Regarding the empirical findings for Q7 and Q8 which measure respondents’ herding degree, the average degree of herding behavior is more equally spread. This advocates the assumption of PT in which most of The Impact of Loss Aversion Bias on Herding Behavior of Young Swedish Retail Investors individuals are bounded by loss aversion bias i.e., they find the pain of losing a specific amount of financial wealth much stronger than the joy of gaining the same amount (Kahneman & Tversky, 1979, 1992). Referring to the underlying assumptions of PT, the collected data show that while facing financial uncertainty and risk most of the respondents would rather choose the option that bring them an absolute or certain financial gain or enable them to avoid an absolute or certain financial loss. To expand, the results of the conducted questionnaire exhibits a strong level of financial loss aversion among the respondents similar to the loss aversion described by Kahneman and Tversky’s (1979, 1992) prospect theory. This strong level of loss aversion observed among the respondents is perfectly in line with and support findings from the existing empirical studies conducted by scholars such as Kahneman and Tversky (1979, 1992), Thaler and Johnson (1990), Kahneman et al., (1991), Thaler and Rabin (2001), and Beckman et al., (2011).
Most respondents score either 4 or 5 for Q5 and Q6 which specifically address their financial loss aversion in a hypothetical scenario in which they are exposed to a certain financial gain and loss. As the table and figures illustrate, the initial evaluation of collected data exhibit strong loss aversion observed among the respondents. Referring to table 2 and figures 3 and 4, they include average frequencies of respondents’ level of loss aversion and herding behavior. Finally, further interpretation and analysis of the results from the statistical testing methods is provided based on the authors’ both implementation of the main arguments, theories, and empirical findings within the theoretical framework, and consideration of other relevant aspects. These tables provide processed data that are further interpreted using measures of model fit, T-test, F-test, the critical value approach, and the P-value approach.
Second, the generated average values together with the other collected data are included in and processed by IBM SPSS using the multiple regression analysis tool, following the Descriptive Statistics, Model Summary, ANOVA, and Coefficients tables. This is followed by analysis and interpretation of the data represented in the table and figures. The purpose of this chapter is to evaluate and analyze the empirical findings from responses to the questionnaire through processing of raw data using IBM SPSS software, and interpretation of these data based on the main arguments, theories, and empirical findings included in the theoretical framework in chapter 3.įirst, table 2 and figures 2 and 3 exhibit an initial processing of raw data to generate average quantitative values for Q5 and Q6 that represent respondents’ degree of loss aversion, and Q7 and Q8 that cover respondents’ degree of herding behavior. Get Complete Project Material File(s) Now! » Analysis and Interpretation