Expected Returns
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Expected Returns

An Investor's Guide to Harvesting Market Rewards

Antti Ilmanen

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eBook - ePub

Expected Returns

An Investor's Guide to Harvesting Market Rewards

Antti Ilmanen

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About This Book

This comprehensive reference delivers a toolkit for harvesting market rewards from a wide range of investments. Written by a world-renowned industry expert, the reference discusses how to forecast returns under different parameters. Expected returns of major asset classes, investment strategies, and the effects of underlying risk factors such as growth, inflation, liquidity, and different risk perspectives, are also explained. Judging expected returns requires balancing historical returns with both theoretical considerations and current market conditions. Expected Returns provides extensive empirical evidence, surveys of risk-based and behavioral theories, and practical insights.

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Information

Publisher
Wiley
Year
2011
ISBN
9781119990772
Part I
Overview, historical returns, and academic theories
1. Introduction
2. Whetting the appetite: Historical averages and forward-looking returns
3. The historical record: The past 20 years in a longer perspective
4. Road map to terminology
5. Rational theories on expected return determination
6. Behavioral finance
7. Alternative interpretations for return predictability
1
Introduction
ā€¢ This book covers the general topic of expected returns on investments. The traditional paradigm among institutional investors focuses too much on historical performance and too narrowly on asset class allocation. This book argues that investment decision making should be broadened beyond the asset class perspective and a wider set of inputs should be used for assessing expected returns.
ā€¢ The book considers in detail a wide range of return sources: major asset classes (stocks, bonds, and alternative investments) and strategy styles (value, carry, momentum, and so forth) as well as risk factors (such as growth, inflation, and liquidity).
ā€¢ The main inputsā€”beyond discretionary viewsā€”for investors to judge expected returns are (1) historical performance, (2) theories, and (3) forward-looking indicators. A better understanding of these inputs and a better balance among them is needed.
ā€¢ Well-known evidence of historical asset returns include the significant long-run outperformance of stocks over bonds (less so in the 19th and 21st century than in the 20th century) as well as more moderate rewards for bearing interest rate risk and credit risk.
ā€¢ Less familiar historical findings include the pervasive success of value, carry, and momentum strategy styles in several markets as well as the tenuous relation between volatility and average returns. This book highlights the low long-run returns of the most volatile assets within each asset class, a finding that may reflect risk-seeking (ā€œlottery-playing)ā€ behavior by investors, or that may be explained by leverage constraints.
ā€¢ Finance theories have changed dramatically over the past 30 years, away from the restrictive theories of the single-factor CAPM, efficient markets, and constant expected returns. Current academic views are more diverse, less tidy, and more realistic. Expected returns are now commonly seen as driven by multiple factors. Some determinants are rational (risk and liquidity premia), others irrational (psychological biases such as extrapolation and overconfidence). Expected returns on all factors may vary over time.
ā€¢ A central insight from academic finance theories is that required asset returns have little to do with an assetā€™s standalone volatility and more to do with when losses can be expected to occur. Investors should require high-risk premia for assets that fare poorly in bad times, whereas safe haven assets (that fare well in bad times and less well in good times) can justify low or even negative risk premia. Strategies that resemble selling financial catastrophe insuranceā€”steady small gains punctuated by infrequent but large lossesā€”warrant especially high risk premia because their losses are so highly concentrated in the worst times.
ā€¢ Forward-looking indicators such as valuation ratios have a better track record in forecasting future asset class returns than rearview mirror measures. The practice of using historical average returns as best estimates of future returns is dangerous when expected returns vary over time. Recall stock markets in 1999ā€“2000.
ā€¢ Long-run expected returns for any investment tend to be especially high following adverse events. For example, equity markets tend to have predictably higher returns after recessions, and nominal bonds after high inflations.
ā€¢ Investors can try to boost expected returns by taking risks that produce attractive rewards for all market participants (beta risks) and/or by skillful active management (alpha) which may involve exploiting regularities and market inefficiencies. This book offers a comprehensive guide for smart harvesting of beta risk premia, covering both long-run exposures to traditional and alternative betas as well as tactical beta timing. However, I concede from the outset that the magic of view-based alpha generation cannot be conveyed in a book.
ā€¢ Two visual aidsā€”an elephant and a cubeā€”help the reader keep ā€œthe big pictureā€ in mind through the book.
ā€¢ Although I present large amounts of empirical evidence about historical returns and forward-looking indicators, as well as numerous theories in an attempt to make sense of the data, I believe it is important to stress humility. Hindsight bias makes us forget how difficult forecasting is, especially in highly competitive financial markets. Expected returns are unobservable and our understanding of them is limited. Even the best expertsā€™ forecasts are noisy estimates of prospective returns.
It was six men of Hindostan,
To learning much inclined,
Who went to see the elephant
(Though all of them were blind);
That each by observation
Might satisfy his mind.
ā€”J.G. Saxe (to be continued)

The traumatic housing and credit crisis that began in 2007 challenged many beliefs about investing and financial markets. The aftershocks of the crisis are still felt in many markets and economies (not least in public finances), but it is no longer necessary or advisable to view the future solely through the prism of this crisis. Instead, this book surveys the landscape of expected returns and long-term investment prospects based on lessons learned over decades.
The traditional paradigm of institutional investing focuses on relatively static asset class allocations that are largely determined by historical performance. We must go back to basics and broaden the traditional paradigm in two ways. The inputs used for assessing expected returns should be better balanced and the idea of what constitutes investments should be challenged beyond the asset class perspective.
Figure 1.1. The elephant: Shining light on expected returns from different directions.
002
The foremost need for multi-dimensional thinking is on inputs. When investors make judgments about the expected returns of various investments, they should guard against being blinded by past performance and must ensure that they take all or most of the following considerations into account:
ā€¢ historical average returns;
ā€¢ financial and behavioral theories;
ā€¢ forward-looking market indicators such as bond yields; and
ā€¢ discretionary views.
Figure 1.1 recalls the parable about several blind men and an elephant, as told by the American poet John Godfrey Saxe (1816ā€“1887), each man describing one part of the elephant from his narrow vantage point. One man is feeling the leg and calling it a tree, another touching the ear and naming it a fan, a third mistaking the tail for a rope, and so on. Each man misses the big pictureā€”and so will investors who study expected returns from a single vantage point.
The first approached the elephant,
And happening to fall
Against his broad and sturdy side,
At once began to bawl,
ā€œBless me, it seems the elephant
Is very like a wall.ā€
So the challenge is to refine the art of investment decision making in a way that exploits all our knowledge about historical experience, theories, and current market conditions, without being overly dependent on any one of these. This book will summarize the state of knowledge on all these aspects, but it focuses on the first three inputs since these are systematic. I have less to say about discretionary views since these are inherently investor specific. However, the approaches described in this book will help readers form such views. Stated differently, investing involves both art and science; a solid background in the science can improve the artist.
Figure 1.2. The cube: Three perspectives on investments and their expected returns.
003
Before turning to these inputs, I address the reasonable question ā€œExpected returns on what?ā€ The traditional paradigm has been to break the complex world of investments into simplified groupings called asset classes. Analyzing, and allocating to, asset classes has been the dominant approach but I argue that studying investments from perspectives other than asset classes can enhance our understanding of return sources and our ability to diversify effectively. This book will add to the asset class perspective the complementary viewpoints of strategy styles and risk factors, as in the three-dimensional ā€œcubeā€ in Figure 1.2:
ā€¢ Starting with the asset class perspective, I will cover all traditional asset classes (equities, government bonds, credits) plus many alternative ones (including real estate, commodities, hedge funds, and private equity). I focus on long-run returns but also review tactical market-timing approaches. A broader mindset naturally leads to questioning the traditional 60/40 portfolio which relies excessively on one source of excess returns (the equity premium) and which therefore has highly concentrated risk (more than 90% of portfolio volatility is due to equities).
ā€¢ The strategy style perspective is especially important for understanding the profit potential of popular active-trading approaches. Value, carry, momentum, and volatility styles have outperformed buy-and-hold investments in many asset classes. Styles can also offer better diversification opportunities than asset classes.
ā€¢ Sophisticated investors are increasingly trying to look beyond asset classes and strategies in order to identify the underlying factors driving their portfolio returns. A factor-based approach is also useful for thinking about the primary function of each asset class in a portfolio (stocks for harvesting growth-related premia, certain alternatives for illiquidity premia, Treasuries for deflation hedging, and so on) as well as for diversifying across economic scenarios. Among underlying risk factors, I opt to focus on growth, inflation, illiquidity, and tail risks (volatility, correlation, return asymmetries).
The second, feeling of his tusk,
Cried, ā€œHo! What have we here
So very round and smooth and sharp?
To me, ā€™tis mighty clear
This wonder of an elephant
Is very like a spear.ā€
How can investors deal with the complexity of multiple inputs and perspectives, let alone with the even more bewildering assortment of novel investment products on offer? This book provides a map to investors, giving a birdā€™s eye view over a rugged terrain and occasionally zooming in to interesting locations (12 case studies), not unlike Google Earthā„¢. I hope my two visual aidsā€”the elephant and the cubeā€”will help readers keep the forest in sight among the many trees along the way.
Next, Sections 1.1ā€“1.4 give an overview on the four perspectives on ā€œfeeling the elephantā€ (i.e., on considerations for judging expected returns). These themes will be expanded on through the book.

1.1 HISTORICAL PERFORMANCE

Historical average returns are a common starting point for judging expected returns. The idea is that if expected returns are constant over time, long-run average realized return is a good estimate of expected future return. Unexpected news dominates returns in the short run but the effects of such news tend to cancel out in the long run.
Why should you think twice before using historical returns as forecasts of future returns?
ā€¢ Any sample period may be biasedā€”in the sense of not being representative of market expectationsā€”so that unexpected returns do not neatly cancel out, especially if the sample starts or ends at times of exceptionally high or low market valuations. Windfall capital gains during a benign sample can boost average returns meaningfully even over multiple decades. Bond indices are a prime example, given the downtrend in bond yields since the 1970s and 1980s when a number of the widely used bond index histories start.
ā€¢ In principle, longer historical windows reduce sample specificity and enable more accurate estimates of average returns. However, distant historical data may be irrelevant due to structural changes, apart from lower data quality. Would we really want to include data from the 1600s even if good-quality returns were available to us?
ā€¢ Expected returns may vary over time in a cyclical fashion, which makes extrapolation of multi-year performance particularly dangerous. Periods of high realized returns and rising asset valuationsā€”think stock markets in the 1990sā€”are often associated with falling forward-looking returns.
ā€¢ For specific funds and strategies, the historical performance data that investors get to see are often upward biased. This bias is due to the voluntary nature of performance reporting and survivorship bias (so that poor performers are left out of databases or are not marketed by the fund manager). A similar caveat applies to simulated ā€œpaperā€ portfolios because backtests may be overfitted and trading costs ignored or understated.
These concerns notwithstanding, this book presents extensive evidence of long-run realized returns, when possible covering 50-to-100-year histories. Several main findings are familiar to most readers:
ā€¢ Stock markets have outperformed fixed income markets during the past century in all countries studied. The compound average real return for global equities between 1900 and 2009 is 5.4%, which is 3.7% (4.4%) higher than that of long-term government bonds (short-dated Treasury bills). Stocksā€™ outperformance over bonds is 0.5% to 0.8% higher for the U.S. than globally and was even more pronounced before the negative returns in 2000s. The experience of the current investor generation has buried the myth that stocks always beat bonds over 20-year or 30-year horizons. (This myth was never true. Many exceptions to it occurred outside the U.S. in the 20th century and inside the U.S. during the 19th century.)
ā€¢ Among fixed income markets, long-term bonds have outperformed short-dated bonds by 0.5% to 1% and credit-risky corporate bonds have outperformed comparable government bonds by 0.3% to 1% (low end for investment-grade bonds, high end for h...

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