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Table of Contents
Title Page
Copyright Page
Foreword
Dedication
Acknowledgments
Abbreviations and acronyms
Disclaimer
Part I - Overview, historical returns, and academic theories
Chapter 1 - Introduction
1.1 HISTORICAL PERFORMANCE
1.2 FINANCIAL AND BEHAVIORAL THEORIES: A BRIEF HISTORY OF IDEAS
1.3 FORWARD-LOOKING INDICATORS
1.4 VIEW-BASED EXPECTED RETURNS
1.5 GENERAL COMMENTS ABOUT THE BOOK
1.6 NOTES
Chapter 2 - Whetting the appetite: Historical averages and forward-looking returns
2.1 HISTORICAL PERFORMANCE SINCE 1990
2.2 SAMPLE-SPECIFIC RESULTS: DEALING WITH THE PITFALLS
2.3 FORWARD-LOOKING RETURN INDICATORS
2.4 NOTES
Chapter 3 - The historical record: The past 20 years in a longer perspective
3.1 STOCKS
3.2 BONDS
3.3 REAL ASSET INVESTING AND ACTIVE INVESTING
3.4 FX AND MONEY MARKETS
3.5 REAL RETURN HISTORIES
3.6 NOTES
Chapter 4 - Road map to terminology
4.1 CONSTANT OR TIME-VARYING EXPECTED RETURNS?
4.2 RATIONAL OR IRRATIONAL EXPECTATIONS FORMATION?
4.3 RETURN MEASUREMENT ISSUES
4.4. RETURNS IN WHAT CURRENCY?
4.5 RISK-ADJUSTED RETURNS
4.6 BIASED RETURNS
4.7 NOTES
Chapter 5 - Rational theories on expected return determination
5.1 THE OLD WORLD
5.2 THE NEW WORLD
5.3 DETOUR: A BRIEF SURVEY OF THE EFFICIENT MARKETS HYPOTHESIS
5.4 NOTES
Chapter 6 - Behavioral finance
6.1 LIMITS TO ARBITRAGE
6.2 PSYCHOLOGY
6.3 APPLICATIONS
6.4 CONCLUSION
6.5 NOTES
Chapter 7 - Alternative interpretations for return predictability
7.1 RISK PREMIA OR MARKET INEFFICIENCY
7.2 DATA MINING AND OTHER “MIRAGE” EXPLANATIONS
7.3 NOTES
Chapter 8 - Equity risk premium
8.1 INTRODUCTION AND TERMINOLOGY
8.2 THEORIES AND THE EQUITY PREMIUM PUZZLE
8.3 HISTORICAL EQUITY PREMIUM
8.4 FORWARD-LOOKING (EX ANTE OBJECTIVE) LONG-TERM EXPECTED RETURN MEASURES
8.5 SURVEY-BASED SUBJECTIVE EXPECTATIONS
8.6 TACTICAL FORECASTING FOR MARKET TIMING
8.7 NOTES
Chapter 9 - Bond risk premium
9.1 INTRODUCTION, TERMINOLOGY, AND THEORIES
9.2 HISTORICAL AVERAGE RETURNS
9.3 ALTERNATIVE EX ANTE MEASURES OF THE BRP
9.4 YIELD CURVE STEEPNESS: IMPORTANT PREDICTIVE RELATIONS
9.5 EXPLAINING BRP BEHAVIOR: FIRST TARGETS, THEN FOUR DRIVERS
9.6 TACTICAL FORECASTING—DURATION TIMING
9.7 NOTES
Chapter 10 - Credit risk premium
10.1 INTRODUCTION, TERMINOLOGY, AND THEORY
10.2 HISTORICAL AVERAGE EXCESS RETURNS
10.3 FOCUS ON FRONT-END TRADING—A POCKET OF ATTRACTIVE REWARD TO RISK
10.4 UNDERSTANDING CREDIT SPREADS AND THEIR DRIVERS
10.5 TACTICAL FORECASTING OF CORPORATE BOND OUTPERFORMANCE
10.6 ASSESSING OTHER NON-GOVERNMENT DEBT
10.7 CONCLUDING REMARKS
10.8 NOTES
Chapter 11 - Alternative asset premia
11.1 INTRODUCTION TO ALTERNATIVES
11.2 REAL ESTATE
11.3 COMMODITIES
11.4 HEDGE FUNDS
11.5 PRIVATE EQUITY FUNDS
11.6 NOTES
Chapter 12 - Value-oriented equity selection
12.1 INTRODUCTION TO DYNAMIC STRATEGIES
12.2 EQUITY VALUE: INTRODUCTION AND HISTORICAL PERFORMANCE
12.3 TWEAKS INCLUDING STYLE TIMING
12.4 THE REASONS VALUE WORKS
12.5 DOES THE VALUE STRATEGY WORK IN EQUITIES BEYOND INDIVIDUAL STOCK SELECTION ...
12.6 RELATIONS BETWEEN VALUE AND OTHER INDICATORS FOR EQUITY SELECTION
12.7 NOTES
Chapter 13 - Currency carry
13.1 INTRODUCTION
13.2 HISTORICAL AVERAGE RETURNS
13.3 IMPROVEMENTS/REFINEMENTS TO THE BASELINE CARRY STRATEGY
13.4 WHY DO CARRY STRATEGIES WORK?
13.5 CARRY HERE, CARRY THERE, CARRY EVERYWHERE
13.6 NOTES
Chapter 14 - Commodity momentum and trend following
14.1 INTRODUCTION
14.2 PERFORMANCE OF SIMPLE COMMODITY MOMENTUM STRATEGIES
14.3 TWEAKS
14.4 WHY DOES MOMENTUM—SUCH A NAIVE STRATEGY—WORK?
14.5 MOMENTUM IN OTHER ASSET CLASSES
14.6 NOTES
Chapter 15 - Volatility selling (on equity indices)
15.1 INTRODUCTION
15.2 HISTORICAL PERFORMANCE OF VOLATILITY-TRADING STRATEGIES
15.3 TWEAKS/REFINEMENTS
15.4 THE REASONS VOLATILITY SELLING IS PROFITABLE
15.5 OTHER ASSETS
15.6 NOTES
Chapter 16 - Growth factor and growth premium
16.1 INTRODUCTION TO UNDERLYING FACTORS IN CHAPTERS 16–19
16.2 INTRODUCTION TO THE GROWTH FACTOR
16.3 THEORY AND EVIDENCE ON GROWTH
16.4 ASSET MARKET RELATIONS
16.5 TIME-VARYING GROWTH PREMIUM
16.6 NOTES
Chapter 17 - Inflation factor and inflation premium
17.1 INTRODUCTION
17.2 INFLATION PROCESS—HISTORY, DETERMINANTS, EXPECTATIONS
17.3 INFLATION SENSITIVITY OF MAJOR ASSET CLASSES AND THE INFLATION PREMIUM
17.4 TIME-VARYING INFLATION PREMIUM
17.5 NOTES
Chapter 18 - Liquidity factor and illiquidity premium
18.1 INTRODUCTION
18.2 FACTOR HISTORY: HOW DOES LIQUIDITY ITSELF VARY OVER TIME?
18.3 HISTORICAL EVIDENCE ON AVERAGE LIQUIDITY-RELATED PREMIA
18.4 TIME-VARYING ILLIQUIDITY PREMIA
18.5 NOTE
Chapter 19 - Tail risks (volatility, correlation, skewness)
19.1 INTRODUCTION
19.2 FACTOR HISTORY
19.3 HISTORICAL EVIDENCE ON AVERAGE ASSET RETURNS VS. VOLATILITY AND CORRELATION
19.4 THEORY AND EVIDENCE ON THE SKEWNESS PREMIUM
19.5 VERDICT ON WHY HIGH-VOLATILITY ASSETS FARE SO POORLY
19.6 TIME-VARYING PREMIA FOR TAIL RISK EXPOSURES
19.7 NOTES
Part III - Back to broader themes
Chapter 20 - Endogenous return and risk: Feedback effects on expected returns
20.1 FEEDBACK LOOPS ON THE DIRECTION OF RISKY ASSETS
20.2 FEEDBACK LOOPS ON LESS DIRECTIONAL POSITIONS
20.3 AGENDA FOR MARKET-TIMERS AND RESEARCHERS
20.4 NOTES
Chapter 21 - Forward-looking measures of asset returns
21.1 POPULAR VALUE AND CARRY INDICATORS AND THEIR PITFALLS
21.2 BUILDING BLOCKS OF EXPECTED RETURNS
21.3 NOTES
Chapter 22 - Interpreting carry or non-zero yield spreads
22.1 INTRODUCTION
22.2 FUTURE EXCESS RETURNS OR MARKET EXPECTATIONS?
22.3 EMPIRICAL HORSE RACES FOR VARIOUS ASSETS
22.4 CONCLUSIONS
22.5 NOTES
Chapter 23 - Survey-based subjective expected returns
23.1 NOTES
Chapter 24 - Tactical return forecasting models
24.1 INTRODUCTION
24.2 WHAT TYPE OF MODEL?
24.3 WHICH ASSETS/TRADES?
24.4 WHICH INDICATOR TYPES?
24.5 ENHANCEMENTS AND PITFALLS
24.6 NOTES
Chapter 25 - Seasonal regularities
25.1 SEASONAL, CYCLICAL, AND SECULAR PATTERNS IN ASSET RETURNS
25.2 MONTHLY SEASONALS AND THE JANUARY EFFECT
25.3 OTHER SEASONALS
Chapter 26 - Cyclical variation in asset returns
26.1 TYPICAL BEHAVIOR OF REALIZED RETURNS AND EX ANTE INDICATORS THROUGH THE ...
26.2 TYPICAL BEHAVIOR OF REALIZED RETURNS AND EX ANTE INDICATORS ACROSS ...
26.3 NOTES
Chapter 27 - Secular trends and the next 20 years
27.1 CONTRASTING 1988–2007 WITH 1968–1987
27.2 REVERSIBLE AND SUSTAINABLE SECULAR TRENDS
27.3 THE NEXT 20 YEARS
27.4 NOTES
Chapter 28 - Enhancing returns through managing risks, horizon, skill, and costs
28.1 INTRODUCTION: HOW CAN INVESTORS ENHANCE RETURNS?
28.2 RISK
28.3 INVESTMENT HORIZON
28.4 SKILL
28.5 COSTS
28.6 NOTES
Chapter 29 - Takeaways for long-horizon investors
29.1 KEY TAKEAWAYS FROM THEORY
29.2 EMPIRICAL RETURN SOURCES
29.3 MY TAKE ON KEY DEBATES
29.4 KNOW THYSELF: LARGE LONG-HORIZON INVESTORS’ NATURAL EDGES
29.5 INSTITUTIONAL PRACTICES
29.6 NOTES
Appendix A - World wealth
Appendix B - Data sources and data-series construction
Bibliography
Index
For other titles in the Wiley Finance Series please see www.wiley.com/finance
This edition first published 2011 © 2011 Antti Ilmanen
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ISBN 978-1-119-99072-7
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Foreword
The first time I met Antti Ilmanen I thought he was insane. I was right. But, I was to discover quickly he was insane in a good way. The incident in question was at a new Ph.D. student mixer, about as exciting as it sounds, where seconds after being introduced to Antti he asked me “who do you rate in the top-five academics in finance and why?” He had his own answers on a set of Post-it notes. By the way, Antti has become famous for these Post-it notes. Suffice it to say if he consults the Post-its, and says you said something 17 years ago that turned out to be disproved in the latest Journal of Finance paper, just assume he’s right and move on.
Getting back to my story, he couldn’t understand how I couldn’t name five. Truth be told I probably could have named maybe three academics in total, and as to justifying my choices with “why?”, I was stuck at zero. I had not chosen finance because, like Antti, I was already obsessed with it. I chose it as my dad, a lawyer, forbade me to go to law school, I had some mild ability at mathematics, I recognized that finance might be both intellectually interesting and provide a good living, and finally I chose a Ph.D. as being a professor seemed like a nice life (little did I know the Sirens of Wall Street would soon call me away . . .) Antti looked at me with a “what the heck are you doing in the Ph.D. program” confused stare, and I politely ran away from the very intense, very finance-obsessed young Finn. Now, 20+ years later, and after countless similar incidents, I no longer run away (he finds me anyway), but he’s still intense and obsessed with finance. Over the years, and specifically through this book, those traits of his have made us all better off.
One more aside before my foreword begins in earnest. I briefly considered not writing this foreword in protest or as a rearguard action. Antti gives away a lot in this book. Perhaps few true secrets (though there are some!), as this is more a textbook than original research. But he makes much of what has become called “quantitative finance” easily (OK, 300+ dense pages, in original format, of “easily”) accessible in one place. Long term, that can’t be good for people like me who make their livings from this stuff being at least a bit secret. But being skilled at game theory I quickly determined that if I didn’t write the foreword somebody else would, so refusal would not accomplish much. With that strategy shot down, I very fleetingly considered having him killed, but this seemed to entail too much “tail risk” (see Chapters 15 and 19) and, anyway, is at least somewhat morally ambiguous. Besides, Antti’s just the type to have stashed a Post-it at his lawyer with a note “in the event of my untimely . . .” So in the end I decided to smile and write the foreword, and just resolve to work harder (along with many others at my firm and others throughout the field) to give Antti material for a sequel 20+ years from now!
Now let’s talk about the title subject.
Expected returns are how much you make on average over time on an investment or strategy. Risk is the possibility that, over any time horizon, you never get your expectation, as once again the world interferes with a perfectly good plan. Risk can make you fail to reach your expectations because of the simple uncertainty around expectations it brings, or because, as in 2008 for many, bad realizations call into question long-term survival or at least the ability to stick with a plan. Still, expected returns are incredibly important. If you survive and stick to a good plan, they add up nicely.
Antti has chosen to write a book on expected return in the Age of Risk. Risk, and particularly risk in the sense of survival, is all the rage in these days following a major financial crisis. This wide-ranging discussion of risk is right and proper. If some investors took too much risk and that caused or exacerbated the financial crisis, that’s a pretty important event to learn from. If some investors thought risk was simple and all figured out, and got a black swan dropped on their heads, it is important to learn from that too. However, it’s not the whole story.
While perhaps differing from the vast majority of risk-focused researchers and authors these days, I’d argue that the study of expected returns deserves more of our attention, even just after one of the biggest “left tails” in history. For one thing, as scary as the world got, some of our much maligned simple “normal” models actually did OK for all assets other than highly structured and/or levered ones, or over the very short term (see http://www.dimensional.com/famafrench/2009/05/how-unusual-wasthe-stock-market-of-2008.html). For another thing, in a theme Antti returns to again and again in his book, expected returns don’t have to stay the same throughout time. Part of what we see as “risk” materializing during events like the 2008 financial crisis, and the 1999–2000 tech bubble, are more accurately seen as investors misunderstanding or misestimating expected returns. In both those cases the extreme dénouement that followed occurred, at least according to many (and me), because before the disaster, investors were willing to accept far too low an expected return, first on stocks and specifically on technology stocks, and then a decade later on credit and real estate. In both the theory and the reality of these globe-shaking events, the discussions of risk and expected return are intimately linked.
So why so much more discussion of risk than expected return these days? Well, obviously the magnitude of recent events makes all of us greatly value the chance we could have avoided that pain. But again, a careful study of expected return might have easily, perhaps even more easily, led to the same protection by avoiding certain investments on the ground that their expected returns were too low. Frankly, I think a lot of the answer is that discussing risk is inherently sexier than discussing expected returns. Good forecasts of expected return add up over the long term, but don’t matter for squat next week. Risk can kill you, or make you a hero, in the time it takes you to say “flash crash”. Would you rather write about a tsunami or erosion? More specifically, from a safe perch, say the hindsight of authoring a book, which event would be more dramatic to narrate? The analogy, forced though it may be, continues to work as erosion, or expected return, might be mind-numbingly boring at any one moment, but it has a heck of a lot to say about how the future will be shaped.
For perspective, you want to see a black swan? Try making nothing on your equities in your final 20 years until retirement because you bought them at an extremely high price (low expected return). That is one pile of ebony long-necked bird. If risk is about surviving the short term, expected return is about whether, after surviving, you think it was worth it.
Here’s another secret. Besides being at least as important, estimating expected returns is much harder than estimating risk. Now, estimating risk is no easy task. But at least finance wears its insecurity on its sleeve here. Are returns “normal” or do we have to worry about “black swans”, “fat tails”, and all that? This worry and effort is worthwhile, but those trying to estimate the expected return on various assets smile at those taking on the comparatively easy task of estimating risk. Basically, you need a heck of a lot more data to estimate expected returns than to estimate risk. In geek-speak, the first moment laughs at and taunts the second moment (which I’m going to pretend for a second is all you need for risk). The second moment gives up its secrets reluctantly, but far more readily than that more covert first moment. To estimate risk we lament (as statisticians not humanitarians) that we don’t get to see a few more disasters. To estimate expected return we lament we don’t get to see a few more centuries.
Now that the motivation behind and the difficulty of Antti’s task is clear, let’s talk about how one might actually try to forecast expected returns. Starting with the very big picture, why is there a positive expected return (let’s make that positive relative to some riskless rate or, in other words, a positive risk premium) on any asset or investment strategy? Well, there are two possible reasons. First, in a rational world you should get paid a positive expected return for bearing a risk others don’t wish to bear. As an aside, Antti repeatedly hammers home the poorly understood point that you should get paid particularly well for bearing risks that hurt you exactly when it is most painful to be hurt, and less or not at all for risks that only bring you harm when all is well. Second, in a world that permits some irrationality, you can also get paid for someone else’s systematic mistakes (or pay for your own).
While this parsing is useful, and Antti makes great use of it throughout the book, he takes it further, examining expected returns along three different dimensions (and asking the rational vs. irrational question for each part):
1. The expected return you get paid for owning any of the major asset classes (stocks, bonds, commodities, etc.).
2. The expected return you get from pursuing well-known strategies such as value investing, momentum investing, and carry-based investing. These are fundamentally different from the returns in (1) as, for instance, in examining value investing you don’t count the expected return from just being long stocks, but rather the extra return that has historically accrued to value stocks vs. the universe of all stocks. These strategies also tend to be far more dynamic than the asset classes in (1), changing their portfolio holdings more often through time.
3. The expected return you get from being willing to take the risk of being exposed to economic or other risks (e.g., shocks to growth, shocks to inflation, liquidity risk, etc.).
These are all connected and overlapping. For instance, passive ownership of equities exposes you more to risk of poor real economic growth than does passive ownership of bonds, which exposes you more to risk of higher-than-expected inflation. Small stocks expose you to more liquidity risk than large ones. The overlapping descriptions go on and on. Antti doesn’t mean for these three ways to look at expected returns to be a clean decomposition, rather he finds use for all three at once (remember, he calls this art and science). He continually stresses that there is no perfect way to examine (or later forecast) expected returns. You want to use every framework that is useful and brings anything new to the study. In this sense his three-way examination succeeds handily.
OK, let’s recap. So there are two ways you can get a positive expected return, by taking a risk you get paid for (roughly, “beta”), or by outsmarting someone else (“alpha”). There are three useful perspectives to examine the source of expected returns: asset classes, systematic strategies, and risk factors such as economic growth and liquidity. Exposure to any of these three can generate a positive return for either of the first two reasons (rational compensation for risk, or outsmarting of others who are less than rational). Now we’re cooking. All we need now—assuming we have identified one or more of the three categories of sources of expected returns (from the overlapping categories of asset class, strategy, and risk factor exposure) and have a theory as to why an investor gets paid this expected return (rational vs. irrational)—is a way to estimate the size of that expected return going forward. Here, you guessed it, Antti gives us not one but three very useful methods. They are again complementary—not competitors. In order from weakest to strongest (Antti’s ordering which I agree with): (1) you can forecast the future from looking purely at how something has done in the past, (2) you can forecast the future based solely on your theory of how the world should work without examining data, (3) you can jump straight to current measures (e.g., the P/E of the stock market, the nominal or real yield on bonds) and use them to forecast. Like Antti, for reasons you’ll have to get from the book, I favor (3), but even using current measures like P/E and yield you still need history and theory. You would like some theory to guide why you think today’s stock market P/E should be related to its future return, and probably would like some evidence that this has historically been an effective tool.
So, remember, there are two reasons you might get paid an expected return, three overlapping ways to parse the different sources of expected returns, and three non-mutually exclusive methods to estimate the expected return going forward, all probably containing part but not all the truth, so all must be strongly considered, but none blindly, and all at once. You got that?
Well, I didn’t promise you this would be simple, did I? In fact, I told you the opposite. Expected returns are interesting precisely because they are hard (and very important)! This means there is no easy answer. But, it also means that effort on this front is potentially highly valuable. Understanding easy but very important problems is also important, but the barriers to entry are low, and getting an advantage from such an easy understanding is usually difficult because the understanding is so widespread. (On the other hand, the investing public’s continued failure to understand basic ideas like diversifying widely, keeping average costs low, and realizing that it is hard to beat the market, etc., makes even this effort worthwhile to the marginal investor.) But, understanding deeply, if imperfectly, what many don’t understand at all or even get backwards (like the common error of thinking expected returns are especially high going forward after realized returns have had an exceptionally good run), well, that is great stuff!
Antti’s book is complicated and dense. The best compliment I can pay it is that it’s not more complicated than it has to be. It chooses to take on a hard question and is honest about this degree of difficulty. It chooses to offer multiple overlapping methods at each point, as there truly is not one certain method, and each brings some value. Another, far weaker, even harmful, book could tell you that forecasting long-term future returns is easy. That all you have to do is listen to the author’s simple formula and prosper (Dow 36,000 anyone?). Antti tells you it’s hard. He says if you follow our best minds, and use the best data we have, you probably have an edge, or at least your mistakes are not silly, but he says it is art and science, and makes no guarantees.
If I can leave you with advice that applies directly to Antti’s book, but is actually far more general, it’s to listen to people who take on difficult problems boldly. Listen to people who are honest that our best hope is improved but not perfect understanding. Listen to people who aren’t afraid to tell you the world is a complicated place, but then are damned talented at making it as simple as possible (but no simpler).
In other words, read this book. Listen to Antti.
Clifford S. Asness AQR Capital Management LLC
The information set forth herein has been obtained or derived from sources believed by the author to be reliable. However, the author does not make any representation or warranty, express or implied, as to the information’s accuracy or completeness, nor does the author recommend that the attached information serve as the basis of any investment decision. This document has been provided to you solely for information purposes and does not constitute an offer or solicitation of an offer, or any advice or recommendation, to purchase any securities or other financial instruments, and may not be construed as such. This document is intended exclusively for the use of the person to whom it has been delivered by the author, and it is not to be reproduced or redistributed to any other person.
Dedicated to Rory Byrne, in memoriam