Behavioral Biases and Investor Decision-Making in the Saudi Stock Market: The Moderating Roles of Overconfidence and Loss Aversion in an Islamic and Oil-Dependent Economy
Jul 2026· Journal of Risk and Financial Management· Vol 19, pp. 522· 0 citations· 33 references
Abstract
Background: This study examines how four canonical behavioral biases (overconfidence, herding, anchoring, and loss aversion) influence investor decision-making in the Saudi stock market (Tadawul), and whether overconfidence and loss aversion operate as moderating forces on herding and anchoring, respectively. Methods: Employing a quantitative, cross-sectional design with a stratified sample of 384 retail investors, the study applies Partial Least Squares Structural Equation Modelling (PLS-SEM) to test six hypotheses derived from Modern Portfolio Theory and Behavioral Finance frameworks. The measurement model satisfies established thresholds for reliability, convergent validity, and discriminant validity. Results: Results confirm that loss aversion is the dominant predictor of behaviorally influenced decision-making (β = 0.402, p < 0.001, f2 = 0.188), followed by herding (β = 0.234, p < 0.001) and overconfidence (β = 0.164, p = 0.001), while anchoring does not exert a statistically significant independent effect (β = 0.102, p = 0.084 one-tailed, p = 0.168 two-tailed). Neither the overconfidence × herding (β = 0.005, p = 0.920, two-tailed) nor the loss aversion × anchoring (β = −0.039, p = 0.330, two-tailed) interaction terms reach significance, indicating that these bias pairs operate as independent additive forces rather than compounding systems. The model explains 55.7% of the variance in investor decision-making (R2 = 0.557). Conclusion: The findings advance behavioral finance theory in GCC and Islamic equity markets by (1) demonstrating non-equivalence of anchoring effects relative to Western-market benchmarks, (2) resolving competing theoretical predictions about bias interaction effects, and (3) providing context-specific evidence that loss aversion subsumes anchoring cognition in the Saudi market. Practical implications for the Capital Market Authority, financial educators, and individual investors are discussed and contextualized within the Saudi market setting.
Indian retail investors increasingly deviate from rational decision-making during periods of stock-market volatility, yet the mechanisms underlying this deviation remain incompletely modelled in the Indian context. Drawing on Prospect Theory, this study examines how five behavioural biases, Prudent and Precautionary Behaviour, Financial Heuristics, Self-Regulation Bias, Anchoring Bias, and Information Heuristics, shape retail investors' buy, hold, and sell decisions across positive and negative volatility phases. Primary survey data were collected from 329 individual investors across Tier I, II, and III Indian cities using a structured, validated questionnaire. Confirmatory Factor Analysis and Structural Equation Modelling, conducted in SPSS and AMOS, validated a hierarchical five-factor bias structure (Cronbach's α = .693–.910; 59.37% variance explained) and tested ten hypothesised bias–decision paths. Seven paths were statistically significant, and behavioural biases consistently exerted stronger effects during negative volatility than positive volatility, with anchoring bias and self-regulation bias emerging as the strongest predictors of irrational decisions. These findings extend Prospect Theory's loss-aversion principle to India's retail-investor context and carry direct implications for investor education, behavioural nudges on digital trading platforms, and advisor-level behavioural profiling.
Kantesha Sanningammanavara, Ashoka S· International Journal For Mu...· 0 citations
Background: Behavioural finance challenges the assumption of fully rational investment decisions by showing that cognitive biases can shape how retail investors evaluate risk, information and market opportunities. In this context, integrating behavioural biases with the Theory of Planned Behaviour provides a useful framework for examining the investment intentions of retail investors.
Aims: This study examines the influence of behavioral biases and TPB components such as attitude, subjective norms, and perceived behavioral control on investment intentions of retail investors based in Delhi-NCR region, where behavioral biases are treated as second order construct, consisting of anchoring, availability, loss aversion, mental accounting, overconfidence, representativeness, and regret aversion.
Method: A structured questionnaire was administered to 379 retail investors using purposive and snowball sampling techniques. The data were analysed using PLS-SEM (SmartPLS 4.0) with bootstrapping based on 10,000 resamples.
Findings: Behavioral biases emerged as the strongest predictor of intention to invest (β = 0.441, p < 0.001) followed by perceived behavioral control (β = 0.199, p < 0.001), attitude (β = 0.159, p = 0.001), while subjective norms were insignificant (β = 0.088, p = 0.113). It was further noted that attitude mediated the link between behavioral biases and the intention to invest (β = 0.149, p < 0.001). The model accounted for 58.6% of variance (R² = 0.586).
Conclusion: This study provides a validated second-order model of behavioral biases and demonstrates that biases outperform TPB constructs, thus broadening TPB to behavioral finance theory. This mediation by attitude also suggests that there are two parallel decision routes for investment, one involves evaluation of attitudes, while the other route goes directly to making the decisions based on affects. This study advises on design of intervention strategies to mitigate bias and boost self-efficacy among advisors, fintech, regulators and educators.
U. Gutt, Fiza Bhateja· Asian Journal of Economics B...· 0 citations
This paper examines how investors behave in the Dar es Salaam Stock Exchange (DSE), with a focus on their tendency to follow others when making investment decisions. Based on survey data from 356 investors, the study uses Partial Least Squares Structural Equation Modeling (PLS-SEM) to explore how psychological, demographic, and informational factors shape herding behaviour. The results reveal that psychological traits including risk aversion, overconfidence, and trust in peers together with the market information environment, have a strong and significant effect on herding. In contrast, demographic factors such as age, education, and income show only weak influence. In the presence of limited information and uncertainty, psychological biases have more significance, hence making the investors base their decision on the actions of other people instead of their independent analysis. Such collective behaviour creates mispricing in the market, leading to inefficiency and poor investment performance. According to the findings of the paper, information transparency and better awareness of the investors would be effective in preventing herding behaviour.
Abraham Charles Nathanael, Karoli Calist Chami· Sriwijaya International Jour...· 0 citations
This study aims to analyze the influence of investor sentiment, investor overconfidence, and investor attention on stock price crash risk, as well as to examine the role of analyst herding behavior as a moderating variable among technology sector companies listed on the Indonesia Stock Exchange (IDX), Singapore Exchange (SGX), Bursa Malaysia (KLSE), and the Stock Exchange of Thailand (SET) during the 2021–2025 period. The study employs a quantitative approach using secondary data obtained from financial statements, stock trading data, and corporate annual reports. The sample was determined using a saturated sampling technique, resulting in 468 observations. Stock price crash risk is proxied using Negative Conditional Skewness (NCSKEW) and Down-to-up Volatility (DUVOL). Data analysis was conducted using descriptive statistics, classical assumption tests, Moderated Regression Analysis (MRA), F-tests, t-tests, the coefficient of determination, and robustness tests. The research results indicate that investor sentiment, investor overconfidence, and investor attention do not significantly affect stock price crash risk, whether measured using the NCSKEW or DUVOL proxies. Furthermore, analyst herding does not moderate the relationship between these behavioral factors—investor sentiment, overconfidence, and attention—and stock price crash risk. Robustness tests employing both crash risk proxies and regression model comparisons yield consistent conclusions. These findings suggest that the examined investor behavioral factors fail to explain the variation in stock price crash risk among technology sector companies in Southeast Asia, implying the existence of other factors outside the research model that may influence such risk.
H. Herlina, Rr.Sri Handayani· Dinasti International Journa...· 0 citations
This study examines the demographic, strategic, and behavioural determinants of investor satisfaction among mutual fund investors, addressing the gap in existing literature that typically studies these factors in isolation. Using primary data collected from 500 mutual fund investors through a structured questionnaire, the study analyses demographic profile, investment strategies, risk management practices, and reactions to market movements through percentage analysis, cross-tabulation, one-way ANOVA, and multiple regression analysis. The findings reveal that the typical investor is a middle-aged, educated, salaried individual with moderate income, investing primarily for retirement and children's education, and relying heavily on mutual fund distributor recommendations as both a strategy and a decision criterion. ANOVA results confirm that income, age, and occupation each significantly influence overall satisfaction, perceived strategy effectiveness, annual returns, and strategy performance ratings. The regression model explains 46.7% of the variance in overall satisfaction, with following market trends (β = 0.491), strategy used (β = 0.338), and income (β = 0.204) emerging as the strongest predictors, while confidence level and age show no significant independent effect. The study concludes that investor satisfaction is driven more by behavioural engagement and financial capacity than by psychological disposition alone, and offers practical suggestions for investors, distributors, fund houses, and policymakers to strengthen investor education and distributor accountability.
Gowtham G, Dr. V. Padmanabhan· Journal of Asia Entrepreneur...· 0 citations
This study examines the impact of behavioural finance on investment decision-making among retail investors associated with selected investment banks in India. Moving beyond traditional rational finance frameworks, the research focuses on two primary psychological dimensions: heuristics and prospect theory. Primary data were gathered through a structured questionnaire from a sample of 184 active investors using a convenience sampling technique. The data were analyzed using Pearson correlation and multiple linear regression analysis. The empirical results demonstrate that both heuristics and prospect theory have a statistically significant negative relationship with effective investment decision-making. Specifically, a heavy reliance on cognitive mental shortcuts and prospect-related illusions (such as loss aversion and anchoring) significantly reduces the overall rationality and quality of investment choices. Comparatively, heuristics exert a substantially stronger negative influence on decision-making performance than prospect theory. The findings suggest that financial institutions and policymakers must design targeted advisor frameworks and behavioral financial education initiatives to minimize systematic biases and enhance market efficiency.
Nikhil Dommeti· International journal of bus...· 0 citations
