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Writer's pictureRobin Powell

Institutional investors vs individuals: Who wins?

Updated: Nov 22





Alpha is a zero-sum game, so if there are losers, there must be winners. But are those winners more likely to be institutional investors or individuals? LARRY SWEDROE presents the latest academic evidence.



In his famous 1991 paper, The Arithmetic of Active Management, Nobel Prize winner William Sharpe explained that, before costs, active management is a zero-sum game, and after costs it is a negative-sum game. “Properly measured, the average actively managed dollar must underperform the average passively managed dollar, net of costs. Empirical analyses that appear to refute this principle are guilty of improper measurement.” In other words, for active managers to be successful, they must have victims they can exploit. Who exactly are these victims?


The evidence is that the victims are likely to be individual investors. The research has found that, in aggregate, individual investors around the globe underperform standard benchmarks, such as low-cost index funds, even before costs or taxes. When they trade, they are exploited by institutional investors. And while there is a wide dispersion of results among individual investors, even the best traders have a hard time covering costs. Interestingly, research by Brad Barber and Terrance Odean has found that not all underperformance can be attributed to the excessive trading done by individual investors—on average, individual investors exhibit perverse security-selection abilities, buying stocks that go on to earn subpar returns and selling stocks that go on to earn above-average returns.



"Lottery" stocks

Research, such as the study Lottery Preference and Anomalies, has demonstrated that “lottery” stocks — those offering the potential for outsized returns, like penny and growth stocks — have performed poorly. The study Do the Rich Gamble in the Stock Market? Low Risk Anomalies and Wealthy Households also has found that there are investors who have a “taste,” or preference, for lottery-like investments — investments that exhibit positive skewness and excess kurtosis (fat tails). This leads them to irrationally (from a traditional finance perspective) invest in high-volatility stocks (which have lottery-like distributions), driving their prices higher and thus resulting in poor returns — they pay a premium to gamble.


If the markets were perfectly efficient, arbitrageurs would drive prices to their right levels. However, in the real world, limits to arbitrage, and the costs and fear of shorting, can prevent rational investors from correcting mispricings. The low-beta/low-volatility anomaly (low-beta/low-volatility stocks have higher risk-adjusted returns than high-beta/high-volatility stocks) is an example of the lottery effect with mispricings persisting.


Lottery-like distributions have been found in IPOs, “penny stocks,” extreme high-beta stocks, small-growth stocks with low profitability and high investment, and financially distressed stocks that are either in or near bankruptcy. However, the preference for lottery-like distributions doesn’t explain all of the underperformance of individual investors. Research, such as the study Investor Sentiment and the Cross-Section of Stock Returns, has found individual investors are more prone than institutional investors to trade based on sentiment — they tend to be “noise traders.” And trading on “noise” negatively impacts returns.



Who are the winners?

Because alpha is a zero-sum game, if there are losers (retail investors) even before costs, there must be winners. Who are the winners? The winners are institutional investors, such as actively managed mutual funds. The research shows that on a gross return basis, active fund managers are able to generate alpha, exploiting the bad behavior of individual investors. For example, Jonathan Berk and Jules van Binsbergen, authors of the study Measuring Skill in the Mutual Fund Industry, found that the average mutual fund has added value by extracting about $2 million per year from financial markets, and that the value added is persistent for as long as 10 years. Berk and van Binsbergen concluded: “It is hard to reconcile our findings with anything other than the existence of money management skill.”


The study Mutual Fund Performance: An Empirical Decomposition into Stock-Picking Talent, Style, Transactions Costs, and Expenses by Russ Wermers, provides further evidence of stock-picking skill. Wermers found that on a risk-adjusted basis, the stocks active managers selected outperformed their benchmark by 0.7 percent per year. However, investors earn net, not gross, returns. The research finds that their total expenses—not just the fund’s expense ratio, but trading costs as well—more than eroded the benefits derived from their stock-selection skills, leaving investors with net negative alphas. What economists call the “economic rent” is going to the scarce resource (the ability to generate alpha), not to the plentiful resource (investor capital). That occurs just as economic theory predicts it should. But while active institutional investors have been able to exploit the bad behavior of individual investors (who exhibit a preference for lottery-like stocks), the fund sponsors have been the winners, not investors in the funds.



Latest research

Ecenur Uğurlu-Yıldırım and Ilkay Sendeni-Yüncü contribute to the literature with their study Additional Factor in Asset-Pricing: Institutional Ownership, published in the May 2021 issue of Finance Research Letters. Based on the evidence that institutional investors’ stock selection has outperformed that of individual investors, they hypothesised that “institutional investor variable is a proxy for some systematic risk factors.” Thus, they added a new IMI (institutional minus individual) factor to the Carhart four-factor (market beta, size, value and momentum) model to determine if it added explanatory power to the cross-section of returns. In addition to their hypothesis that IMI is a proxy for systematic risk factors, it’s also possible that IMI could explain behavioral anomalies, such as the preference for lottery-like stocks. Their data sample spanned the period 1980-2016. Following is a summary of their findings:


  • The new five-factor model reduces mispricing.


  • The greatest improvement in explanatory power was in small stocks (consistent with research demonstrating that small stocks with the highest individual ownership are more subject to investor sentiment than others) and stocks with the lowest and highest institutional ownership.


  • There is a significant relationship between IMI and change in investor sentiment — the IMI factor most likely proxies for noise-trader risk.


  • The bid-ask spread was greater for the portfolios with the lowest institutional ownership than for those with the highest institutional ownership —prices become more informative because of informed investor trading. Thus, IMI might proxy for information asymmetry risk.


  • Results were robust to testing against the Fama-French five-factor model (market beta, size, value, profitability and investment).



Conclusions

Their findings led Uğurlu-Yıldırım and Sendeni-Yüncü to conclude: “Our findings suggest that IMI helps us to improve the asset-pricing models especially for portfolios including the lowest institutional ownership and for portfolios including the highest institutional ownership. This result resonates well with the related literature suggesting that noise-trader risk is more probably observed in stocks with the highest individual ownership.”

Their findings provide further evidence for why individual investors should avoid buying individual stocks. Instead, they should focus on managing risk through broad diversification across unique sources of risk — best accomplished through mutual funds and ETFs.




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