BEHAVIOURAL BIASES, RISK TOLERANCE AND INVESTMENT DECISION BY LISTED COMPANIES IN NAIROBI SECURITY EXCHANGE, KENYA

Abstract

Investor often makes incorrect decisions often due to and not limited to inadequate technical expertise, overconfidence, herding, disposition effect and desire for faster returns. Researchers have however proved that due to the market inefficiencies, the standard finance models employed by market practitioners have failed to account for the market anomalies. There is a gap in relevant literature in developing markets particularly Kenya which is an emerging security market. The general objective of the study was to establish the effect of behavioral biases, risk tolerance, investment decisions of listed companies at Nairobi security exchange, Kenya. Specific objectives are; to establish the effect of herding bias on investment decisions; to analyze overconfidence biases that affect investor’s decisions; to examine regret biases that affect investments decisions; to evaluate conservatism biases that affect investment decisions; to assess mediating effect of risk tolerance on investment decision. The study period covered a 10 years from 2014 to 2023; the study adopted causal research design. This research design was suited because it enabled the researcher to collect data from different investors for the purpose of determining the existence and extent of a phenomenon as well as established the relationship between variables and the cause and effect of variables. The units of study were listed companies trading at Nairobi security exchange. Currently NSE has 62 listed companies. Secondary data collection schedule was utilized to collect data needed for the research. The study entailed descriptive and inferential statistics data and it was collected coded and analyzed using quantitative analysis method. The findings revealed a significant positive effect between herding bias and investment decisions (p = 0.0404 < 0.05, R² = 0.0215), indicating that herding behavior modestly explained 2.15% of variations in investment decisions. A significant positive relationship between overconfidence bias and investment decisions was also found (p = 0.000 < 0.05, R² = 0.1209), suggesting that overconfidence accounted for 12.09% of the variance in investment decisions. Similarly, a significant negative association between regret bias and investment decisions was established (p = 0.000 < 0.05, R² = 0.1832), implying that higher regret tendencies reduced the quality of investment decisions. Furthermore, conservatism bias had a significant positive influence on investment decisions (p = 0.000 < 0.05, R² = 0.2808). The introduction of risk tolerance as a mediating variable resulted in an R² change of 0.0788, with the overall model explaining 46.14% (R² = 0.4614) of the variance in investment decisions (p = 0.000 < 0.05), confirming the mediating role of risk tolerance in the relationship between behavioral biases and investment decisions. The study concluded that behavioral biases significantly influence investment decisions, and that risk tolerance plays a critical mediating role in this relationship. It recommends that investors at the NSE use average market returns as a benchmark to minimize herd behavior, base confidence on trading volume analysis, and view past investment regrets as learning opportunities rather than deterrents. Additionally, investors should rely on fundamental indicators such as net book value relative to market value when making investment decisions. The study suggests further research on diverse investor categories and other forms of behavioral biases to deepen the understanding of investor psychology in emerging markets.