Revisiting overconfidence in investment decision-making: Further evidence from the U.S. market

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. [Display omitted] •Feedforward neural network nonlinear Granger causality test, and nonlinear impulse response analysis based on local projections used.•The presence of overconfidence behavior is tested by examining a causal relationship between return and trading volume.•Investors overconfidence is still present in the U.S market from 2016 to 2021 including the Covid-19 uncertainty period.