nvestor overconfidence leads to excessive trading due to positive returns, causing inefficiencies in stock markets. Using a novel methodology, we build on the previous literature by investigating the existence of overconfidence by studying the causal relationship between return and trading volume covering the COVID-19 period. We implement a nonlinear approach to Granger causality based on multilayer feedforward neural networks on daily returns and trading volumes from 2016 to 2021, covering 1424 daily observations of the S&P 500 index. The results provide evidence of overconfidence among investors. Such behavior may be linked to the increase in the number of investors. However, there is a decline in the rate of returns during the study period, implying uncertainty caused by the COVID-19 pandemic.
Bouteska, A., Harasheh, M., Abedin, M.Z. (2023). Revisiting Overconfidence In Investment Decision-Making: Further Evidence From The U.S. Market. RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE, 66, 1-20 [10.1016/j.ribaf.2023.102028].
Revisiting Overconfidence In Investment Decision-Making: Further Evidence From The U.S. Market
Harasheh, Murad;
2023
Abstract
nvestor overconfidence leads to excessive trading due to positive returns, causing inefficiencies in stock markets. Using a novel methodology, we build on the previous literature by investigating the existence of overconfidence by studying the causal relationship between return and trading volume covering the COVID-19 period. We implement a nonlinear approach to Granger causality based on multilayer feedforward neural networks on daily returns and trading volumes from 2016 to 2021, covering 1424 daily observations of the S&P 500 index. The results provide evidence of overconfidence among investors. Such behavior may be linked to the increase in the number of investors. However, there is a decline in the rate of returns during the study period, implying uncertainty caused by the COVID-19 pandemic.File | Dimensione | Formato | |
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