Stock market return predictability: Google pessimistic sentiments versus fear gauge

Abstract

This study aims at comparing Google Search Volume Indices (GSVIs—including market crash and bear market) and VIX (Investor Fear Gauge Index) in terms of explaining the S&P 500 returns. The VIX is found a more robust predictor of stock market returns than Google indices, and it does granger cause the GSVIs more robustly. In addition, in vector auto-regression model, VIX has more prominent effect of its past values on both Google indices. Finally, using the autoregressive distributed lag (ARDL) and nonlinear ARDL models, contrary to prior literature, we find significant symmetric negative relationship between changes in VIX and S&P 500 returns.

Keywords:

• investors’ pessimistic sentiments
• Google Search Volume
• ARDL
• NARDL
• stock market returns
• volatility index

JEL code classifications:

• C22
• G02
• G12

Public Interest Statement

Recently, both academics and practitioners have started to embrace the idea of behavioral biases of investors (investor sentiments) and their impacts on pricing of the assets. However, it is really difficult to capture and measure the variety of sentiments that matters to investors. Researchers have started to construct a laundry of such measures using both qualitative and quantitative methods. This study using Google Search Volume Index and Chicago Board Options Exchange’s Volatility Index as proxies of the pessimistic sentiment indices compares in both explaining broader market (S&P 500) returns and question whether such a relation is symmetric or asymmetric using autoregressive models. Findings suggest that volatility index as a better representative of investor sentiments that Google Search-based indices, and it has a symmetric relationship with the S&P 500 market index, which is contrary to prior literature.

Notes

1. https://support.google.com/.

Additional information

Notes on contributors

Ume Habibah

Suresh Rajput is an Assistant Professor of Finance and Accounting at the Sukkur IBA University (Pakistan). His PhD research on the pattern recognition techniques and financial analysis received an Exceptional PhD Thesis Dean’s Award from Massey University. Recently, his research focuses on the investor sentiments in capital markets, policy uncertainty, and exchange rate changes.

Suresh Rajput

Ume Habibah is a PhD scholar at Sukkur IBA University. She secured first position in MSc Accounting and Finance from Bahauddin Zakariya University, Multan, and was awarded with gold medal. Her main research interest includes behavioral finance.

Ranjeeta Sadhwani

Ranjeeta Sadhwani is a Lecturer in Finance and PhD scholar at Sukkur IBA University. She has working experience of Assistant Manager Finance at Center for Entrepreneurial Leadership & Incubation in Sukkur IBA. Her main research interest includes behavioral finance, capital asset pricing, and portfolio management.