This paper sheds empirical light on whether investor sentiment affects the profitability of price momentum strategies. We hypothesize that when investors are optimistic, their expectations will be more miscalibrated relative to those obtained from objective probabilities, and arbitrage will be more difficult with short-selling constraints. Our results show that momentum rises only when investor...

Individual investors trade stocks in a way very different from what mainstream financial economic theory would predict: they generate too much trading volume and yet obtain belowbenchmark performance. This chapter overviews major 'puzzles' of individual investor trading. The extant literature suggests that behavioral biases and psychological explanations are largely responsible for many of the ...

This paper studies the relation between individuals’ mutual fund flows and fund characteristics, establishing three key results. First, consistent with tax motivations, individual investors are reluctant to sell mutual funds that have appreciated in value and are willing to sell losing funds. Second, individuals pay attention to investment costs as redemption decisions are sensitive to both exp...

In 1980s, many empirical researches’ findings (i.e., Shiller(1984), Thaler (1985) et al. ) did not support efficient market hypothesis (EMH). Previous studies (e.g., Bernartzi and Thaler, 1995) related to behavioral model suggest that certain market anomalies are consistent with the presence of irrational trades by investors. Kahneman and Tversky (1979) proposed the prospect theory as an altern...

Empirical studies show that individual investors do not always behave rationally and do not use standard investment portfolio selection tasks. In this paper we focus on investor choices and the basic elements affecting them. The paper presents optimization model based on a measure of investor satisfaction. The model is created on the basis of surveys conducted among Polish individual investors....

We examine the situation when the investor wants to outperform a certain benchmark by actively trading in this asset, typically a stock index. We consider an investor who wants to minimize the expected shortfall in the case he fails to achieve this goal. Using recently developed techniques of Föllmer and Leukert, we can relate this optimal investment problem to option hedging. This allows us to...

This appendix reports the results for the baseline and yearly/quarterly context-based classifiers when using the 1:10 regulator cost setting. Since the AUC values are computed across different cost settings (and are therefore the same for the investor and regulator situations), we report only the legitimate/fraud recall rates. Overall AUC values as well as results for the investor cost setting ...

We show that the optimal asset allocation for an investor depends crucially on the theory with which the investor is modeled. For the same market data and the same client data different theories lead to different portfolios. The market data we consider is standard asset allocation data. The client data is determined by a standard risk profiling question and the theories we apply are mean–varian...