Financial Markets and Investor Behavior Evidence File

Jan19: Financial Markets and Investor Behavior: Indicators and Surprises
Why Is This Information Valuable?
A number of new papers have shed more light on the genetic roots of risk tolerance and risky behaviors
SURPRISE
To the extent that they are genetically based (as opposed to learned or situationally based), differences in risk tolerance are likely to be impervious to attempts to modify them (e.g., through education). This suggests that financial advisors (and regulators) should instead focus on ways to compensate for them.

In “Genome-Wide Association Analyses of Risk Tolerance and Risky Behaviors in Over 1 Million Individuals Identify Hundreds of Loci and Shared Genetic Influences”, by Auton et al, the authors “find evidence of substantial shared genetic influences across general risk tolerance and risky behaviors in the driving, drinking, smoking, and sexual domains.”

Other research has found that impulsivity and risk tolerance are actually separate concept with different genetic and neurochemical roots (e.g., see, “Risk Taking and Impulsive Behaviour: Fundamental Discoveries, Theoretical Perspectives and Clinical Implications” by Isles et al).

In “Relationships Among Impulsive, Addictive and Sexual Tendencies and Behaviours: A Systematic Review of Experimental and Prospective Studies in Humans”, Leeman et al find that “generalized, self-reported impulsivity is a predictor of addictive and sexual behaviours at a wide range of severity.” Separate research has found that impulsive behavior also has a strong genetic component (e.g., see “Genetics of Impulsive Behavior” by Bevilacqua and Goldman).

In “Three Gaps and What They Mean for Risk Preference”, Hertwig et al note that risk tolerance measures based on self-reported preferences are more stable over time than those based on observed behaviors.” In our experience, this reflects the significant role that situational factors play in many decisions taken in the fact of risk, uncertainty, and ignorance.
The end of 2018 also saw the publication of a number of articles describing the increasing challenge to active management posed by algorithms.
The FT’s Robin Wigglesworth noted “a flurry of finger-pointing by humbled one-time masters of the universe, who argue that the swelling influence of computer-powered quantitative, or quant, investors and high-frequency traders is wreaking havoc on markets and rendering obsolete old-fashioned analysis and common sense” (“Volatility: how ‘algos’ changed the rhythm of the market”, FT 8Jan19).

A recent research paper highlighted the increasing efficiency that appears to have resulted from the deployment of algorithmic strategies in some markets. In their study of the forward exchange rate market between 1994 and 2016, Levich et al “find widespread evidence of excess-predictability, hence currency market inefficiency, in the early part of the sample period and then at specific times, such as the recent global financial crisis. In the more recent part of the sample period, the evidence of excess-predictability [i.e., inefficiency] is largely limited to emerging market currencies” (“Measuring Excess-Predictability of Asset Returns and Market Efficiency over Time”).

However, another paper found that systematic/algorithmic strategies do not yet deliver superior performance in more complex environments, such as global macro funds (see, “Systematic and Discretionary Hedge Funds: Classification and Performance Comparison” by Chuang and Kuan).

Another recent research paper highlighted the human biases that some algorithmic strategies seek to exploit: “Most research on heuristics and biases in financial decision-making has focused on non-experts, such as retail investors who hold modest portfolios. We use a unique data set to show that financial market experts (institutional investors with portfolios averaging $573 million) exhibit costly, systematic biases.

“A striking finding emerges: while investors display clear skill in buying, their selling decisions underperform substantially in terms of both benchmark-adjusted and risk-adjusted returns. We present evidence consistent with limited attention as a key driver of this discrepancy, with investors de-voting more attentional resources to buy decisions than sell decisions” (“Selling Fast and Buying Slow: Heuristics and Trading Performance of Institutional Investors” by Klakow Akepanidtaworn et al).
Along with many others, we mourn the passing of Jack Bogle, who encouraged us when we launched The Index Investor back in 1997.
In all the coverage of his accomplishments, a key issue, that we know bothered Bogle deeply, has received far too little attention: the difference between index investing and passive investment.

Bogle was suspicious of exchange traded funds from the moment they were launched, fearing that over time they would grow in number, be based on ever narrower indexes, and encourage investors to frequently trade. In short, he feared that ETFs would become the antithesis of long term passive investing in a diversified portfolio of mutual funds that are based on broad asset class indexes. His fears were sadly prescient.

For example, a recent article (“Index Funds Are King, But Some Indexers Are Passive-Aggressive”, by Peter Coy on Bloomberg, 24Jan19), and a recent academic paper (“The Active World of Passive Investing”, by Easley et al) both note that the majority of ETF products amount to lower cost active strategies based on indexes that track a wide range of sectors, regions, styles, factors, and investment themes. Picking narrowly defined index products instead of individual stocks or bonds or commodities does not make one a passive investor.

To be sure, there will always be an active part of investing, whether at the level of investment policy formulation (e.g., how much to save, when to retire, target bequests, etc.), asset class definition, portfolio construction, product selection and timing to implement portfolio strategy, and/or policy and portfolio risk management decisions.

However, for more than 20 years we have strongly supported Jack Bogle’s view that most investors can maximize the probability of achieving their goals by passively investing in a broadly diversified portfolio of broadly defined index funds. Our key additions to that philosophy is the recognition that avoiding large losses is critical to achieving long-term goals, particularly when markets can operate far from equilibrium. Wise investors therefore pay careful attention to both current asset class valuation metrics and the complex mix of macro forces that cause them to change over time.

Dec18: Financial Markets and Investor Behavior: Indicators and Surprises
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Perspectives on Today’s ‘Unconventional’ Portfolio Positions”. In this note to investors, GMO offered such a clear and succinct statement of its investment philosophy that it bears sharing here (it is also a view with which we strongly agree).

Investing success comes from identifying a coherent and grounded investment philosophy, building a repeatable investment process and adhering to both of them. We seek to be long-term, long-horizon investors. Most capital that is invested institutionally is for long-term needs, yet unfortunately often acts with a short-term viewpoint. GMO’s objective is to buy assets that trade below their intrinsic value and let the force of mean reversion work on our behalf.

We believe investors should move their assets commensurate with the return opportunities that are presented to them, as well as the risks that are being underwritten. Valuation is a wonderful guide to do so. At times, we will look different as we believe that is the only way to outperform the crowd and avoid overpriced assets. The challenge is valuation offers limited insight on timing and requires patience as the investor may experience periods of protracted underperformance.


We believe that investors should focus on the risks that really matter – risks that can permanently impair their capital in the long run – such as buying overpriced assets. Many investors prefer the short-term comfort within the crowd and lose focus on what really matters. Valuation sensitive investing is hard because it takes time to work, it requires patience, and it often results in an unpopular portfolio.”

Finance’s Lengthening Shadow”, by Nicole Gelinas in City Journal.
Gelinas offers a clear warning that nonbank (or “market-based”) lending is likely to play a significant role in our next financial crisis. This warning has recently become more acute, as investors have begun to flee riskier corporate debt markets.

“Banks remain hugely important, of course, but the potential for a sudden, 2008-like seizure in global credit markets increasingly lies beyond traditional banking…the financial system isn’t just banks. Over the last ten years, a plethora of “nonbank” lenders, or “shadow banks”—ranging from publicly traded investment funds that purchase debt to private equity firms loaning to companies for mergers or expansions—have expanded their presence in the financial system, and thus in the U.S. and global economies. Banks may have tighter lending standards today, but many of these other entities loosened them up. One consequence: despite a supposed crackdown on risky finance, American and global debt has climbed to an all time high…

“The ultimate cause of the [2008] crisis, however, wasn’t complex at all: a massive increase in debt, with too little capital behind it…”

As examples of market based lending vehicles that could present future systemic risks, Gelinas points to ETFs that invest in relatively illiquid bonds and bank loans, as well as private credit funds.
Passive Attack: The Story of a Wall Street Revolution”, by Robin Wigglesworth in the 19Dec18 Financial Times
This is one of the best short histories of index investing — from how it began to what it has become — that I’ve read in 20+ years of being involved with this industry. Well worth a read.
“20 for Twenty: Selected Papers from AQR Capital Management on Its 20th Anniversary”
At 632 pages, this is much longer than Wigglesworth’s short history of indexing, but equally rewarding, with 20 thought provoking (but often technical) articles for investors.
“Intelligence and You: A Guide for Policymakers”, by Brian Katz
As we have frequently noted over the years, there are far more similarities between investment management and intelligence analysis than both sides realize. With that in mind, Brian Katz’ article should be a very thought-provoking read for investment managers, who we are sure will come away more effective for having read it.

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Nov18: Financial Markets and Investor Behavior: Indicators and Surprises
Why Is This Information Valuable?
Bogle Sounds a Warning on Index Funds”, Wall Street Journal, 29Nov18
SURPRISE

“The father of the index fund says it’s probably only a matter of time before they own half of all U.S. stocks; ‘I do not believe that such concentration would serve the national interest…

There no longer can be any doubt that the creation of the first index mutual fund was the most successful innovation—especially for investors—in modern financial history. The question we need to ask ourselves now is: What happens if it becomes too successful for its own good…

“If historical trends continue, a handful of giant institutional investors will one day hold voting control of virtually every large U.S. corporation. Public policy cannot ignore this growing dominance, and consider its impact on the financial markets, corporate governance, and regulation. These will be major issues in the coming era.”
Beware of Gradual, then Sudden Fissures in Credit”, by Michael Mackenzie in the 30Nov18 Financial Times
“We are heading into a typical late-cycle period where the excesses of corporate borrowing come home to roost, an outcome that usually surprises many investors accustomed to the good times…there is a lot more credit exposure in the form of baskets such as exchange traded funds. As we have seen, this can exacerbate selling pressure across the broad credit market.”

“Against that dynamic what really worries many in the market is the expansion of triple B-rated debt, now running at $2.5tn, up from $670bn in 2008…What remains to be seen is whether private equity funds, which have become much bigger players in credit, stick to the long view and don’t join the rush to the exit.”
Investors Start to Fret About Ballooning US Public Debt”, by Gillian Tett, in the Financial Times 8Nov18
“According to the Congressional Budget Office, the total annual cost of net interest payments on American debt in 2018 will be around $318bn. Right now, that sum seems manageable, relative to the overall American budget. But the CBO calculates that servicing costs will triple in size to nearly $1tn by 2028, on current policy trajectories and assuming that interest rates rise towards their long-term average of 3.7 per cent and 2.8 per cent for 10-year bonds and three-month bills respectively (or slightly above the current levels of 3.2 per cent and 2.34 per cent). If so, interest payments will soon become the third biggest item on the budget, eclipsing even military spending.

However, if interest rates rise faster than the CBO expects, the picture would be worse. For another striking feature of American debt is that its average maturity is only six years, shorter than most European countries. And during the Trump administration this maturity has —lamentably — shortened.”
Complacent investors face prospect of a Minsky moment”, by John Plender in the Financial Times, 13Nov18
Plender begins by highlighting “the debt-dependent nature of economic growth in the developed world.”

“Since 2008 debt has grown notably faster than nominal gross domestic product. This is most obviously the case in the US where public sector debt was on an unsustainable path even before Donald Trump introduced the first pro-cyclical fiscal expansion since Lyndon Johnson’s in the 1960s. Federal government debt is thus on a trajectory where the debt-to-GDP ratio could, according to the IMF, exceed 90 per cent by 2024. With a presidential election looming there is little likelihood Mr Trump will suddenly embrace fiscal orthodoxy…”

“Another important area of potential complacency relates to liquidity or the ability to deal without prompting adverse price movements. Regulatory curbs on proprietary trading in banks are clearly having an impact. So, too, are many structural changes in the markets including collective investment vehicles [e.g., government debt mutual funds and ETFs] that are assumed to be able to liquidate investments if investors seek to pull out in a troubled market.”

“[A further] difficulty is that the search for yield has pushed people into areas such as the corporate bond market that has never been particularly liquid … Liquidity is an elusive quality at the best of times. In a bear market it can disappear in a moment. Rest assured that not all of today’s trading strategies are predicated on that reality.”
Loss attitudes in the US Population” by Chapman et al
SURPRISE

“Base on a representative sample of the U.S. population (N = 2;000)…we find that around 50% of the U.S. population is loss tolerant. This is counter to earlier findings, which mostly come from lab/student samples, that a strong majority of participants are loss averse. Loss attitudes are correlated with cognitive ability: loss aversion is more prevalent in people with high cognitive ability, and loss tolerance is more common in those with low cognitive ability.
The Current State of Quantitative Equity Investing” by Becker and Reinganum
An excellent overview that makes a critical point.

“The current approaches and products of quantitative equity investing stand on the shoulders of major theoretical and empirical contributions in financial economics. At the root of disciplined, modern investment processes are two intuitive concepts: risk and return. The notion of total return is obvious—price appreciation plus any dividend payments.”

“Risk is not so straightforward. Indeed, in Risk, Uncertainty, and Profit, Knight (1921) distinguished between risk and uncertainty. In essence, uncertainty involves environments in which investors cannot articulate potential outcomes or the likelihood of those outcomes. In contrast, risk is much more precise, like a roulette wheel. The possible outcomes are well specified and the likelihood of each outcome is known, but in advance, an investor does not know which outcome will be realized. Quantitative methods rely on this latter view of risk.”

At The Index Investor, our focus is instead on Knightian uncertainty that does not lend itself to easy quantification based on the frequency of historical events.
Replicating Anomalies”, by Hou et al
As Stanford’s John Ioannidis has repeatedly shown in his research, replicating previous academic findings is a serious problem across the social sciences. This paper extends this analysis to previous investment research findings of different anomalies and claims that they can be exploited to generate alpha.

The authors find that, “most anomalies fail to hold up to currently acceptable standards for empirical finance.” They conclude that “capital markets are more efficient than previously recognized.”
“The Many Faces of Human Sociality: Uncovering the Distribution and Stability of Social Preferences”, by Adrian Bruhin
SURPRISE

This study presents interesting findings that divide people into three different categories of social preference, which remain stable over time.

“There is vast heterogeneity in the human willingness to weigh others’ interests in decision making. This heterogeneity concerns the motivational intricacies as well as the strength of other-regarding behaviors, and raises the question how one can parsimoniously model and characterize heterogeneity across several dimensions of social preferences while still being able to predict behavior over time and across situations…”

“We find that non-selfish preferences are the rule rather than the exception. Neither at the level of the representative agent nor when we allow for several preference types do purely selfish types emerge in our sample. Instead, three temporally stable and qualitatively different other-regarding types emerge without pre-specifying assumptions about the characteristics of types.”

“When ahead in a contest, all three types value others’ payoffs significantly more than when behind. The first type, which we denote as strongly altruistic type, is characterized by a relatively large weight on others’ payoffs – even when behind – and moderate levels of reciprocity.”

“The second type, denoted as moderately altruistic type, also puts positive weight on others’ payoff, yet at a considerable lower level, and displays no positive reciprocity.”

“The third type is averse to being behind, puts a large negative weight on others’ payoffs when behind, and behaves selfishly otherwise.”

“We also find that there is an unambiguous and temporally stable assignment of individuals to types.”
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Oct18: New Financial Markets and Investor Behavior Information: Indicators and Surprises
Why Is This Information Valuable?
Empirical Asset Pricing via Machine Learning” by Gu et al.
Excellent overview of the asset pricing accuracy of different ML techniques. Key insight: the best performing methods to a better job than traditional approaches of capturing non-linear interactions between key variables
Index Proliferation Adds Choice But Fuels Confusion” by Pauline Skypla in the Financial Times
“A recent survey by the Index Industry Association revealed its 14 member companies publish 3.29m indices, of which 3.14m cover stock markets. Only 5.6 per cent of these 3.14m are factor or smart beta indices, which are based on factors other than companies’ market capitalisation. However, that modest percentage still works out at more than 175,000.”

“These measures may not all be investable indices — benchmarking, where investors use an index to assess their own performance, is also a driver of proliferation. Even so, the choice facing investors can be confusing. “The proliferation of indices, and the way providers calculate indices that sound the same differently, makes the job of investors more difficult,” says Deborah Fuhr, managing partner at ETFGI, a London-based consultancy. Problematically, there is no standard set. “Smart beta is a space that isn’t well defined or owned by a couple of index providers,” says Ms Fuhr.”

“A check of five well-known providers in the field (ERI Scientific Beta, Vanguard, State Street Global Advisors, FTSE Russell Global Factor Index Series, MSCI Factor Indexes) shows they all include the criteria of value, momentum and volatility that are among the top half dozen filters commonly applied to smart beta products.”
The above column highlighted the growing number of indexes that underlie so-called “smart beta” products. This brought to mind a number of previous papers on the smart-beta approach, which concluded that many investors were likely to be disappointed. These include Rob Arnott’s “How Can Smart Beta Go Horribly Wrong”, by Rob Arnott, “Quantifying Backtest Overfitting in Alternative Beta Strategies”, by Suhonen et al, and “Smart Beta Herding and Its Economic Risks: Riding the Dragon” by Krkoska and Schenk-Hoppé.
Since the smart beta products first appeared, The Index Investor, we have emphasized that they are active management products (see, The Confusing World of Factor (“Smart Beta”) Models and Indexes, from our August 2003 issue). While it is possible that they will return lower returns with less risk, or higher returns with more risk than a broad market index fund, a belief that they will produce higher returns with lower risk rests on three hiqhly questionable assumptions:

(1) The mispricing of factor risks that smart beta products claim to exploit is a durable phenomenon – e.g., one caused by investors’ systematic cognitive or emotional biases;

(2) There are durable barriers that prevent other investors (including algorithmically driven funds) from arbitraging away the mispricing of one or more factor risks that smart beta products exploit; and

(3) Investors are able to identify in advance smart-beta funds that are based on those factors to which assumptions (1) and (2) apply.
Unfortunately, once it becomes widely recognized, the failure of smart-beta funds to deliver superior returns is likely to further shake investor confidence in active management.
It Was the Worst of Times: Diversification During a Century of Drawdowns” by AQR Capital Management
AQR highlights a critical distinction between diversification and hedging. The former involves investing in assets whose returns have a low correlation to equities. There is no guarantee that the returns on diversifying investments will be positive when those on equities are negative. And as we saw in 2008, correlations across asset classes can substantially increase during periods of extreme uncertainty and system stress.

In contrast, hedges are deliberately designed to increase in value when returns on equities decline –put options being the classic example.

However, for this very reason, hedging investments will tend to be more expensive than diversifying investments.
Challenging the Conventional Wisdom on Active Management: A Review of the Past 20 Years of Academic Literature on Actively Managed Mutual Funds”, by Cremers et al
Cremers presents a good summary of arguments in favor of active management. At Index Investor, we have never denied that over some periods of time many active managers will outperform an appropriate passive benchmark index.

What we have always questioned, however, is (1) their ability to sustain that superior forecasting performance (or luck) over time; (2) their ability to identify and implement profitable investment opportunities as their funds grow in size; and (3) investors’ ability to identify these superior active managers in advance, rather than in hindsight. If you consider this a joint probability and assume that each of these probabilities is slightly better than luck – say, 55% -- then the joint probability – which essentially equals the probability of an active management strategy outperforming a passive strategy over the long term – is only equal to about 17% -- or a one in six chance.
Private equity deals fail to keep up pre-crisis successFinancial Times 17Oct18
This column is a good example of the argument against active management outlined above.

The proportion of winning private equity deals — those that deliver more than three times the original investment — has seen a sharp decline in the years since the financial crisis as buyout groups struggle with record-high valuations and fierce competition, an analysis has shown.”

“On average, 35 per cent of deals produced healthy returns between 2002 and 2005 compared to roughly 20 per cent of winning transactions between 2010 and 2013, an analysis by Cambridge Associates and Bain & Company showed.”
One week after the above story this one appeared: “Private equity set to surpass hedge funds in assetsFinancial Times, 24Oct18
Private equity will overtake hedge funds as the largest alternative asset class within the next five years as investors flock to private rather than public markets in search of returns, according to a new analysis.”

There are at least two possible explanations for this: (a) optimism, overconfidence, and conformity biases on the part of the institutional investors committing more funds to private equity in spite of declining recent returns; or (b) a rational decision to take on more risk in pursuit of higher returns, even though the probability of the latter being realized has significantly declined.

In the latter case, I have in mind the no-win situation faced by public sector pension funds in the United States, most of which are badly underfunded. Their managers must choose between hoping to reduce underfunding by earning high investment returns, or telling public sector employers that they must increase their annual pension fund contributions, which in turn will necessitate either cuts in spending in other areas, and/or an increase in taxes on the public.

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Sep18: New Financial Markets and Investor Behavior Information: Indicators and Surprises
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Stories on 10th anniversary of the Lehman Bankruptcy
A recurring theme is how little has changed. While very aggressive monetary, and in some cases fiscal policy, staved off a severe and prolonged downturn, little was done to address the underlying causes of the 2008 crisis, which in some ways have arguably become worse over the past decade (e.g., debt levels, inequality, low productivity, corporate concentration, and declining labor share of national income).
The Next Financial Crisis Won’t Come from a Known Unknown” by Robin Wigglesworth in the Financial Times

No Deal Brexit has Big Implications for Europe’s Derivatives Market” by John Dizard in the Financial Times

How Hedge Funds Keep Markets Trading in a Crunch” by Gillian Tett in the Financial Times
Surprise.

Wigglesworth highlights that in a complex adaptive system like the global financial markets, crises are most likely to emerge from unanticipated combinations of apparently benign factors. He also notes that since “high frequency trading, quants, passive funds, and options now account for about 90 percent of US equity trading volumes”, this structural change in the market is likely to rapidly accelerate, and potentially exponentially increase the damage caused by whatever combination of causes trigger the next global financial crisis.

Dizard suggests one potential cause that is easily overlooked – the post 2008 concentration of derivative trading in a small number of clearinghouses that lack sufficient capital to make good on a rapidly increasing number of failed trades, as might occur if the next crisis produced, as the last one did, an exponential increase in funding/liquidity problems – e.g., for leveraged hedge funds that, as Tett reports, have, since Dodd-Frank imposed higher limits on bank capital, become much more important sources of market liquidity than they were in 2008.
The FTSE All World ex US index results compared to US equity market returns. Through September, the rest of world is down (5.26%), while the US is up 8.96%. But gains in the US are narrowly concentrated: FTSE Health, up 16.1%; Consumer Services, 18.5%, and Technology, 19.1%
Narrow markets imply a high degree of social learning and imitation, which is a hallmark of situations characterized by high uncertainty and elevated potential for sudden and substantial changes and regime shifts.