The Role of Cognitive Biases in Digital Trading Environments: An Empirical Study of the Zimbabwe Stock Exchange

Abstrak

Purpose: This study investigates the influence of cognitive biases on investor behavior in digital trading environments, focusing on the Zimbabwe Stock Exchange (ZSE). Research Methodology: A mixed-methods approach was employed, combining survey data from active ZSE traders, semi-structured interviews with market analysts, and trading platform analytics to examine the prevalence and impact of the key cognitive biases. Results: Quantitative analysis revealed that overconfidence and herd behavior were significantly associated with higher trade frequency (? = 0.31, p < .01) and increased market volatility (p < .05). Loss aversion is negatively related to risk-taking behavior (? = ?0.27, p < .01). These findings highlight that cognitive biases substantially shape trading decisions and contribute to market inefficiency. Conclusion: Cognitive biases undermine rational investment behavior in digital trading environments. Overconfidence and herd behavior drive frequent and volatile trades, whereas loss aversion reduces risk-taking, collectively affecting market efficiency. Limitations: The study is limited to investors active on ZSE digital platforms, which may not be generalizable to other markets or offline trading contexts. Contributions: This research informs policymakers, platform developers, and financial advisors of the influence of psychological factors on trading behavior, recommending enhanced investor education, behavioral nudges, and targeted regulatory interventions to improve market efficiency and investor decision-making in Zimbabwe.