• Samih Antoine Azar Haigazian University
Keywords: Stock Market Data, Behavioral Finance, Valuation Function, Loss Aversion Coefficient, Loss Aversion Exponents, Certainty Equivalence, Expected Utility, Probability Weighting.


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


Abdellaoui, M. (2000). Parameter-free elicitation of utility and probability weighting functions. Management science, 46(11), 1497-1512.

Abdellaoui, M., Bleichrodt, H., & l’Haridon, O. (2008). A tractable method to measure utility and loss aversion under prospect theory. Journal of Risk and uncertainty, 36(3), 245.

Abdellaoui, M., Bleichrodt, H., & Paraschiv, C. (2007). Loss aversion under prospect theory: A parameter-free measurement. Management Science, 53(10), 1659-1674.

Akerlof, G. A., & Shiller, R. (2009), Animal Spirits: How Human Psychology Drives the Economy, and Why It Matters for Global Capitalism, Princeton University Press, Princeton.

Angner, E. (2016). A Course in Behavioral Economics, 2nd edition, Palgrave MacMillan.

Benartzi, S., & Thaler, R. H. (1995). Myopic loss aversion and the equity premium puzzle. The quarterly journal of Economics, 110(1), 73-92.

Camerer, C. (2005). Three cheers—psychological, theoretical, empirical—for loss aversion. Journal of Marketing Research, 42(2), 129-133.

Camerer, C. F., & Ho, T. H. (1994). Violations of the betweenness axiom and nonlinearity in probability. Journal of risk and uncertainty, 8(2), 167-196.

Camerer, C. F., Loewenstein, G., & Rabin, M. (Eds.). (2011). Advances in Behavioral Economics, Princeton University Press, Princeton.

Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work, The Journal of Finance, 25(2), 383-417.

Fama, E. F. (1991). Efficient capital markets: II, The Journal of Finance, 46 (5), 1575-1617.

Fishburn, P. C., & Kochenberger, G. A. (1979). Two‐piece von Neumann‐Morgenstern utility functions. Decision Sciences, 10(4), 503-518.

Foellmi, R., Jaeggi, A., & Rosenblatt-Wisch, R. (2019). Loss aversion at the aggregate level across countries and its relation to economic fundamentals. Journal of Macroeconomics, 61, 103136.

Gal, D., & Rucker, D. D. (2018). The loss of loss aversion: Will it loom larger than its gain?. Journal of Consumer Psychology, 28(3), 497-516.

Kahneman, D. (2011). Thinking, fast and slow. Macmillan.

Kahneman, D., & Tversky, A. (Eds.) (2000). Choices, Values, and Frames, Princeton University Press, Cambridge.

Levy, M. (2010). Loss aversion and the price of risk. Quantitative Finance, 10(9), 1009-1022.

Malkiel, B. G. (1996). A Random Walk Down Wall Street, Norton: New York.

Markowitz, H. (1952). Portfolio selection, The Journal of Finance, 7(1), 77-91.

Novemsky, N., & Kahneman, D. (2005). The boundaries of loss aversion. Journal of Marketing research, 42(2), 119-128.

Paraschiv, C., & L'Haridon, O. (2008). Aversion aux pertes: origine, composantes et implications marketing. Recherche et Applications en Marketing (French Edition), 23(2), 67-83.

Ross, S. A., Westerfield, R. W., & Jaffe, J. (2002). Corporate Finance, McGraw Hill: New York.

Schmidt, U., & Traub, S. (2002). An experimental test of loss aversion. Journal of risk and Uncertainty, 25(3), 233-249.

Shiller, R. (2000). Irrational Exuberance, Princeton University Press, Princeton.

Tovar, P. (2009). The effects of loss aversion on trade policy: Theory and evidence. Journal of International Economics, 78(1), 154-167.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases, Science, 185(4157), 1124-1131.

Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice, Science, 211(4481), 453-458.

Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty”, Journal of Risk and Uncertainty, 5(4), 297-323.

Wu, G., & Gonzalez, R. (1996). Curvature of the probability weighting function. Management science, 42(12), 1676-1690.
How to Cite
Azar, S. A. (2020). LOSS AVERSION IS CONSISTENT WITH STOCK MARKET BEHAVIOR. International Journal of Accounting & Finance Review, 5(4), 60-73. https://doi.org/10.46281/ijafr.v5i4.893
Research Paper/Theoretical Paper/Review Paper/Short Communication Paper