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Yayın Investment behaviour and risk perception: an analysis for Turkish market(PressAcademia, 2023-07-30) Teker, Dilek; Teker, Suat; Demirel, EsinPurpose- 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.Yayın Determinants of Bitcoin price movements(Suat Teker, 2024-07-30) Teker, Dilek; Teker, Suat; Demirel, EsinPurpose- Investors want to include Bitcoin in their portfolios due to its high returns. However, high returns also come with high risks. For this reason, the volatility prediction of Bitcoin prices is the focus of attention of investors. Because Bitcoin's volatility is used as an important input in portfolio selection and risk management. This means that the models to be used in predicting Bitcoin volatility increases the importance of performance. In this research; A comparative examination of the models applied for Bitcoin shows an effective performance in volatility prediction. It is very important for evaluation. The aim of this study is to model Bitcoin price returns and to examine future return predictions and return directions using historical Bitcoin prices. Methodology- Many models have been used in studies on financial instruments and price predictions. Models such as linear and nonlinear regression, Random Walk Model, GARCH and ARIMA fall into this category. Nonlinear econometric models such as ARCH and GARCH are used for financial time series with variable volatility. These models assume that the variance is not constant. In this study, first Bitcoin price returns for the period between January 2020 and December 2023 will be modeled with the GARCH model, and then the ARCH-GARCH models will be used for future prediction of returns for the period between January 2024 and June 2024. Finally, the actual values will be compared with the forecasted values. In other words, the primary aim of this study is to use the daily Bitcoin closing price between May 2020 and December 2023 to estimate the returns for the periods of 2024 and compare it with the actual returns. Findings- The analysis reveals that GARCH Model results showed that in the mean and variance equations, it is seen that all variables are except intercept of the mean equation significant according to the error level of 0.05. Namely, the reaction and persistence parameters are significant accourding to 0.05 in the variance equation. Both the coefficient of the reaction parameter and the coefficient of the persistent parameter are higher than zero (positive). Also, the coefficient of the reaction parameter plus the coefficient of the persistent parameter approximately equals 0.72. That is, it is lower than 1 and higher than zero (positive). The level of persistence is not too high. So, we do not think about non-stationary variance in the model. Reaction parameter’s coefficient is 0.13. And persistence parameter’s coefficient is 0.58. As we can see, persistent parameter is much higher than reaction parameter. That is, when there is a new shock that creates the persistent parameter, that shock will be in effect for a long time, it will not disappear immediately. That is, a significant part of the shock that occurs in one period flows into the next period. After determining the appropriate mean and variance models, a forecast is made using Automatic ARIMA forecasting for BITCOIN return forecasting. This forecast is made for the first five months of 2024, without adding the actual values of the first five months of 2024 to the data. The program ranks the most appropriate model. The program chose GARCH(3,3) as the most appropriate model in "bitcoin return prediction". Conclusion- The results of the test applied in the study can be summarized that the unit root test results showed that it was necessary to work with return series. GARCH(1,1) model results show when there is a new shock that creates the persistent parameter, that shock will be in effect for a long time, it will not disappear immediately. That is, a significant part of the shock that occurs in one period flows into the next period. According to GARCH automatic forecasting results, the best GARCH model that models Bitcoin return is the GARCH(3,3) model. According to these model results, although the slopes of the actual and forecasted return series move in the same direction, the model remains weak for forecasting. In future studies, it may be recommended to estimate Bitcoin returns with non-linear models.Yayın The investor behaviour, risk perception and expectations on cryptocurrency markets(Al-Kindi Center for Research and Development, 2023-12-15) Teker, Dilek; Teker, Suat; Demirel, EsinThe financial sector, which has sparked increasing organizational and scientific interest in recent years, plays a vital rolein the Turkish economy. After enduring multiple economic downturns, consumers have become more cautious when considering financial investments, making it challenging for financial institutions to formulate effective marketing strategies. This study aims to shed light on investor behavior in Tukish markets. The results of two surveys are examined: the first conducted in the final quarter of 2022, and the second in the first quarter of 2023. This article delves into various variables, including stress levels, portfolio holding times, investment choices, and attention to cryptocurrency markets. The methodology employs the Mann-Whitney U test, Cronbach's Alpha, Kolmogorov-Smirnov, and Shapiro-Wilk normality tests. The findings from the two surveys are compared. Based on the analysis results, it can be inferred that respondents' investment preferences and risk tolerance have evolved over time. The results demonstrate a spectrum of portfolio diversification tendencies.
