Investor sentiments and pricing errors

Rahul Verma and Priti Verma

Review of Behavioral Finance, 2020, vol. 13, issue 4, 450-462

Abstract: Purpose - This paper computes the pricing errors ofS&P500 index by employing the valuation model developed by Doranet al.(2009) and investigates its response to individual and institutional investor sentiments. This study contributes to the literature by looking at both rational and quasi-rational sentiments and how noise trading and investments based on fundamentals affect pricing errors. Design/methodology/approach - This paper computes the pricing errors ofS&P500 index by employing the valuation model developed by Doranet al.(2009) and investigates its response to individual and institutional investor sentiments. Findings - Results show that pricing errors are persistent and stock prices systematically deviate from their intrinsic values. The authors also find that both individuals and institutional investors form their expectations based on risk factors as well as noise; however, institutional investors seems to be more driven by rational factors. The findings also suggest that institutional investors have a significant power to cause pricing errors due to unpredictable changes in their sentiments while small investors lack such ability to move stock prices away from their intrinsic values. Additionally, this paper finds that quasi-rational (rational) investor sentiments have positive (negative) impact on pricing errors suggesting that trading based on noise is an important determinant of pricing errors while investors' expectations stemming from fundamentals play an important role in improving market efficiency. Research limitations/implications - The impact of rational outlook due to changes in fundamentals seems to be greater than that of noise on the pricing errors, consistent with both risk-based and behavioral models of the asset pricing literature. Originality/value - Our study contributes to the existing literature in the following ways: first, the authors employ most recent data to compute mispricing for the market index and investigate if it is persistent and systematic. Second, the authors decompose sentiment variables into rational and quasi-rational components and trace their dynamics to better understand the role of risk factors and noise in the formation of sentiments. Third, the authors investigate the relative impact of individual and institutional investor sentiments on mispricing. Lastly, the authors examine the response of pricing errors to both rational and quasi-rational sentiments of individual and institutional investors.

Keywords: Investor sentiments; Pricing errors; Quasi-rational sentiments; Noise trading (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eme:rbfpps:rbf-01-2020-0005

DOI: 10.1108/RBF-01-2020-0005

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