Predicting Stock Returns and Volatility with Investor Sentiment Indices: A Reconsideration Using a Nonparametric Causality‐In‐Quantiles Test

14 Pages Posted: 11 Jan 2018

See all articles by Mehmet Balcilar

Mehmet Balcilar

Eastern Mediterranean University

Rangan Gupta

University of Pretoria - Department of Economics

Clement Kyei

University of Pretoria

Date Written: January 2018

Abstract

Evidence of monthly stock returns predictability based on popular investor sentiment indices, namely SBW and SPLS as introduced by Baker and Wurgler (2006, 2007) and Huang et al. (2015) respectively are mixed. While, linear predictive models show that only SPLS can predict excess stock returns, nonparametric models (which accounts for misspecification of the linear frameworks due to nonlinearity and regime changes) finds no evidence of predictability based on either of these two indices for not only stock returns, but also its volatility. However, in this paper, we show that when we use a more general nonparametric causality‐in‐quantiles model of Balcilar et al., (forthcoming), in fact, both SBW and SPLS can predict stock returns and its volatility, with SPLS being a relatively stronger predictor of excess returns during bear and bull regimes, and SBW being a relatively powerful predictor of volatility of excess stock returns, barring the median of the conditional distribution.

Keywords: causality‐in‐quantiles, investor sentiment, linear causality, nonlinear dependence, nonparametric causality, stock markets

JEL Classification: C22, C32, C53, G02, G10, G11, G17

Suggested Citation

Balcilar, Mehmet and Gupta, Rangan and Kyei, Clement, Predicting Stock Returns and Volatility with Investor Sentiment Indices: A Reconsideration Using a Nonparametric Causality‐In‐Quantiles Test (January 2018). Bulletin of Economic Research, Vol. 70, Issue 1, pp. 74-87, 2018. Available at SSRN: https://ssrn.com/abstract=3099824 or http://dx.doi.org/10.1111/boer.12119

Mehmet Balcilar (Contact Author)

Eastern Mediterranean University ( email )

Gazimagusa
Turkey

HOME PAGE: http://www.mbalcilar.net

Rangan Gupta

University of Pretoria - Department of Economics ( email )

Lynnwood Road
Hillcrest
Pretoria, 0002
South Africa

Clement Kyei

University of Pretoria

Physical Address Economic and Management Sciences
Pretoria, 0002
South Africa

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