Dual momentum investing pdf download






















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Dreaming of a sea or tree change? Keith Hay Homes national sales and mar. This is an excellent book on the various forms of price momentum: why they work, including a very clever way to use them. I highly recommend investors read this book. Gary Antonacci takes us on a comprehensive tour of investment methods, exploring their strengths and weaknesses, and lays out a strong case for combining absolute and relative momentum.

I consider Dual Momentum Investing an essential reference for system designers, money managers, and investors. Dual Momentum Investing is a treasure of well-researched momentum-driven investing processes. After a thorough and enlightening review of historical momentum writings and a brief, critical review of modern portfolio theory, he clearly shows a number of different methods that anyone who is serious about a long-term strategy will find easy to implement.

This is one of those five-star books; it is logical and easy to grasp. In Dual Momentum Investing , Gary Antonacci presents a clear and scholarly sound case for the success of a simple momentum-based strategy. It is easy to implement, yet its quantitative nature helps you avoid your own behavioral biases.

This is an ambitious and must-have book. This is a must-read for both individual investors as well as financial advisors.

It will forever change the way you think about developing investment and asset allocation strategies. Gary Antonacci provides a fantastic and valuable viewpoint of dual momentum investing. This book is highly informative, substantive, and readable for the sophisticated investor. Gary presents a well-crafted balance between academic findings and application of this emerging topic.

Few authors can review the breadth of competing investment theories and practices in such an accessible manner. Even fewer can make their own contributions. All rights reserved. Except as permitted under the United States Copyright Act of , no part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written permission of the publisher. All trademarks are trademarks of their respective owners.

Rather than put a trademark symbol after every occurrence of a trademarked name, we use names in an editorial fashion only, and to the benefit of the trademark owner, with no intention of infringement of the trademark.

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This is a copyrighted work and McGraw-Hill Education and its licensors reserve all rights in and to the work. Use of this work is subject to these terms. You may use the work for your own noncommercial and personal use; any other use of the work is strictly prohibited. Your right to use the work may be terminated if you fail to comply with these terms. McGraw-Hill Education and its licensors do not warrant or guarantee that the functions contained in the work will meet your requirements or that its operation will be uninterrupted or error free.

Neither McGraw-Hill Education nor its licensors shall be liable to you or anyone else for any inaccuracy, error or omission, regardless of cause, in the work or for any damages resulting therefrom. McGraw-Hill Education has no responsibility for the content of any information accessed through the work. My relationship with Gary was born via the same mechanism through which I meet many fascinating folks: a blog romance. I was thinking about a momentum-related content piece for TurnkeyAnalyst.

Here we go again— another practitioner posing as a serious academic researcher. The further I read, the more impressed I became. The paper was well written, clear, scientific in its construction, and read like an academic journal article. I had to learn more. After multiple conversations via e-mail and phone, I decided I had to meet Gary in person.

As I waited in the lobby of the Hyatt Regency watching herds of famous and infamous academics scurry along to the various sessions, a curly haired, low-profile man confidently strolled through the fancy double doors in a pair of jeans and a short-sleeved collared sheet. This was no tweed-clad academic with Coke bottle glasses. We were running late, so we ran out the door toward the lake where the finance sessions were under way. Gary and I strolled outside with our coffee, and he started shedding some light on his background.

I knew that a military background often drives certain character traits that are useful in the investing world. I lived in India for a few years, went on tour as a comedy magician for a while, was an award-winning artist, and I have an MBA from the Harvard Business School.

I almost followed your same path when I was your age. I applied to the Chicago Finance PhD program and was accepted. I really wanted to be an academic researcher. So what is the moral of the story here, and why have I spent so much time describing my relationship and experience with Gary?

My hope is that you can identify, as I did, that Gary is a unique person with unique talents. Gary has a way of compiling massive amounts of research from diverse areas and synthesizing it in such a way that even a struggling momentum half-wit like me can actually comprehend what is going on.

And make no mistake. What Gary has done is extremely challenging. It requires broad- ranging knowledge and an ability to connect the dots across many domains.

I know, because I have tried. My own research on value investing and behavioral finance led to my coauthored book on value investing, Quantitative Value. My book serves as a reminder that 1 I will never be Buffett, and 2 combining a systematic decision process with a sound investment philosophy has historically been a successful way to compound wealth over time. I was feeling a bit jealous. I hope everyone enjoys the read as much as I did, and most importantly, I hope you learn something that makes you a better investor in the future.

Wesley R. If I have seen further, it is by standing on the shoulders of giants. Jones, who painstakingly hand-calculated and published the very first quantitative study of momentum in Practitioners today, me included, still incorporate momentum in much the same way that Cowles and Jones presented it.

I wish to thank Wes Gray for his encouragement in getting me to put words to paper. I am indebted to Tony Cooper for his insightful comments and worthwhile contributions to this book. Finally, I am grateful to my excellent editorial team of Jonathan Lobatto, Dr. Profit in the share market is goblin treasure; at one moment, it is carbuncles, the next it is coal; one moment diamonds, and the next pebbles.

The volatility is too significant. Almost any asset can suddenly become much more risky. You need something more to manage risk well. Now somebody needs to pay for that lunch.

Because financial markets have become progressively more integrated and correlated, multiasset diversification can no longer protect investors from severe market losses.

Such losses can cause investors to overreact and convert temporary setbacks into permanent ones by closing out their investments prematurely.

We need a way to earn long-term above-market returns while limiting our downside exposure. This book shows how momentum investing can make that desirable outcome a reality. Momentum, or persistence in performance, has been one of the most heavily researched finance topics over the past 20 years. Academic research has shown momentum to be a valid strategy from the early s up to the present, and across nearly all asset classes.

I wrote this book to help bridge the gap between the academic research on momentum, which is extensive, and its real-world application, which is still minimal. The first goal of this book is to explain momentum principles so readers can easily understand and readily appreciate them. I present the history of momentum investing and bring readers up to speed on modern financial theory and the possible reasons why momentum works.

I then look at a wide range of asset choices and alternative investment approaches. I finally show how dual momentum—a combination of relative strength and trend-following methods that I introduced in two award-winning research papers—is the ideal way to invest.

Using only a U. I am always amazed when I think of how much time and effort most people put into accumulating wealth and how little study and effort they put into finding the best ways of preserving and growing that wealth. Warren Buffett says that risk comes from not knowing what you are doing. This book should help remedy that situation and steer you in the right direction.

Dual Momentum Investing is more than just an introduction to momentum investing ideas. It is also a practical guide to help investors and investment professionals tune in with market forces and profit from this newfound knowledge. I have tried to make the book interesting and useful to as many readers as possible.

I include some advanced material for those interested in an in-depth treatment of the subject, while also keeping the book understandable to more casual readers. I provide a glossary for those who may need help with the vocabulary of modern finance. So, let us get started. Never trust the experts. However, that is not correct. Let me tell you how it really happened.

At that time Smith Barney was a prestigious investment banking and institutional brokerage firm similar to Goldman Sachs, Salomon Brothers, and First Boston. Along with the rest of the Street at that time, Smith Barney wanted more of a retail distribution network, so they had recently acquired Harris Upham, a retail-oriented wirehouse.

As is usual after these kinds of acquisitions, Smith Barney let go the redundant operations of Harris Upham. In those days, there was no electronic marketplace.

A top-notch OTC market maker could become a terrific profit center for a firm. They could slant their bids and offers to end up with larger positions in stocks they really liked, and smaller or short positions in those they disliked. Bob was one of the very best stock pickers in the business.

Smith Barney was proud to have Bob onboard. They sent him around to all their offices so representatives could learn more about Bob and feel comfortable directing business his way. Soon after the merger, Bob came around to our office to introduce himself and explain what he could do for us. It was not Bob and what Bob did that opened my eyes, but rather it was the story that he told us. Bob arrived about an hour before lunch and gave an impressive presentation explaining some of the finer points of OTC market making.

It was obvious to everyone there why Bob was so admired and respected. One of my colleagues complimented Bob on his superior trading ability and his profit-generating capability. In fact, this person has done better in the market than anyone else I know.

Bob had our complete attention. Would you like to hear how she does it? Now he was about to tell us how she did it. As they say, you could have heard a pin drop. She bought U. Steel, U. Shoe, U. Gypsum, U. We did not know if Bob was serious or if he was putting us on. After a number of years, she wanted to buy some additional stocks. However, for days, and then weeks, I could not stop thinking about Dee.

Dee had access to some astute investment information herself. Had she just been incredibly lucky? After a few weeks, the answers came to me. She bought stocks only once and held onto them forever. Commissions were a lot higher back then, and this was a significant cost saving. We will see later that this is often a significant drag on investor returns. Lack of portfolio turnover and emotionally based decision making were not the whole story, however. Dee also did not have to pay management fees to anyone.

This was not true of most investor portfolios at the time. They usually had a bias toward a particular investment style, such as defensive, growth, large cap, and so on.

It was like the market itself—equally balanced among small cap, large cap, value, growth, and just about every other factor. She did so without the need for brokers, money managers, or anything else, except a dictionary. Here are the lessons I took away from my understanding of why Dee was successful:.

This is the easiest way to earn risk-adjusted excess return alpha. One should diversify with respect to company size, investment style, industry concentration, and other biases. Very few investors do. Replicating the market portfolio may be a good thing. Based on these realizations, I decided to quit the brokerage business.

It no longer made sense for me to be a stock jockey saddling investors with high costs and overconcentrated portfolios trying to beat similar accounts handled by other stock jockeys to an ever-elusive finish line. I saw there were now two options left for me with respect to professional investment management.

The first was to become an efficient marketeer, which sounded similar to being a Mickey Mouseketeer and, to me, was no less silly. I viewed efficient markets like I viewed Ptolemaic astronomy, with both based largely on a priori assumptions. My second option, according to those in academic finance at that time, was to become like Don Quixote, tilting at the windmills of efficient market theory. EMH is the belief that prices of stocks fully reflect all publicly available information about them.

This means that no one can expect to beat the market consistently. I had toyed briefly with the EMH idea. However, I never attended due to frightening thoughts I had of being tarred and feathered as a heretic on the University of Chicago quadrangle.

The price movements, therefore, represent everything everybody knows, hopes, believes, and anticipates. The value which they acquire may be regarded as the judgment of the best intelligence concerning them.

Bachelier compared the behavior of stock market buyers and sellers to the random movement of particles suspended in fluid. Bachelier concluded that stock price movements are random, and it is impossible to make predictions about them. Prior to this, in , Jules Regnault used a randomness model to say that the deviation of stock prices is directly proportional to the square root of time.

Bachelier, however, was the first to accurately model stochastic processes. These were called Brownian motion, after the Scottish botanist Robert Brown, who in first noted the random movements of pollen grains suspended in water. Einstein got the credit for explaining Brownian motion mathematically in , but Bachelier had already done so in his PhD dissertation written five years earlier. Bachelier was also way ahead of his time with respect to his pioneering work on probability theory.

Paul Samuelson had been working on similar ideas himself. He was delighted to hear from Savage and find out about Bachelier. Samuelson went on to write the bestselling economics textbook of all time in which he strongly endorsed EMH. This was in , the second year of the award.

I will describe the work of Darvas and Levy, who used relative strength momentum-based investing, in more detail in the next chapter. All had consistently outperformed Mr. I could not believe that outperformance by such astute investors was due only to chance or luck. The outcomes of these investors seemed clearly at odds with what academics were saying.

While academics were extolling the virtues of EMH, practitioners like these were doing something completely different, and they were succeeding. Andrew Lo, one of the first economists to look thoroughly at market pricing anomalies, tells how years ago he did some rigorous research on technical analysis. He identified predictable patterns in stock prices, which, to academics back then, was akin to voodoo. If such a model can predict the market, then either the model is wrong or markets are not efficient.

Lo must have done some very good research for his colleague to think up a third alternative, that of erroneous data. Throughout the s and s EMH ruled supreme. Observing correctly that the market was frequently efficient, they went on to conclude that it was always efficient.

The difference between these propositions is night and day. These included premiums on closed-end fund and government-backed mortgage securities that are not arbitraged away, and ubiquitous market bubbles that imply substantial deviations of prices from intrinsic values over extended periods. For better or worse, I took upon myself the formidable task of trying to identify and exploit true market anomalies and inefficiencies.

Don Quixote, move over. There were no publicly available data feeds back then, so I hired an electrical engineer to tear apart a quote machine, dump the data into a microprocessor, and then feed that into our office minicomputer. I formed partnerships with market makers on all the option exchange floors, did well initially, and then suffered the same fate as later befell LTCM.

This was due to the same reasons of overleverage coupled with highly unusual events. These traders not only were very successful; their results were also largely uncorrelated to one another due to their different trading approaches and diverse portfolios.

Portfolio optimization fit this situation to a tee, and my investment partnerships prospered. I felt fully vindicated in venturing outside the realm of efficient market theory. I did not know, however, if I would ever again find another opportunity that was this rewarding. However, I was motivated to keep looking. Commodity trading has capacity constraints. Some of the best traders end up returning investor funds and trading mostly their own accounts, which is what happened with several of my traders.

In addition, the generous commodities risk premium that speculators enjoyed from the s to the s had largely dissipated by the s. Speculator participation had risen sharply, and there were many more speculators around to share in the limited amount of risk premium provided by hedgers. It was time to move on. Little did I know at the time that it would take nearly 20 years before I would find another opportunity to exploit market trends using what is essentially the same principle—systematic price momentum.

With it came challenges to rational expectations and the EMH. It is remarkable in the immediacy of its logical error and in the sweep and implications for its conclusions. His textbook taught that the stock market was perfectly efficient, and that nobody could beat it. But his own money went into Berkshire Hathaway and made him wealthy. Something new under the sun. Maybe the wheel, the alphabet, and Gutenberg printing were not that great after all.

The burgeoning field of behavioral finance led some to question whether investors always acted rationally and in their own best interests. People acting in emotional and irrational ways could cause prices to depart systematically from their fundamental values in predictable ways.

Maybe the markets could be beat after all, since irrational investors might allow anomalies to persist. In light of this possibility, momentum started to receive attention from the academic community beginning in the early s.

Behavioral factors could be used to explain many of the characteristics of momentum. Not only did momentum research benefit from EMH losing its hold over modern finance, but the findings of momentum researchers added considerably to the body of knowledge that itself contradicted the efficient markets hypothesis. The following chapters will show how I combined the best elements of academic momentum research, added a few ideas of my own, and came up with a simple and practical method for generating exceptional profits with less risk by using momentum.

Furthermore, I will show how you can apply this methodology to the largest liquid markets having high expected long-run returns. I will also show how momentum fits into the strange and mysterious world of modern finance.

Then we will look at the logical underpinnings behind momentum to help you better understand how and why it works. Next, we will look at asset choices and alternative investment opportunities. I will then be ready to present a simple and effective momentum-based model that you can use.

After presenting my model, I will explore other momentum approaches and additional applications using dual momentum. By the end of the book, you should have a good understanding of momentum, as well as everything you need to know in order reap its rewards.

IT is the tendency of investments to persist in their performance. Investments that have done well will continue to do well, while those that have done poorly will continue to do poorly. I will take you through its evolution. It is unlikely Sir Isaac had investing in mind when he came up with this law. If he did, then he should have paid more attention to apples falling from trees and reminded himself that what goes up, must come back down.

Newton lost a fortune in the South Seas stock bubble of — by buying too late and holding on too long. The first notable person to express momentum principles in investment terms was the great classical economist, David Ricardo. It describes the thoughts and exploits of legendary trader Jesse Livermore. Livermore introduced the momentum idea of buying stocks when they are making new highs. Richard Wyckoff also wrote books beginning in the s that drew heavily on momentum principles. In his book, How I Trade in Stocks and Bonds: Being Some Methods Evolved and Adapted During My Thirty-Three Years Experience in Wall Street, Wyckoff advocated buying the strongest stocks within the strongest sectors and within the strongest index when they were trending up during the marking up phase of their accumulation-distribution cycle.

Wyckoff used his ideas to amass a fortune in the stock market before he retired to a 9. Sloan, the legendary chairman of General Motors. In his bestseller, The Seven Pillars of Stock Market Success, George Seamans recommended that traders buy stronger stocks during an advance and short weaker stocks during declines, which is very much in tune with relative strength momentum investing. On the quantitative side of things, beginning in the late s, Arnold Bernhard, founder of the Value Line Investment Survey, successfully used relative strength price momentum in conjunction with earnings growth momentum.

According to the Value Line website, Group 1 stocks are those ranked highest in performance over the past year and that had accelerating earnings growth. From through , Group 1 stocks had an average annual gain of Group 5 stocks had a —9. Gartley developed momentum-based relative velocity ratings in the s. In his book Profits in the Stock Market, Gartley introduced the world to trend-following moving averages.

Bernhardt and Gartley were both early pioneers of quantitative, rules-based momentum strategies. Jones Cowles was a prominent economist who founded the Cowles Foundation for Economic Research, initially at the University of Chicago and now at Yale. There were no computers back then, so Cowles and Jones painstakingly hand-compiled stock performance statistics from through This was a remarkable accomplishment at that time.

Cowles and Jones found that the strongest stocks during the preceding year had a very strong tendency to remain strong during the following year. Here is some advice Chestnutt gave his newsletter readers:. Which is the best policy? To buy a strong stock that is leading the advance, or to shop around for a sleeper or behind-the-market stock in the hope that it will catch up? On the basis of statistics covering thousands of individual examples, the answer is very clear as to where the best probabilities lie.

Many more times than not, it is better to buy the leaders and leave the laggards alone. In the market, as in many other phases of life, the strong get stronger, and the weak get weaker. Chestnutt also wrote a book on relative strength investing and used this approach to manage successfully the American Investors Fund. From January through March , this fund had a cumulative return of Chestnutt never became well known, but another momentum investor and mutual fund manager at the time did.

Tsai, a colorful figure, championed momentum and increased the popularity of momentum investing to the point that he became the first mutual fund manager to gain celebrity treatment in the press. This idea is right out the momentum playbook. The book describes his adventures as a professional dancer traveling the world while sending off buy and sell cables to his broker.

Darvas would buy strong stocks making new highs, hold them until their momentum began to wane, and then replace them with new price leaders. According to Soros, buying begets further buying in a self-reinforcing process.

We will see in Chapter 4 that positive feedback trading due to behavioral factors is one of the key characteristics of momentum. Momentum has always been the engine behind speculative commodity trading. Richard Donchian launched the first managed futures fund in Donchian thought price movements in stocks and commodities were often too optimistic or pessimistic because they reflected the emotions of the people trading them.

In , Donchian began a weekly commodities newsletter that featured his 5- and day moving average trend-following system. His well-known 4-week channel breakout method inspired other great traders like Ed Seykota and Richard Dennis. I know of no other trader who has his track record over the same length of time. One prominent momentum investor, however, was the outspoken philanthropist and mutual fund manager, Richard Driehaus.

Driehaus began his investment career in Here are a few quotes from Driehaus describing his momentum-based approach:. Perhaps the best-known investment paradigm is buy low, sell high. I believe that more money can be made by buying high and selling at even higher prices ….

I try to buy stocks that have already had good price moves, that are already making new highs, and that have positive relative strength ….

I always look for the best potential performance at the current time. Even if I think that a stock I hold will go higher, if I believe another stock will do significantly better in the interim, I will switch. Even before serious academic research on momentum began in earnest in the s, it was hard to dismiss the practical value and impressive results of relative strength momentum investing.

Levy This confusion between systematic, rules-based momentum and seat-of-the-pants discretionary momentum persists even today.

When academics caught on to momentum, they probably did not want to have their work associated with Levy. They preferred instead to engage in identity theft by changing the name from relative strength to momentum. They were either unaware that this term momentum was already being used by practitioners to mean something similar but different—or they just did not care. Levy later expanded his study and wrote a book on the subject of relative strength investing.

Levy said:. Michael Jensen, a respected academic, criticized Levy for ignoring transaction costs and risk factors. Brush and Boles presented evidence of excess returns from relative strength momentum applied to 18 years of stock data, even after adjusting for transaction costs and risk. Despite the growing evidence of abnormal profits from momentum investing, even after accounting for costs and risk factors, there was still little interest in momentum among academics.

During this time, belief among academic researchers in efficient markets was still prevalent, which is a major reason why momentum never got the attention or respect that it deserved.

Many academics still thought stock market returns followed a random walk process, similar to Brownian motion, where aggressive competition among market participants to exploit any predictable patterns made price changes random and unpredictable.

As the saying goes, if your only tool is a hammer, everything looks like a nail. Academics pounded on momentum until it was barely noticeable. This began to change in the s. Keim and Stambaugh presented evidence that stock returns contain predictable components. This one-day collapse strained the limits of rationality. Academics had also begun documenting persistence in stock prices due to positive serial correlation, which contradicts the random walk theory of stock price movement.

These all cast doubts on perfect market efficiency. Behavioral finance also started gaining traction as a way of explaining the growing number of market anomalies, such as price momentum and mean reversion. The academic community had begun to wake up and take notice. Behavioral finance is the study of the influence of psychology on the behavior of investors and the effect this has on markets.

Behavioral biases helped to resolve some of the growing disconnect between theory and reality in the world of finance. Chapter 4 will shed more light on the rational and behavioral aspects of momentum, including how they help explain why momentum works and why it is likely to continue to work in the years ahead.

This outperformance was essentially the same thing that Cowles and Jones had discovered 30 years earlier. This, and considerable subsequent momentum research on additional data by others, did away with concerns that momentum profits could be attributable to data mining biases.

Quantitative research helped to transform momentum from a discretionary approach to a rules-based one. This was especially true with respect to a 6- to month look-back window.

As an added bonus, a rules-based approach such as this helps remove behavioral bias from the decision-making process and lessens the chance that investors will make poor decisions based on emotional responses to market conditions.

In fact, momentum has been become one of the most heavily researched finance topics over the past 20 years. Since Jegadeesh and Titman, there have been more than academic papers on momentum, including over in the last five years. Research has focused on four areas:. Continuing research has established momentum as an anomaly that works well within and across nearly all markets, including U.

Chabot, Ghysels, and Jagannathan showed that momentum worked well in U. Geczy and Samonov showed that momentum was effective through out-of-sample testing on U.

Over this year history the equally weighted top one-third of stocks sorted on price momentum significantly outperformed the bottom one-third of stocks by 0. In the s, Schwert did a study of market anomalies related to profit opportunities, such as value, size, calendar effects, and momentum. Momentum was the only one that persisted.

Momentum has continued to perform well out-of-sample during the two decades following the seminal studies by Jegadeesh and Titman. The premier market anomaly is momentum. Stocks with low returns over the past year tend to have low returns for the next few months, and stocks with high past returns tend to have high future returns.

Readers can easily satisfy themselves as to the efficacy of momentum by reviewing some of the important academic research papers referenced in this book. DWA manages two mutual funds and four broad- based exchange-traded funds using a proprietary approach that selects for small cap individual stocks using relative strength momentum. Its broad-based funds cover U. DWA reassesses and rebalances its momentum-based portfolios quarterly.

AQR usually rebalances positions quarterly. The fund weights its positions based on volatility and rebalances them semiannually. All of these publicly available products apply relative strength momentum to individual stocks.

Using momentum with individual stocks also results in substantially higher transaction costs than applying momentum to broad asset classes and indexes.

AQR, for example, estimates transaction costs of its U. Also important is the fact that while relative strength momentum can enhance returns, it does little to reduce volatility or maximum drawdown.

These risks may even increase compared to similar portfolios using nonmomentum, buy-and-hold strategies. I n Chapter 7, we will discuss absolute momentum, which can enhance expected returns like relative momentum does.

However, unlike relative momentum, absolute momentum can also reduce extreme downside exposure that is associated with long- only investing.

Absolute momentum aims to beat the market by avoiding the beatings. In Chapter 8, we will construct a simple and practical investment model using dual momentum, which is the amalgamation of both relative and absolute momentum.

A physicist, a chemist, and an economist are stranded on an island with nothing to eat. A can of soup washes ashore. Prior to this, there had been no quantitative way of simultaneously using expected return, volatility, and correlation to determine optimal portfolio combinations.

Markowitz called his methodology mean-variance optimization MVO. During the oral exam defending his Ph. Markowitz received his PhD anyway and went on to become the father of modern portfolio theory. On the practical side of things, there are problems, however, in implementing MVO. As is common with many economic models, the assumptions underlying MVO do not fit the real world very well. MVO results are also highly sensitive to the inputs used.

These can give unreliable results, since MVO maximizes the estimation errors of these inputs. Small input differences can lead to large output differences. This has led to MVO creating error maximizing portfolios.

Users of MVO often have to adjust the inputs, constrain them to reduce sampling error, or incorporate prior information to shrink the estimates back to values that are more reasonable. Return inputs are particularly unreliable, and some MVO users ignore them entirely by opting to use instead a minimum variance portfolio. DeMiguel, Garlappi, and Uppal showed that any gains from optimal diversification were more than offset by estimation errors.

MVO produces extreme weights that fluctuate substantially over time and performs poorly out of sample. However, researchers did not realize this during the early years of MVO. What they did realize is that computers had limited power back in the s, and MVO was computationally demanding. MVO could require matrix inversions involving covariances and returns of thousands of assets. A 1,asset portfolio, for example, would require , covariances. Therefore, in the early to mids, a number of academic researchers working independently developed a simplified alternative to MVO called the capital asset pricing model CAPM.

CAPM also tells you that the expected return on any security is proportional to the risk of that security as measured by its beta. The intercept of the regression equation is the alpha. It is what you have left over once you remove beta from the equation.

Alpha represents abnormal profits. It is what you earn in excess of the reward for assuming market risk.

Instead of having to deal with possibly thousands of inputs to construct optimal portfolios, with CAPM you only need information pertaining to your portfolio of stocks and the market index.

If you diversify among a number of stocks spread out in different industries, you could target the expected return and volatility you want for your portfolio by targeting the average beta of your stocks. Economists also liked the fact that statistical significance could be associated with alpha and beta in the form of t-statistics and probability values. Good point. It is very interesting and I believe it works but I know in the periods of underperformance I would be nervous and I would try to outwit the strategy and tinker it.

I would agree with that. But large drawdowns tend to occur in overpriced markets. If you value invest, the risk of large drawdowns decreases. Are you talking about using value for timing the market? It depends. The US stock market has a PE10 of Given the rules based nature of this approach and the requirement of ony three ETFs is there a dual momentum etf that will do all the work for a lazy investor;-0 That would eliminate the need for an individual investor to rebalance, which is especially difficult during market turmoil status quo bais, investors not willing to realize losses, etc.

Good question. As of right now there are no rule-based ETFs like this but I know of at least one or two that will be coming to market in the next few months. Instead of diversifying between US and international stocks, this relative momentum approach holds exclusively one or the other. The biggest single driver of the selection is U. Obviously, sustained currency trends will benefit the system, while currency whipsaws can cause it to underperform both stock indexes.

One can obtain similar numbers using small cap vs large cap or growth vs value relative momentum models. But these approaches inherently involve less-diversified sector overweights. The results are fairly impressive, although there of course have been false signals and whipsaw action there are well. I ran the numbers back to and found there were roughly 60 total trades in the system, so less than 1. The centroid of a month moving average is only 6. Empirical observations show that bonds perform better than average when stocks are on a sell signal, which often coincides with recession.

Big institutions are never going to engage in absolute momentum market timing. Among other things, trading cost escalates in proportion to share volume raised to the 1. Absolute momentum is one of the few edges that individual traders have over institutions. Good summary, thanks. Another reason that these rules should continue to work more oftern than not over time. My conclusion? Value investing works. Momentum investing works.

Trend following rules work. Index investing works. Diversified global asset allocation works. And all of them work much better […]. Ben, thanks for the introduction to this simple strategy. I also ran the numbers on the strategy and they are quite impressive even if you change the parameters of the underlying indices.

Regarding your caveats and drawbacks listed, I can see the advantage of using a simple GEM strategy as the tactical asset allocation piece in a portfolio. Again, thanks for the overview. Thanks Daniel. The former compares an investment against another investment. Whichever one […]. Thank you for this summary.

Can you tell whether Antonacci uses total returns or just price action in determining which investment to use? What do you think of a possible simplification of just comparing us vs international vs bond and investing in best performing? A Wealth of Common Sense is a blog that focuses on wealth management, investments, financial markets and investor psychology. More about me here.

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