Yen carry trades have made headline news for over a decade. We examine the profitability of such trades for the period 2001–2009. Yen carry trades generated high mean returns and Sharpe ratios prior to the recent financial crisis. They continued to outperform major stock markets for the full sample period. Given the non-normality of carry trade returns, we apply non-parametric tests based on stochastic dominance (SD) to evaluate whether the high returns of yen carry trades are compatible with risk as reflected in returns on US and global stock market indices. We apply a general test for SD developed recently by Linton, Maasoumi and Whang (2005) to six currencies as well as portfolios of these currencies. For a large class of risk-averse investors, profits from yen carry trades cannot be attributed to risks.

Bali et al. (2011) uncover a new anomaly (the “MAX effect”) related to investors’ desire for stocks with lottery-like payoffs. Specifically, stocks with high maximum daily returns (high MAX) over the past month perform poorly relative to stocks with low maximum daily returns (low MAX) over the past month. We show that the MAX effect is strongly dependent on investor sentiment and is mainly due to the poor performance of high MAX stocks rather than high returns of low MAX stocks. Investors’ desire to gamble in high MAX stocks is not limited to individual investors but is also present amongst some institutions. Controlling for past sentiment reduces the significance of the MAX effect. Our findings provide a behavioral underpinning to recent “optimal beliefs” theories (Brunnermeier et al., 2007) where investor optimism generates a preference for lottery-type securities.

This paper re-examines the impact of number of trades, trade size and order imbalance on daily stock returns volatility. In contrast to prior studies, we estimate daily volatility using realized volatility obtained by summing up intraday squared returns. Consistent with the theory of quadratic variation, realized volatility estimates are shown to be less noisy than standard volatility measures such as absolute returns used in previous studies. In general, our results confirm [Jones, C.M., Kaul, G., Lipson, M.L., 1994. Transactions, volume, and volatility. Review of Financial Studies 7, 631–651] that number of trades is the dominant factor behind the volume–volatility relation. Neither trade size nor order imbalance adds significantly more explanatory power to realized volatility beyond number of trades. This finding is robust to different time periods, firm sizes and regression specifications. The implications of our results for microstructure theory are discussed.