LOSS AVERSION IS CONSISTENT WITH STOCK MARKET BEHAVIOR

Samih Antoine Azar

doi:10.46281/ijafr.v5i4.893

Samih Antoine Azar Haigazian University

DOI: https://doi.org/10.46281/ijafr.v5i4.893

Keywords: Stock Market Data, Behavioral Finance, Valuation Function, Loss Aversion Coefficient, Loss Aversion Exponents, Certainty Equivalence, Expected Utility, Probability Weighting.

Abstract

The purpose of this paper is to verify that discrete statistical distributions of the US stock market are consistent with loss aversion. Loss aversion has the following tenets: an S-shaped valuation function, characterized by diminishing sensitivity, a loss aversion coefficient higher than +1, probability weighting, and reference-dependence. Diminishing sensitivity implies that the exponent of the valuation function is between 0 and +1. It is expected that this exponent be higher for losses. Probability weighting replaces objective with subjective probabilities. Loss aversion is indicated by a coefficient higher than +1 for the valuation of losses. There are three parameters: the two exponents of the valuation function, and the loss aversion coefficient. There is one non-linear equation: the certainty equivalence relation. The procedure is to fix two parameters and find the third parameter by solving the non-linear certainty equivalence equation, using the EXCEL spreadsheet. The program is repeated for more than one case about the fixed parameters, and by enriching the analysis with probability weighting. The calibrations executed point strongly to the conclusion that loss aversion is consistent with six discrete distributions of the first two moments of returns of the US stock markets. The calibration process provides for reasonable estimates of the key parameters of loss aversion. These estimates suggest a more pronounced diminishing sensitivity, and a higher than expected coefficient of loss aversion, especially when probability weighting is imposed.

Author Biography

Samih Antoine Azar, Haigazian University

Full Professor, Faculty of Business Administration & Economics, Haigazian University, Beirut, Lebanon

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