INVESTMENT BEHAVIOUR AND RISK PERCEPTION: AN ANALYSIS FOR TURKISH MARKET
Bibliographic record
Abstract
Purpose- The cognitive comprehension of financial indicators, risk aversion, risk perception, and investment behavior is defined as financial literacy. It's possible that a variety of characteristics, such as gender, age, income level, social standing, education, etc., will affect an investor's behavior. The purpose of this study is to highlight the behavior of investors in Turkish capital markets. The analysis is done on the results of two surveys, the first conducted in the fourth quarter of 2022 and the second in the first quarter of 2023. Methodology- This study's objective is to highlight investor behavior and risk perception in Turkish financial markets. In the most recent two consecutive quarters, the results of two surveys are analyzed and compared. Three sections comprise the surveys. A demographic question is asked in the first section. The second section asks questions concerning investment behavior, signs of financial stress, and confidence in regard to one's financial literacy. The final aspect contributes to the analysis of what people think of the Bitcoin market. In this study, Graphic analysis, Cronbach Alpha, Normality, and Mann-Whitney U tests are performed, respectively. First, the graphical analysis of the selected questions is made. Based on these graphs, the similarities and differences between the surveys are shown. Second, The reliability test is applied to the selected questions for the statistical modeling of the analysis. This test is determined as the Cronbach Alpha test. Third, the Normality test is applied to reveal which test to use in the next step. Two different tests are used for this analysis. These are the Kolmogorov-Smirnov and Shapiro-Wilk tests. Fourth, the Mann-Whitney U test is applied. At this stage, firstly, Mann-Whitney U and Wilcoxon W test statistics are examined. The ranks are calculated for each variable. Finally, the Mann-Whitney U test is applied, and the results are interpreted. Fifth, The results of the two surveys are compared. Findings- The findings show both similarities and differences among numerous variables. For instance, holding time is defined as the amount of time an investor holds an investment or as the time between purchasing it and selling it. Investors' risk aversion and financial literacy both influence the holding period. Riskier assets force investors to adjust their purchase or sell actions dynamically. The results show various portfolio diversification behaviours. While men prefer to start with foreign currency investments, women are more interested in making gold investments. Also, middle-aged investors invest more in cryptocurrencies and take more risks than younger investors. Conclusion- based upon the analysis, findings it may be concluded that respondents do differ in their investment preferences and risk-taking over the years. The findings show various portfolio diversification behaviors. While men prefer to invest in foreign currency, women are more interested in purchasing gold. Keywords: Investor behavior, risk perception, cryptocurrency market, Bitcoin, Mann-Whitney U test. JEL Codes: G1, G4, C4
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".