Using trading data from Finland and the US, I empirically show that investors tend to buy riskier stocks following realized losses. The measure of risk that the investors seem to pay attention to is the market beta of a stock. This behavior of buying higher beta stocks after a realized loss is observed in institutional as well as individual investors, but is more pronounced among individual investors with lower expertise, who on an average buy a new stock with up to 15% higher beta than that of the old stock they were holding. For an agent with utility consistent with prospect theory, this behavior emerges as the optimal response to her problem of maximizing utility within a mental account. Furthermore, this behavior can aggregate up during market downturns and cause return predictability in high beta stocks. With this insight, I suggest a modification to the betting against beta trading strategy that can improve the Sharpe ratio more than twofold.
This paper finds evidence that despite disposition effect investor decision to sell or hold on to stock is rational in the short run. First of all, running hazard models on a large data-set spanning over fourteen years, I find that the decision to sell a stock is more related to its short term return jump, rather than its overall return over the entire holding period. Moreover, individuals’ decision to sell/hold a stock is extremely well timed in the short run (weekly horizon). On average, individual investors are successful at timing their selling/holding decisions of individual stocks, both with respect to the market performance and the overall performance of their own portfolios.
Consumption Based Asset Pricing Adjusting for Measurement Error [link]
This paper presents a modification to the testable Euler equation in the form of an adjustment term due to additive measurement error in consumption data. The error in consumption data has the potential to magnify the equity premium puzzle in a CRRA framework and including the adjustment term leads to a reduction in the estimated risk aversion coefficient. The paper also empirically estimates a ballpark figure for the variance of measurement error and demonstrates a significant resolution of the puzzle by including measurement error in the model. Using the correction term, with the standard consumption data from BEA, I solve the equity premium with a relative risk aversion coefficient of 2.6.