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 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.