Abstract
The inclination for optimizing returns by taking maximum risk has implications for both individual investors, as well as fund managers. For the former, risk tolerance will determine the appropriate composition of assets in a portfolio, which is optimal in terms of risk and returns relative to the needs of the individual. For fund managers, the inability to effectively determine investor risk tolerance may lead to homogeneity among investment funds. This paper investigates the extent to which financial attributes affect individual investor risk tolerance at the Nairobi Securities Exchange (NSE), Kenya. Financial attributes in this study were measured in two main aspects: individual monthly earnings income and home ownership. A sample of 500 Central Depository System (CDS) account holders was selected from a population of 932,510 investors at the NSE. Single independent variable cross tabulation on risk tolerance as well as paired cross tabulation on the dependent variable was performed. Analysis of variance was also used to determine how each group of the independent variable affects the dependent variable. Ordinal logistic regression model (OLRM) was employed to establish the contribution of financial attributes on risk tolerance. Single independent variable cross tabulation revealed that home owners were more risk tolerant than non owners. However, one way Analysis of Variance revealed that the variable had a P value of 0.710, hence not significantly affecting risk tolerance. The result of ANOVA on income was significant at a P value of 0.014 individual earnings, hence influences risk tolerance. Risk tolerance increased with earnings up to very high, except for those who earned more than 120,000 per month. OLMR fitted well with a significance level of 0.027 less than ?=5%, although it showed that home ownership is not a significant determinant at a P value of 0.761. For every single unit of home ownership for those with homes to those without, the expected log of odds increased by 0.060 as the threshold of risk tolerance increased, holding other factors constant. Income levels for those earning 90,000-120,000 per month showed a P value of 0.006, hence income was a major determinant of risk tolerance. For every single unit increase of investors earning 90,000-120,000, the expected ordered log of odds of risk tolerance reduced by 1.077 as the threshold of risk tolerance increased, holding other factors constant. Therefore fund managers, investment advisors and individual investors should consider the contribution of financial attributes in financial decision making.
Highlights
Risk tolerance levels of present and potential investors are rarely accorded sufficient attention in the investment decision making process
This paper investigates the extent to which financial attributes affect individual investor risk tolerance at the Nairobi Securities Exchange (NSE), Kenya
Anova results showed that home ownership is not a significant factor on its own, in influencing individual investor risk tolerance among various groups interviewed, recording significance at a P Value of 0.710 as shown in the table below
Summary
Risk tolerance levels of present and potential investors are rarely accorded sufficient attention in the investment decision making process. Kenyan fund managers and investment advisors may not be adequately assessing and taking into account the factors that influence the degree of willingness of an individual to accept risk, when constructing their investment portfolios, (NSE, 2008) They rarely consider the variables that inform the degree to which an investor is willing and able to accept the possibility of uncertain outcomes to an economic decision. Studies from the developed world such as Davey (2002), indicate that investment advisors have specific tools for evaluating ones’ risk tolerance on the onset of investment advice; their tool incorporates some aspects of the variables above Such tools promote efficiency in the financial market as envisaged in Kenya vision 2030 under the economic pillar of financial www.ccsenet.org/ass
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