Taiwan Mutual Fund Performance Evaluation and The Relevant Economic Variables Forecast–Application of Grey System Theory

• Main Authors: Pei-Cheng Chu, 朱倍誠
• Other Authors: Pao-Tung Hsu
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/45864931902643354761

碩士 === 樹德科技大學 === 經營管理研究所 === 99 === Mutual funds is entrusted to professional financial institutions, diversified investment in the financial markets, giving investors the opportunity to pursue a stable return. Mutual funds in Taiwan is influenced by the Taiwan Weighted Index and its related impact of economic variables, and also affects the performance of fund performance. This study is discussed from 2009 to 2010 per quarter relationship between performance of the Taiwan stock funds and economic data. Republic of China Securities Investment Trust and Consulting Association announced the opening of Taiwan Equity Fund Performance of the top five of object-oriented. Because mutual funds are a wide range of investment, and the complex factors that affect the fund performance. In this research, the gray gray system theory for analysis associated with the gray prediction. By their correlation and prediction of the characteristics of the impact of Fund Performance discusses the relevant economic variables. And use of better forecasting model accuracy: GM (1,1) model, least squares, exponential smoothing method for prediction and validation,in order to achieve the combination of theory and realities. Expected to provide investors in mutual fund selection and portfolio strategy development when the objective basis. Studies have shown that the results of gray relational analysis is: HSBC successful fund performance associated with the highest foreign exchange reserves, CSC Grammy fund performance and Fubon high growth fund performance are associated with the highest import value, Prudential New Century fund associated with the highest exchange rate, WF WF associated with the highest export value. In the forecasting model, GM (1,1) model and least squares model are higher than the 80% average accuracy, and these models are also useful for the efficient prediction models.