Applying prospect theory to improve the performance of capital asset pricing models in an emerging market

This study aimed to investigate whether the addition of the “PEAK-END” rule, which suggests that people consider only the best and most recent parts of their past experiences when making decisions, could improve the performance of capital assets pricing models in explaining excess returns. We combined the “PEAK-END” rule with five popular pricing models, creating ten different specifications of the models. The study compared the explanatory power of these models in the Iran capital market (as an emerging market) based on “market conditions” and “portfolio.” The results indicated that the effectiveness of the “PEAK-END” rule in improving the explanatory power of pricing models depends on market conditions and the type of companies. Specifically, for companies with large size and high momentum and in emotional markets with a comparative climate among investors, adding this rule could improve explanatory power of the pricing models. Otherwise, traditional simple models would work better.