This article examines the efficiency of the National Football League betting market. The standard ordinary least squares regression methodology is replaced by a probit model. This circumvents potential econometric problems, and allows the authors to implement more sophisticated betting strategies where bets are placed only when there is a relatively high probability of success. In-sample tests indicate that probit-based betting strategies generate statistically significant profits. Whereas the profitability of a number of these betting strategies is confirmed by out-of-sample testing, there is some inconsistency among the remaining out-of-sample predictions. The authors' results also suggest that widely documented inefficiencies in this market tend to dissipate over time.

This paper studies the role that risk and mispricing play in the negative relation between extreme positive returns and future returns. We document a strong ‘MAX effect’ in Australian equities over 1991–2013 that is robust to risk adjustment, controlling for other influential stock characteristics and, importantly, manifests in a partition of the 500 largest stocks. While there is no evidence that MAX proxies for sensitivity to risk, the findings are highly consistent with a mispricing explanation. Adapting the recent methodological innovation of Stambaugh et al. (2015) to classify stocks by their degree of mispricing, we show that the MAX effect concentrates amongst the most-overpriced stocks but actually reverses amongst the most-underpriced stocks. Consistent with arbitrage asymmetry, the magnitude of the MAX effect amongst overpriced stocks exceeds that amongst underpriced stocks, leading to the overall negative relation that has been well documented.

There is a large body of literature examining the association between stock characteristics and the cross-section of stock returns in international markets. Recently, Cooper et al. (2008) reported a strong association between total asset growth and stock returns in the US. In this paper, we show that an asset-growth effect also exists in the Australian equity market. Of particular interest, it is present amongst the largest Australian stocks. Over the 1983–2007 period, an equally-weighted portfolio of low-growth Big stocks outperforms a portfolio of high-growth Big stocks by an average 1% per month, equating to nearly 13% per annum. At an individual stock level of analysis, the asset-growth effect remains even after controlling for other variables whose association with the cross-section of returns is well known. Finally, we explicitly test whether asset growth is a priced risk factor using the common two-stage cross-sectional regression methodology. We find no evidence to support a risk-based explanation, thereby lending credence to Cooper et al.’s (2008) suggestion that the asset-growth effect is attributable to mispricing.

Subsequent to the influential paper of [Chan, K.C., Karolyi, G.A., Longstaff, F.A., Sanders, A.B., 1992. An empirical comparison of alternative models of the short-term interest rate. Journal of Finance 47, 1209–1227], the generalised method of moments (GMM) has been a popular technique for estimation and inference relating to continuous-time models of the short-term interest rate. GMM has been widely employed to estimate model parameters and to assess the goodness-of-fit of competing short-rate specifications. The current paper conducts a series of simulation experiments to document the bias and precision of GMM estimates of short-rate parameters, as well as the size and power of [Hansen, L.P., 1982. Large sample properties of generalised method of moments estimators. Econometrica 50, 1029–1054], J-test of over-identifying restrictions. While the J-test appears to have appropriate size and good power in sample sizes commonly encountered in the short-rate literature, GMM estimates of the speed of mean reversion are shown to be severely biased. Consequently, it is dangerous to draw strong conclusions about the strength of mean reversion using GMM. In contrast, the parameter capturing the levels effect, which is important in differentiating between competing short-rate specifications, is estimated with little bias.

As a consequence of the 2008 financial crisis, the Australian regulator mandated daily reporting and disclosure of both short flow and short interest at an individual stock level. This provides a unique opportunity to study the nature and source of information embedded in each metric. Our empirical findings are consistent with short sellers being heterogeneous with respect to their information. Short flow is strongly related to recent returns and buy-order imbalance, and both anticipates and reacts to price-relevant announcements. In contrast, short interest is related to the mispricing of firm fundamentals. The distinct differences in the nature of information embedded in the two metrics provide an economic rationale for both the unique ability of each metric to predict returns and the future horizons over which the information is relevant.

Lettau and Ludvigson [Lettau, M., Ludvigson, S, 2001. Consumption, aggregate wealth and expected stock returns. Journal of Finance 56, 815–849] argue that fluctuations from the equilibrium ratio of consumption to wealth (cây) reflect changing expectations of asset returns and document significant short-horizon predictability based on cây. This paper further explores the role of consumer expectations in modeling time variation of expected equity returns by considering two measures of consumer expectations: (i) consumer behavior as reflected in cây, and (ii) a more-direct measure of expectations captured by the Index of Consumer Sentiment (ICS). We report strong regression-based evidence of return predictability based on cây, which remains evident even after accounting for various sources of estimation risk. However, the regression-based evidence of predictability does not necessarily imply that shifts in aggregate consumption and the components of aggregate wealth give rise to economically significant investment signals. The survey-based measure of expectations (ICS) is shown to complement the behavioral measure (cây) but has no apparent stand-alone predictive value in forecasting equity returns.

ABSTRACT This article examines the efficiency of the National Football League (NFL) betting market. The standard ordinary least squares (OLS) regression methodology is replaced by a probit model. This circumvents potential econometric problems, and allows us to implement more sophisticated betting strategies where bets are placed only when there is a relatively high probability of success. In‐sample tests indicate that probit‐based betting strategies generate statistically significant profits. Whereas the profitability of a number of these betting strategies is confirmed by out‐of‐sample testing, there is some inconsistency among the remaining out‐of‐sample predictions. Our results also suggest that widely documented inefficiencies in this market tend to dissipate over time.

The first 100 days of a newly-elected President's administration are often a period of substantial and concentrated policy change. This paper shows that measures of uncertainty and risk aversion rise sharply during Presidential honeymoons. Consistent with theoretical models that suggest that investors demand compensation for bearing heightened political risk, we document striking spread returns to value, investment and profitability anomalies during honeymoons. For example, the book-to-market value premium averages 3.51% per month during Presidential honeymoons, yet only 0.27% per month at other times. These findings survive numerous robustness checks. Nonetheless, establishing a direct link between escalating political risk and equity returns proves challenging.