We show that book-to-market, size, and momentum capture cross-sectional variation in exposures to a broad set of macroeconomic factors identified in the prior literature as potentially important for pricing equities. The factors considered include innovations in economic growth expectations, inflation, the aggregate survival probability, the term structure of interest rates, and the exchange rate. Factor mimicking portfolios constructed on the basis of book-to-market, size, and momentum therefore serve as proxy composite macroeconomic risk factors. Conditional and unconditional cross-sectional asset pricing tests indicate that most of the macroeconomic factors are priced. The performance of an asset pricing model based on the macroeconomic factors is comparable to the performance of the Fama and French (1992, 1993) model. However, the momentum factor is found to contain incremental information for asset pricing.

Macroeconomic Risks and Characteristic-Based Factor Models

This study examines the relationship between positive and negative investor sentiments and stock market returns and volatility in Group of 20 countries using various methods, including panel regression with fixed effects, panel quantile regressions, a panel vector autoregression (PVAR) model, and country-specific regressions. We proxy for negative and positive investor sentiments using the Google Search Volume Index for terms related to the coronavirus disease (COVID-19) and COVID-19 vaccine, respectively. Using weekly data from March 2020 to May 2021, we document significant relationships between positive and negative investor sentiments and stock market returns and volatility. Specifically, an increase in positive investor sentiment leads to an increase in stock returns while negative investor sentiment decreases stock returns at lower quantiles. The effect of investor sentiment on volatility is consistent across the distribution: negative sentiment increases volatility, whereas positive sentiment reduces volatility. These results are robust as they are corroborated by Granger causality tests and a PVAR model. The findings may have portfolio implications as they indicate that proxies for positive and negative investor sentiments seem to be good predictors of stock returns and volatility during the pandemic. 

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Investor sentiments and stock markets during the COVID-19 pandemic

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https://doi.org/10.1016/j.najef.2022.101712

The COVID-19 pandemic uncertainty, investor sentiment, and global equity markets: Evidence from the time-frequency co-movements

ABSTRACT We examine the asymmetric effect of COVID-19 government interventions on global stock markets using a sample of 61 countries over the period of January 2020 to December 2021, applying Quantile ARDL (QARDL) and panel threshold regressions. The QARDL results show a heterogenous effect of government interventions on stock markets which varies along with country income level and stock market size. Additionally, the panel threshold regression reveals a positive effect before and a negative effect after the threshold level of government interventions. Our findings can assist policymakers to formulate intervention plans in limiting financial turbulence.

The asymmetric effect of COVID-19 government interventions on global stock markets: New evidence from QARDL and threshold regression approaches

Purpose: This paper aims to investigate the moderating role of government policy interventions amid the early spread of novel coronavirus (COVID-19) (January–May 2020) on the investor sentiment and stock returns relationship. Design/methodology/approach: This paper uses panel data from a sample of 53 countries to examine the impact of investor sentiment, measured by the financial and economic attitudes revealed by the search (FEARS) index (Da et al., 2015) on the stock return. Findings: The moderating role of government policy response indices with the FEARS index on the global stock returns is further explored. This paper finds that government policy responses have a moderating role in the sentiment and stock returns relationship. The effect holds true even when countries are split based on five classifications, i.e. cultural distance, health standard, government effectiveness, social well-being and financial development. The results are robust to an alternative measure of pandemic search intensity, quantile regression and two measures of stock market activity, i.e. conditional volatility and exchange traded fund returns. Research limitations/implications: The sample period of this study encompasses the early spread phase (January–May 2020) of the novel COVID-19 spread. Originality/value: This paper provides some early evidence on whether the government policy interventions are helpful to mitigate the impact of investor sentiment on the stock market. The paper also helps to shed better insights on the role of different country characteristics for the sentiment and stock return relationship. © 2021, Emerald Publishing Limited.

Investor sentiment and government policy interventions: evidence from COVID-19 spread

This paper investigates the relationship between economic policy uncertainty (EPU), an index capturing newspaper coverage of policy-related issues, and momentum profits. Momentum remains an unexplained anomaly. Our findings reveal a statistically negative association between EPU and hedge momentum portfolios. The short side portfolio dominates this effect as compared to the long side. EPU is statistically significant after controlling for macroeconomic variables. Furthermore, the paper conducts a battery of time series analysis, which highlights that EPU has a causal relationship with the hedge portfolio in the short run. On the other hand, the hedge portfolio has a long-term relationship with EPU, not the other way around.

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Garima Goel

Papers

Investor sentiment and government policy interventions: evidence from COVID-19 spread

Economic Policy Uncertainty and Stock Return Momentum