How behavioural factors shape investor decisions during uncertain times: evidence from the Shanghai stock exchange

The aim of this study is to examine the impacts of overconfidence and disposition biases on investor behaviour at the Shanghai Stock Exchange in China. We employ vector autoregression and impulse response functions on the SSE 50 index and its constituent stocks between 1 January 2016 and 30 April 2023, further splitting the data into pre- and post-uncertain time periods, i.e., the COVID-19 pandemic and the Russia–Ukraine war to identify overconfidence bias and the disposition effect. The results show investors in the China stock market are disposed to overconfidence bias at the market level as they are following past market returns. The disposition effect also exists during the study period. It is however determined that the overconfidence bias is the more prevalent of the two. Furthermore, these two biases have been clearly segregated for all 50 stocks before and after the aforementioned crises. Our analysis in this connection reveals that behavioural finance may be able to explain the odd patterns and swings on the Chinese financial markets that the efficient market model cannot. The study suggests that investors, policymakers, and market regulators should perform a post analysis of each investment so that they become aware of past behavioural mistakes and refrain from repeating the same. This also might help investors to minimize the negative impact of overconfidence and disposition biases on their expected utility over wartime and the regulators could build favourable policies for investors through which market volatility could be controlled during stressful periods such as the Russia–Ukraine war.

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Publication Details

Journal
Review of Behavioral Economics
Published
2026-04-14
DOI
https://doi.org/10.1108/rbe-05-2025-0230
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
0.00
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article

How behavioural factors shape investor decisions during uncertain times: evidence from the Shanghai stock exchange

Ahmed Bouteska, Mohammad Zoynul Abedin, Taimur Sharif, Jihene Ghouli
Review of Behavioral Economics
Market Dynamics and Volatility
article

How behavioural factors shape investor decisions during uncertain times: evidence from the Shanghai stock exchange

Ahmed Bouteska, Mohammad Zoynul Abedin, Taimur Sharif, Jihene Ghouli
article en

Abstract

The aim of this study is to examine the impacts of overconfidence and disposition biases on investor behaviour at the Shanghai Stock Exchange in China. We employ vector autoregression and impulse response functions on the SSE 50 index and its constituent stocks between 1 January 2016 and 30 April 2023, further splitting the data into pre- and post-uncertain time periods, i.e., the COVID-19 pandemic and the Russia–Ukraine war to identify overconfidence bias and the disposition effect. The results show investors in the China stock market are disposed to overconfidence bias at the market level as they are following past market returns. The disposition effect also exists during the study period. It is however determined that the overconfidence bias is the more prevalent of the two. Furthermore, these two biases have been clearly segregated for all 50 stocks before and after the aforementioned crises. Our analysis in this connection reveals that behavioural finance may be able to explain the odd patterns and swings on the Chinese financial markets that the efficient market model cannot. The study suggests that investors, policymakers, and market regulators should perform a post analysis of each investment so that they become aware of past behavioural mistakes and refrain from repeating the same. This also might help investors to minimize the negative impact of overconfidence and disposition biases on their expected utility over wartime and the regulators could build favourable policies for investors through which market volatility could be controlled during stressful periods such as the Russia–Ukraine war.

Review of Behavioral EconomicsVol. 13(1)
University of New Orleans (US), Chambre de Commerce et d'industrie de Paris (FR), Swansea University (GB), University of Duhok (IQ)
Openalex Percentile: Top 4%
Market Dynamics and Volatility
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