article · Research in International Business and Finance
Investor 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. Data available on request from the authors
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DOI: 10.1016/j.ribaf.2023.102028
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