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碩士 === 國立成功大學 === 工業與資訊管理學系碩博士班 === 93 === “High return accompanies higher risk” is the constant law of investment. Compared to risk-free interest rate, other tools of personal finance are more risky in despite of higher expected return on investment. Sensitivity, volatility and probability are oft...
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ndltd-TW-093NCKU50410172017-05-28T04:39:12Z http://ndltd.ncl.edu.tw/handle/20546781044296503574 none 應用風險值於共同基金投資風險與績效指標之研究 Yong-Da Chen 陳勇達 碩士 國立成功大學 工業與資訊管理學系碩博士班 93 “High return accompanies higher risk” is the constant law of investment. Compared to risk-free interest rate, other tools of personal finance are more risky in despite of higher expected return on investment. Sensitivity, volatility and probability are often used to interpret the risk of investment in the past. These indicators, however, cannot effectively meet the needs of investors who only care the risk of loss. Value-at-Risk(VaR)has the advantages of both dynamic management of risk and risk quantification. It also gives a good description of downside risk of the investment, which traditional indicators cannot achieve. In recent years, securities investment trust funds(or mutual funds)become one of the most popular tools for personal finance due to the characteristics of professional investment and dispersing the investment risk while statistical data shows that more than half yearly return rate of funds is lower than the risk-free rate of interest. As a result, the key to make more profit is to pick out investments with great potential profit. In order to develop an effective index of investment performance, a VaR method is developed to improve traditional indicators under the assumption of normal-distribution bias. Its effectiveness is verified with the real market data. After sample test of normal-distribution, Monte Carlo Simulation Approach and Historical Simulation Approach are chosen as the VaR models in this research. According to empirical tests, Monte Carlo Simulation can make VaR more close to the real risk of investment by fine-tuning the estimate of VaR, and it is more flexible than Historical Simulation Approach in application. However, the most unfavorable is that its cost of time, manpower and material resources is times to those of the other VaR models. With regard to the application of performance indicators, the concept of VaRRAF can provide information about risk as investment loss exceeds the expectation. In addition, this research finds that the average return rate of weighted TSE index is a dynamic indicator and hence more suitable to be used as an investment benchmark than risk-free interest rate. When the investment market is in bull in the long run, VaB is superior to VaR for reference. Generally speaking, VaR is certainly an excellent risk indicator to measure the amount of loss if its model bias is controlled in a tolerant range. Chang-Chun Tsai 蔡長鈞 2005 學位論文 ; thesis 81 zh-TW |
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碩士 === 國立成功大學 === 工業與資訊管理學系碩博士班 === 93 === “High return accompanies higher risk” is the constant law of investment. Compared to risk-free interest rate, other tools of personal finance are more risky in despite of higher expected return on investment. Sensitivity, volatility and probability are often used to interpret the risk of investment in the past. These indicators, however, cannot effectively meet the needs of investors who only care the risk of loss. Value-at-Risk(VaR)has the advantages of both dynamic management of risk and risk quantification. It also gives a good description of downside risk of the investment, which traditional indicators cannot achieve.
In recent years, securities investment trust funds(or mutual funds)become one of the most popular tools for personal finance due to the characteristics of professional investment and dispersing the investment risk while statistical data shows that more than half yearly return rate of funds is lower than the risk-free rate of interest. As a result, the key to make more profit is to pick out investments with great potential profit. In order to develop an effective index of investment performance, a VaR method is developed to improve traditional indicators under the assumption of normal-distribution bias. Its effectiveness is verified with the real market data.
After sample test of normal-distribution, Monte Carlo Simulation Approach and Historical Simulation Approach are chosen as the VaR models in this research. According to empirical tests, Monte Carlo Simulation can make VaR more close to the real risk of investment by fine-tuning the estimate of VaR, and it is more flexible than Historical Simulation Approach in application. However, the most unfavorable is that its cost of time, manpower and material resources is times to those of the other VaR models. With regard to the application of performance indicators, the concept of VaRRAF can provide information about risk as investment loss exceeds the expectation. In addition, this research finds that the average return rate of weighted TSE index is a dynamic indicator and hence more suitable to be used as an investment benchmark than risk-free interest rate. When the investment market is in bull in the long run, VaB is superior to VaR for reference. Generally speaking, VaR is certainly an excellent risk indicator to measure the amount of loss if its model bias is controlled in a tolerant range.
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Chang-Chun Tsai |
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Chang-Chun Tsai Yong-Da Chen 陳勇達 |
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Yong-Da Chen 陳勇達 |
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Yong-Da Chen 陳勇達 none |
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Yong-Da Chen |
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2005 |
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http://ndltd.ncl.edu.tw/handle/20546781044296503574 |
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