| Summary: | 碩士 === 嶺東科技大學 === 財務金融研究所 === 95 === Any investment strategy in stock markets with either single one of both stocks or futures will definitely face higher risk. How to reduce and control investment risk will be the critical issue. Whenever the risk is reduced, the profit probabilities will be naturally increased relatively. This thesis is combined with bilateral operation on both stocks and futures. The investment performance will be evaluated by means of various investment strategies. Also, the psychologically emotional response of investors in stock markets actually follows a set of system. They create a set of standard operational procedures to act as the tools for mapping investment strategies. There runs a well-known saying among the fund investing managers at the Wall Street and it says: “Cut Your Losses Short and Let Profit Run". The author sincerely hopes every investor can become a winner in stock markets.
This thesis is combined with GRS Model and VPRS Model to solve the problematic limitation and defects in traditional Rough Set Models. It is also integrated with Neuro-fuzzy Theory, Grey System Theory and K-means clustering to create the Prediction Model of DGVPRS to act as the investing strategies for stock screening selection.
The Prediction Model of DGVPRS proposed in this thesis includes 4 steps in the investigate strategies of the combinations in stocks and futures. Step 1 means the analysis for securities and markets. By means of this, we can evaluate the characteristics of risk and predicted return for all possible investing kits. Step 2 means the prevention against risk of fluctuating stock prices by using futures contracts. Step 3 means the adding risk values to effectively control risk with the maximum ROR (rates of returns) reached. Step 4 means the setting for stop-loss points and it is also vested with the Sharpe Indicators to evaluate the performance of investment portfolio.
This thesis is designed with the investing strategies by using numerous investment portfolios. No matter in stocks, stocks-n-TAIEX Future and stocks-n-MiNi TAIEX Future, both ROR and performance were better than the public market. Also, the investment portfolios of stock-n-TAIEX Future reached the best performance. Thus, the investment performance for this model is far better than the public market. No matter in the investment portfolios of stock-n-MiNi TAIEX Future or stock-n-TAIEX, there were 30% ROR reached on the average. In addition, this thesis is also designed with Variance-Covariance VaR available for readers to clearly see the maximum potential risk for the fund they invested.
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