Mean-semivariance behavior: Downside risk and capital asset pricing

TL;DR: Mean-semivariance policy optimization via risk-averse reinforcement learning optimizes the mean-semivariance (MSV) criterion in reinforcement learning w.r.t. steady reward distribution. However, the traditional dynamic programming methods are inapplicable due to the time-inconsistency and non-Bellman equation satisfaction of semivariance. Perturbation Analysis (PA) theory is used to establish the performance difference formula for MSV, leading to the development of two on-policy algorithms. Experiments demonstrate the effectiveness of the proposed methods.

TL;DR: This study examines variance and semivariance premia in global equity markets, finding negative total and downside premia (-15 bps/month) that compensate for extreme negative returns, with term structure driven by upside semivariance premia.

TL;DR: In this article, the authors tested mean-variance and downside risk frameworks in relation to portfolio management and found that the negative risk framework performs better than the positive risk framework in a highly volatile market.

TL;DR: In this paper, the authors present a critique of expected utility theory as a descriptive model of decision making under risk, and develop an alternative model, called prospect theory, in which value is assigned to gains and losses rather than to final assets and in which probabilities are replaced by decision weights.

TL;DR: Prospect Theory as mentioned in this paper is an alternative theory of individual decision making under risk, developed for simple prospects with monetary outcomes and stated probabilities, in which value is given to gains and losses (i.e., changes in wealth or welfare) rather than to final assets, and probabilities are replaced by decision weights.

TL;DR: In this paper, Bernoulli and Cramer show that mean-variance analysis should be rejected as the criterion for portfoliQ selection, no matter how economical it is as compared to alternate formal methods of analysis.

TL;DR: Prize Lecture to the memory of Alfred Nobel, December 7, 1990 as discussed by the authors, and this abstract was borrowed from another version of this item, which was published in 1990.