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Why Do Some Asset Pricing Models Perform Poorly? Evidence from Irrationality, Transaction Costs, and Missing Factors

양철원|채준
경영연구소 (Management Research Center)|2016.06|Seoul Journal of Business|제22권 제1호|pp. 1-64|DOI 10.35152/snusjb.2016.22.1.001

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키워드

Transaction CostAsset Pricing ModelInvestor irrationalityMissing Risk FactorFama and MacBeth (1973) Regression.

초록

We identify and horse race three causes for the underperformance of some asset pricing models: investor irrationality, transaction costs, and missing risk factors. Specifically, we regress the difference of realized over expected returns (pricing error) per various asset pricing models onto proxies for the reasons for explanatory breakdown. First, for the capital asset pricing model (CAPM) and six other models we find that both investor irrationality and transaction costs are significantly related to the pricing error controlling for firm size and valuation. Second, models with more risk factors than the CAPM cannot overcome the shortcoming of the CAPM due to investor irrationality and transaction costs. In conclusion, transaction costs and investor irrationality are shown to be impediments to enhancing the prediction power of tested models regardless of additional risk factors.

Abstract

We identify and horse race three causes for the underperformance of some asset pricing models: investor irrationality, transaction costs, and missing risk factors. Specifically, we regress the difference of realized over expected returns (pricing error) per various asset pricing models onto proxies for the reasons for explanatory breakdown. First, for the capital asset pricing model (CAPM) and six other models we find that both investor irrationality and transaction costs are significantly related to the pricing error controlling for firm size and valuation. Second, models with more risk factors than the CAPM cannot overcome the shortcoming of the CAPM due to investor irrationality and transaction costs. In conclusion, transaction costs and investor irrationality are shown to be impediments to enhancing the prediction power of tested models regardless of additional risk factors.

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