By using Taiwan index futures (TX), Taiwan 50 index futures (T5F), and Taiwan 50 index futures’ component stocks as examples in daily, weekly, and monthly from January 2009 to December 2017, this thesis discuss the performance of moving average considering the transaction costs, and try to establish a short-term, mid-term, and long-term exchanging strategies separately.
The various frequency samples are adopted in the following rules: using 5 days (MA5), 20 days (MA20), and 60 days (MA60) as a horizon to calculate daily moving average; using 4 weeks (MA4), 24 weeks (MA24), and 48 weeks (MA48) as a horizon to compute weekly moving average; and using 12 month (MA12), 24 months (MA24), and 60 months (MA60) as a horizon to calculate the monthly moving average. This thesis uses Grey System Theory to improve the investment performance of moving averages via Gray forecasting Model GM (1.1). This thesis focuses on the analysis of remuneration variances which are under the Band Trade Strategy (BTS) before and after the transparent treatment. At the same time, this study includes the analysis of remuneration variances on the Band Trade Strategy before-and-after transparent treatment and Buy and Hold Strategy. This study also includes the differentiations of before-and-after transparent treatment of Band Trade Strategy, comparing the differences after executing the difference method.
The study results show that, the short-term, mid-term, and long-term band trade strategies cannot beat the Buy and Hold strategy. Even though we improve the Band Trade Strategy through the Gray forecasting Model or differentiations, it is still not beat the Buy and Hold Strategy. Also, the Band Trade Strategy which through the processes of transparent treatment still cannot surpass the strategy which are not under the treatment or even under the differences methods. Hence, stock investors could not make more profits by the Band Trade Strategy structured by moving averages, and the performances of Band Trade Strategy cannot transcend the Buy and Hold Strategy in the Taiwan stock market.
The trend of Taiwan stock market was under the strong bull market after 2009. In this period, Taiwan’s stock markets upward from 4,000 points to 10,000 points, and the Band Trade Strategy bears more transaction costs than Buy and Hold Strategy. After the economic recession in 2008, the efficiency of Taiwan’s stock market increased. Investors had difficulties to earn excess return using technical analysis indicators. Therefore, the results show that the weak-form efficiency market hypothesis in Taiwan’s stock market cannot be rejected

In this paper, the principle of the interaction that the four kinds of representations in the Chinese lunar year of the Chinese Astrology – ZI Wei Dou Shu was applied. Constructed the returns model of the Taiwan stock market and based on the dummy variable as the Chinese lunar year. Examine the impact of the systemic risks in the different Chinese lunar year on the returns of the Taiwan stock market through GJR-GARCH (1,1) -M statistical model. The empirical results show that the returns of the Taiwan stock market exists the decade cyclical fluctuation and there are significant impacts on the sub-index and its component stocks through the time-varying systematic risk. In line with our research hypothesis that the Chinese Astrology – ZI Wei Dou Shu has predictive function on the returns of the Taiwan stock market.

This study focuses on the relations between blood types, personalities, investment behaviors and disposition effect of “Xiaozi” investors. The research method utilized in this study is “Convenience Sampling”, which adopts online questionnaire method, and the research subject is “Xiaozi” investors in Taiwan. The blood types are classified into type A, B, AB and O; the personalities are classified into six categories by using “Exploratory factor analysis” and “Cluster analysis”. In addition, this study employs statistical software “SPSS” as main statistical tool and uses “descriptive statistics”, “Exploratory factor analysis”, “Cluster analysis”, Pearson’s chi-squared test”, “Analysis of Variance ANOVA Test”, and “Scheffé Test” to testify and analyze the research hypothesis in this study.
The research has found the following results. First, there is no evident relations between the blood types and personalities of “Xiaozi” investors, so the blood types will not affect investment personalities. Second, the investment behaviors and “Disposition Effect” will be displayed in varied performances due to Xiaozi investors’ blood types. Thus, investors whose blood type are type AB will have more distinguishable performance in their investment behaviors and “Disposition Effect”. Finally, this study shows that a relation between investment personality, investment behavior and “Disposition Effect” exists. The result of aggressive investors on investor behaviors and “Disposition Effect” is more distinguishable than “Safety First Investor”, “Rational Investor”, “Gambler Investor”, “Gloomy Investor and “Aggressive Investor”