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Asymmetric Effect of Investors Sentiments on Herding Behavior and Stock Returns: Pre and Post Covid-19 Analysis

Bagh, Tanveer and Khan, Muhammad Asif and Fenyves, Veronika and Oláh, Judit (2023) Asymmetric Effect of Investors Sentiments on Herding Behavior and Stock Returns: Pre and Post Covid-19 Analysis. MONTENEGRIN JOURNAL OF ECONOMICS, 19 (1). pp. 43-55. ISSN 1800-5845 (print); 1800-6698 (online)

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Abstract

The study investigates the asymmetric effect of investors sentiments on herding behavior and stock returns of S&P 500 markets during pre and post covid 19. We analyze daily data from May 15, 2000 (Pre Covid) to 20 Feb 2020 and form 20 Feb to –13 May, 2022 (Post Covid). We conduct Modified multiple regression Analysis by introducing investors sentiments proxy i.e., trading volume into the Chang et al., (2000) herding model named as cross-sectional absolute deviation along with Vector Autoregressive Regression and Granger Causality tests. We establish that trading volume increases herding asymmetric. Post COVID-19 has significant negative effects on herding behaviour. The findings illustrate that COVID-19 increased herding behavior in S&P 500 markets and became more intensified during COVID-19, which contributes to accentuate and elongate it. The study also documents significant positive effect of investor sentiment on stock returns, whereas COVID-19 has negative effect on S&P 500 stock returns. We propose that investor sentiments may present extrapolative or predictive feature of herding behaviour. The study will be beneficial to shape an understanding of different dynamics associated with portfolio and market in-efficiency, trading strategies as well as risk management perspective.

Item Type: Article
Uncontrolled Keywords: Investors sentiments, stock returns, COVID-19, herding behaviour
Subjects: H Social Sciences / társadalomtudományok > HG Finance / pénzügy
Depositing User: Enikő Pergéné Szabó
Date Deposited: 30 Sep 2024 06:23
Last Modified: 30 Sep 2024 06:23
URI: https://real.mtak.hu/id/eprint/206402

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