Abstract
Determining the risk-taking attitudes of individuals and the variables that influence investment decisions is crucial for financial investors and stakeholders interested in investment decisions. Therefore, the fundamental focus of behavioral finance is to identify why and how investors are influenced. Among these factors, individuals' demographic and socio-economic characteristics are prominent. The aim of this study is to determine the impact of these factors on risk-taking attitudes and investment preferences. For this purpose, individual investors selected through a convenient and purposive sample were asked demographic and socio-economic questions, as well as questions about their risk-taking attitudes and investment preferences. The risk-taking attitudes variable was defined as risk-loving, risk-neutral, and risk-averse, while investment options were specified as interest, gold, and stocks. Analyses were conducted using the responses of 294 individual investors obtained through an online survey tool. Firstly, descriptive statistical analysis was performed to outline the general structure of the dataset. Then, chi-square analysis was conducted to determine the relationship between demographic and socio-economic characteristics and risk-taking attitudes and investment options. Finally, Classification and Regression Tree (CART) analyses were performed to determine the impact of these characteristics on risk-taking and investment preferences. The results of relational and CART analyses revealed that individuals' risk-taking attitudes are influenced by different demographic and socio-economic characteristics, affecting their investment choices. In other words, individuals with a tendency to take risks were found to prefer low-risk investments. Therefore, evaluating these two phenomena differently will lead to more optimal investment decisions. Moreover, it is believed that techniques based on data mining, such as the CART method, can provide more meaningful results compared to traditional statistical analyses, given the increased availability of data on individual investors in today's world.
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