Investor sentiments and pricing errors

Abstract

PurposeThis paper computes the pricing errors of S&P 500 index by employing the valuation model developed by Doran et 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/approachThis paper computes the pricing errors of S&P 500 index by employing the valuation model developed by Doran et al. (2009) and investigates its response to individual and institutional investor sentiments.FindingsResults 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/implicationsThe 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/valueOur 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.

Domestic Retail Investors’ Participation and Stock Price Efficiency in Nigeria

“…Therefore, given the definition of pricing errors as a markup over the fundamental value, the results imply that a change in the magnitude of retail investors' temporary mispricing by one SD leads to a reduction in the stock pricing errors by -15.41 units in the month of the change, -10.63 units and -6.2 units respectively, in the first and second months following the month of the change. The key implication of these findings is that retail short-run behaviour reduces stock pricing errors in the short run and is in accord with Verma and Verma (2020). The finding is also supported by the view that retailers tend to forecast market prices correctly in the short run (Barber et al, 2008;Jackson, 2003).…”

“…We examine both types of studies in more detail. CORR ADRT Among the price impact studies, Verma and Verma (2020) examine the response of the pricing errors of the S&P index to both retail and institutional sentiments. The results from the regression analysis show that institutional investors cause pricing errors, but retail investors do not.…”

“…The authors conclude, based on these findings, that retail investors' trades lack the force to move prices from their fundamental value and that institutional investors improve market efficiency. Lien et al (2020) and Verma and Verma (2020) sought to ascertain whose trades move stock prices using data on firms listed on the Taiwan Stock Exchange. The study assumed that trade orders impact stock prices and sought to determine the effect of order submission behaviour of investors; that is, order aggressiveness and trade size, on the price contribution of the trade orders.…”

“…PEt will be a positive or negative function of MSt, according to whether retailers are on average abnormally bullish or bearish over the short run. Note that a negative (positive) effect of MLt (MSt) implies that retail long-run mispricing (temporary mispricing) helps improve (reduce) price efficiency (Verma & Verma, 2020). Furthermore, BMt is expected to affect negatively PEt, given the definition of the latter as a markup on the fundamental value.…”

Investor Sentiments and Fama–French Five-Factor Premia

“…Furthermore, the findings of Verma and Verma (2020) 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. Concetto and Ravazzolo (2019) also investigated the effect of investor sentiment on returns of stock market and evaluated the predictability power of sentiment indices on returns of U.S. and European Union stock market.…”