Sports Betting used to explain Value and Momentum Effects

"Progress on the efficient markets question is mired by the joint hypothesis problem (Fama (1970)) that any test of efficiency is inherently a test of the underlying equilibrium asset pricing model. As a result, a host of rational and behavioral theories for the existence of various return predictors populate the literature. Rational theories link return premia to aggregate systematic risks (e.g., macroeconomic shocks or proxies for state variables representing the changing investment opportunity set and marginal utility of investors) through the stochastic discount factor in an informationally efficient market, while behavioral theories link returns to investor cognitive errors or biases in a less than perfectly efficient market.

Capital market security returns provide a difficult, if not impossible, empirical laboratory to distinguish between these broad views of asset pricing since the researcher cannot directly observe marginal utility or investor preferences, and where both rational and behavioral forces may simultaneously be at work.

To circumvent the joint hypothesis problem, I propose an alternative asset pricing laboratory—sports betting markets. The idea is simple. Either our asset pricing models should explain security returns from all markets, or we need different models for different asset types. If the former is more appealing, then there are two key features of sports betting markets that provide a direct test of behavioral asset pricing theory, distinct and not confounded by any rational asset pricing framework: 1) sports bets are completely idiosyncratic, having no relation to any aggregate risk or risk premia in the economy; 2) sports contracts have a very short known termination date where uncertainty is resolved by an outcome independent from betting activity, which allows mispricing to be detected.

For the first feature, the critical point is that I only examine the cross-section of sports betting contracts— comparing betting lines across games at the same time and even across different bets on the same game. Aggregate risk preferences and changing risk premia might affect the entire betting market as a whole but they should have no bearing on the cross-section of games or the cross-section of contracts on the same game.2 Hence, rational asset pricing theories have nothing to say about return predictability for these contracts. On the other hand, sports betting contracts should be subject to the same behavioral biases that are claimed to drive the anomalous returns in financial security markets. The second key feature of the sports betting contracts is that they have a known, and very short, termination date, where uncertainty is resolved by outcomes that are independent of investor behavior, providing a terminal “true” value for each security.

Focusing on the cross-section of sports betting contracts, this study examines cross-sectional predictors of returns found in financial markets: namely the three that have received the most attention from theory, which not coincidentally, also have the most robust supporting evidence—momentum, value, and size.

I find that price movement from the open to the close of betting reacts to momentum and value measures in a manner consistent with the evidence in financial markets. However, thee price movements are fully reversed from the close of betting to the game outcome, where the true terminal value is revealed. The evidence suggests that bettors follow momentum and value signals (e.g., chasing past performance and “cheap” contracts) that push prices away from fundamentals, that get reversed when the true price is revealed. These results are consistent with the delayed overreaction story of Daniel, Hirshleifer, and Subrahmanyam (1998) that argues why similar momentum and value patterns exist in financial security returns.

Can these results also shed light on the return premia in financial markets? While sports betting markets isolate tests of behavioral theories from risk-based theories, other differences between sports and financial markets could also matter for generalizing the results. If investor preferences and/or arbitrage activity are vastly different across the two markets then generalizing the results may be difficult. There are reasons to be both aggressive and cautious in generalizing the results. On the aggressive side, bettors prefer to make rather than lose money,6 and the experimental psychology evidence motivating the behavioral theories comes from generic risky gambles, and hence should apply equally to sports betting contracts as it does financial securities. Finding that the exact same predictors in financial markets also explain returns in sports betting markets provides a direct link to financial markets that implies either that behavioral biases are (at least partially) responsible for the same cross-sectional return patterns in financial markets or that this is just a remarkable coincidence, or that we require different explanations for the same patterns in different markets. On the cautious side, comparing economic magnitudes, I find that the returns generated from momentum and value per unit of risk (volatility) are about one fifth as large as those found in financial markets, suggesting that the majority of the return premia in financial markets could be coming from other sources. In addition, examining the covariance structure of returns, where unlike financial markets, which show significant covariation in value and momentum returns across securities, markets, and even asset types (Asness, Moskowitz, and Pedersen (2013)), I find no covariance among value or momentum betting contracts. This
may be further testament to behavioral forces influencing prices in this market, since there is no common source of risk, but diverges from the evidence in financial markets, where a significant part of the return premia there may come from a separate common source."

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