Portfolio rebalancing with respect to market psychology in a fuzzy environment: A case study in Tehran Stock Exchange

Abstract

While a vast amount of literature shows that psychological factors are major pricing determinants, portfolio optimization models ignore the emotional aspects of financial markets. Accordingly, this paper presents a two-stage portfolio rebalancing method to integrate mean-variance theory with market psychology. At the first stage, the psychological state of market participants is translated into a set of criteria to evaluate stocks, and then, in a fuzzy environment, the process of ratiocination used by technical analysts is simulated to assess the status of these criteria and determine under- and overvaluation possibilities of stocks. At the second stage, a fuzzy programming approach utilizes the calculated possibilities to revise an existing portfolio considering investor profile, transaction costs, and risk-free rate of return. An empirical study using the obtained data from Tehran Stock Exchange is employed to validate the designed method and compare it against several other investment strategies, including Buy-and-Hold strategy and a conventional portfolio rebalancing model. The results show that the proposed fuzzy method responds appropriately to the psychological component of the market. In addition, for all investor profiles, the recommended strategy completely outperforms the market and the remaining strategies.