Investor Sentiment: Does it Augment the Performance of Asset Pricing Models?
38 Pages Posted: 25 Nov 2016
Date Written: June 1, 2016
Abstract
This paper examines whether incorporating various investor sentiment measures in conditional asset pricing models can help to capture the impacts of the size, value, liquidity and momentum effects on risk-adjusted returns of the U.S. individual stocks. Using monthly data of individual securities for the period January 1980 to December 2014, we determine the significance of equity fund flow, IPO first day returns, IPO volume, closed-end fund discount, equity put-call ratio, dividend premium, change in margin debt and sentiment index, by including them as conditioning information in asset pricing models. Our results show that sentiment augmented asset pricing models significantly contributes in capturing the impacts of the size, value, liquidity and momentum effects of risk-adjusted returns. In particular, we observe the outperformance of equity fund flow, IPO first day return and put-call ratio in capturing the predictive power of equity characteristics for all the conditional models examined.
Keywords: Investor sentiment, Asset Pricing, Conditioning information
JEL Classification: G12, G14
Suggested Citation: Suggested Citation