giaimo


Brad is a Principal Partner at Q3 Asset Management. His career started on the floor of the New York Mercantile Exchange in 1982. From 1984‐1986 he worked for Paul Tudor Jones as a proprietary trader for Tudor Investment Corporation. At the end of 1986 he left Tudor to become a member of the New York Board of Trade where he spent the next 12 years as a floor trader. It was during this time that he developed his affinity for quantitative market analysis. Mr. Giaimo is a graduate of the University of Hartford and maintains a Series 65 license.

Eric Detterman


Eric focuses upon Research and Strategy Development at Q3 Asset Management. He graduated with a BS Economics, with honors from Oakland University. Throughout his career he has worked in a diverse range of quantitative and information technology (IT) roles. In early 2008 he left a corporate IT position to focus on developing and running his own quantitative trading programs. His experience in software development and process re-engineering has helped to build the structured and repeatable strategy design, development and testing process in place at Q3 Asset Management.

About Q3 Asset Management Established in 2006, Q3 Asset Management is an independent Registered Investment Advisory firm offering a diverse blend of quantitative investment strategies. Our mission is to provide financial advisors and their clientele with an investment approach that maintains the ability to adapt to changing market conditions. We are firm believers that true diversification lies in combining a strategic blend of non-correlated investment programs.

Q3 Asset Management is located in Birmingham, Michigan. Our investment advisory services are offered through a variety of providers including Trust Company of America, TD Ameritrade, Fidelity, Rydex, ProFunds and Jefferson National. Additional information on Q3 Asset Management can be found at www.q3tactical.com.

i,ii Source: Quantitative Analysis of Investor Behavior, 2012 DALBAR, Inc. www.dalbar.com ii Source: Schwager, Jack (1990) Market Wizards.





Momentum Investing: An Empirical Study

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