Crainich, Eeckhoudt, and Trannoy (2013) show that mixed risk lovers are prudent. I show that common risk loving utility functions may not exhibit mixed risk loving—as is typical for risk aversion and mixed risk aversion—and thus these traits should be carefully distinguished. In particular, risk lovers may be imprudent. (JEL D81)

We propose a simple model of how investors evaluate a trading rule, and show that the market timing of technical trading rules induces lottery-like trading profits. Therefore, investors’ preference for positive skewness caters to the popularity of technical analysis. Since prospect theory implies strong skewness preference, it can explain why investors trade extensively on chart patterns that are meaningless in light of the efficient market hypothesis. Technicians often invoke behavioral finance as its theoretical foundation. Contrary to this view, we show that ideas from behavioral finance explain why technical analysis is popular despite the lack of theoretical foundation and empirical success.

We provide a result on prospect theory decision makers who are naïve about the time inconsistency induced by probability weighting. If a market offers a sufficiently rich set of investment strategies, investors postpone their trading decisions indefinitely due to a strong preference for skewness. We conclude that probability weighting in combination with naïveté leads to unrealistic predictions for a wide range of dynamic setups. (JEL D81, G02, G11)

We propose a new asset pricing model that generalizes the mean-variance framework by including probability weighting, specifically the overweighting of rare, high-impact events. Our model—the $ Π $-CAPM—generates several new predictions: (i) skewness has a positive price effect, amplified by volatility; (ii) the price effect of volatility is negative for left-skewed assets but positive for right-skewed assets; and (iii) option-implied variance premiums for stocks have a U-shaped relation to skewness, amplified by volatility. We find strong empirical support for these predictions. Finally, we show that the $ Π $-CAPM predicts an exaggerated co-movement of assets and can explain the correlation premium.

We develop a tractable equilibrium asset pricing model with cumulative prospect theory (CPT) preferences. Using GMM on a sample of U.S. equity index option returns, we show that by introducing a single common probability weighting parameter for both tails of the return distribution, the CPT model can simultaneously generate the otherwise puzzlingly low returns on both out-of-the-money put and out-of-the-money call options as well as the high observed variance premium. In a dynamic setting, probability weighting and time-varying equity return volatility combine to match the observed time-series pattern of the variance premium. Received May 30, 2017; editorial decision August 10, 2018 by Editor Andrew Karolyi.