Abstract
This study investigates whether Google Search Volume Indices (GSVIs) bring shifts in the expected return of prominent pricing factors in comparison to the Volatility Index (VIX). The results show t...
Highlights
The equilibrium asset pricing models such as Intertemporal Capital Asset Pricing Model (ICAPM) (Merton, 1973), and Arbitrage Pricing Model (APM) (Ross, 1976) imply that expected excess returns should vary with exposure to multiple factors instead of the single market factor of Capital Asset Pricing Model (CAPM) (Sharpe, 1964; Lintner, 1965; Mossin, 1966)
We go step further to examine the effect of Google Search Volume Indices (GSVIs) and volatility index (VIX) to determine variations in the expected return of the pricing factors included in Fama–French five-factor and q-factor model
The findings show that changes in VIX (D_VIX) Granger cause variation in all factors included in the q-factor model and in the five-factor model except high minus low (HML)
Summary
The equilibrium asset pricing models such as Intertemporal Capital Asset Pricing Model (ICAPM) (Merton, 1973), and Arbitrage Pricing Model (APM) (Ross, 1976) imply that expected excess returns should vary with exposure to multiple factors instead of the single market factor of Capital Asset Pricing Model (CAPM) (Sharpe, 1964; Lintner, 1965; Mossin, 1966). We use Volatility Index (VIX) and Google Search Volume Index (GSVI) as proxy for investors’ sentiments to analyze the impact of sentiments on premium of pricing factors included in Fama and French (2015) five factor model and Hou et al (2015) q-factor model. The impact of investor sentiments on the asset pricing models is relatively less explored in the extant literature We address this issue in the paper by empirically testing whether factor returns can be predicted using Google search volume indices (GSVIs). We go step further to examine the effect of GSVIs and VIX to determine variations in the expected return of the pricing factors included in Fama–French five-factor and q-factor model. We use VIX to estimate variations in the expected returns for Fama–French five-factor model and q-factor model
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