The Evaluation of Off-Shore Mutual Fund Risk and Performance-the Application of VaR Adjusted Sharpe Ratio

碩士 === 中原大學 === 企業管理研究所 === 90 === Sharpe Ratio is a well-know method to analyze the performance of mutual funds. As it is well know, the hypothesis of Sharpe Ratio is under the normal distribution of return, it will be bias when the return is non-normality. Besides, Sharpe Ratio uses the standard d...

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Main Authors: Yu-Jou Chang, 張有若
Other Authors: Jo-Hui Chen
Format: Others
Language:zh-TW
Published: 2002
Online Access:http://ndltd.ncl.edu.tw/handle/62725902757313665000
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spelling ndltd-TW-090CYCU51210492015-10-13T12:46:49Z http://ndltd.ncl.edu.tw/handle/62725902757313665000 The Evaluation of Off-Shore Mutual Fund Risk and Performance-the Application of VaR Adjusted Sharpe Ratio 全球共同基金群組風險與績效評估─以風險值修正夏普指標之應用 Yu-Jou Chang 張有若 碩士 中原大學 企業管理研究所 90 Sharpe Ratio is a well-know method to analyze the performance of mutual funds. As it is well know, the hypothesis of Sharpe Ratio is under the normal distribution of return, it will be bias when the return is non-normality. Besides, Sharpe Ratio uses the standard deviation for the risk evaluation. The standard deviation only measures the floating risks, but not the declining risk. Thus, we cannot acquire the real risk. This article proposes the Value at Risk (VaR) to replace the standard deviation and adds the benchmark of relative risk to improve the Sharpe Ratio’s bias and to enhance the sensitivity when the return is non-normality. Firstly, testing the normal distribution of return in the global balanced funds, bond funds, currency funds and fund of funds, we found that not all of the mutual funds were normal distribution. After diversified portfolio, the distribution of return tends to approach the normality. All of the mutual funds are leptokurtosis. Therefore, it represents that the returns of mutual fund are convergence and are heave-tailed relatives to normal distribution. Secondly, we use three main approaches, Historical Simulation approach, Delta Normal approach and Bootstrap, to evaluate the VaR of four kinds of mutual funds and compares with to see which one has better performance. Apparently that the result of the Delta-Normal method in the normal distribution of return is better than others, while the Historical Simulation method is adapted to the non-normality of returns. Using back testing and forward testing to verify the VaR is reasonable. Compared with the standard deviation and the VaR, we discover that standard deviation is less than VaR. The items of mutual fund portfolio will influence the risk, and the fund of funds decreases the risk indeed. The ranking is difference between traditional Sharpe Ratio (Sp) and adjusted Sharpe Ratio (V1), but the reason that makes this raking indistinct is because the return of mutual funds makes great difference. Therefore, the return dominants the ranking. The performance of Sharpe Ratio (V2, using the benchmark return rate to replace the risk-free rate of interest) is better than Sp and V1. Besides, the Sharpe (V3, using the Benchmark-Relative VaR to replace the standard deviation) is great different from other indexes and the variation of ranking is not consistent. Finally, in the forecast of indexes, the result of Spearman testing appears that the Sp, V1 and V2 have a forecasting effect, which the Classic Correlation Coefficient of V1 is higher than others. By using the VaR to replace the standard deviation will increase the feasible of forecasting, and thus it can be applied to mutual funds selection to forecast the future performance. Jo-Hui Chen 陳若暉 2002 學位論文 ; thesis 84 zh-TW
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language zh-TW
format Others
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description 碩士 === 中原大學 === 企業管理研究所 === 90 === Sharpe Ratio is a well-know method to analyze the performance of mutual funds. As it is well know, the hypothesis of Sharpe Ratio is under the normal distribution of return, it will be bias when the return is non-normality. Besides, Sharpe Ratio uses the standard deviation for the risk evaluation. The standard deviation only measures the floating risks, but not the declining risk. Thus, we cannot acquire the real risk. This article proposes the Value at Risk (VaR) to replace the standard deviation and adds the benchmark of relative risk to improve the Sharpe Ratio’s bias and to enhance the sensitivity when the return is non-normality. Firstly, testing the normal distribution of return in the global balanced funds, bond funds, currency funds and fund of funds, we found that not all of the mutual funds were normal distribution. After diversified portfolio, the distribution of return tends to approach the normality. All of the mutual funds are leptokurtosis. Therefore, it represents that the returns of mutual fund are convergence and are heave-tailed relatives to normal distribution. Secondly, we use three main approaches, Historical Simulation approach, Delta Normal approach and Bootstrap, to evaluate the VaR of four kinds of mutual funds and compares with to see which one has better performance. Apparently that the result of the Delta-Normal method in the normal distribution of return is better than others, while the Historical Simulation method is adapted to the non-normality of returns. Using back testing and forward testing to verify the VaR is reasonable. Compared with the standard deviation and the VaR, we discover that standard deviation is less than VaR. The items of mutual fund portfolio will influence the risk, and the fund of funds decreases the risk indeed. The ranking is difference between traditional Sharpe Ratio (Sp) and adjusted Sharpe Ratio (V1), but the reason that makes this raking indistinct is because the return of mutual funds makes great difference. Therefore, the return dominants the ranking. The performance of Sharpe Ratio (V2, using the benchmark return rate to replace the risk-free rate of interest) is better than Sp and V1. Besides, the Sharpe (V3, using the Benchmark-Relative VaR to replace the standard deviation) is great different from other indexes and the variation of ranking is not consistent. Finally, in the forecast of indexes, the result of Spearman testing appears that the Sp, V1 and V2 have a forecasting effect, which the Classic Correlation Coefficient of V1 is higher than others. By using the VaR to replace the standard deviation will increase the feasible of forecasting, and thus it can be applied to mutual funds selection to forecast the future performance.
author2 Jo-Hui Chen
author_facet Jo-Hui Chen
Yu-Jou Chang
張有若
author Yu-Jou Chang
張有若
spellingShingle Yu-Jou Chang
張有若
The Evaluation of Off-Shore Mutual Fund Risk and Performance-the Application of VaR Adjusted Sharpe Ratio
author_sort Yu-Jou Chang
title The Evaluation of Off-Shore Mutual Fund Risk and Performance-the Application of VaR Adjusted Sharpe Ratio
title_short The Evaluation of Off-Shore Mutual Fund Risk and Performance-the Application of VaR Adjusted Sharpe Ratio
title_full The Evaluation of Off-Shore Mutual Fund Risk and Performance-the Application of VaR Adjusted Sharpe Ratio
title_fullStr The Evaluation of Off-Shore Mutual Fund Risk and Performance-the Application of VaR Adjusted Sharpe Ratio
title_full_unstemmed The Evaluation of Off-Shore Mutual Fund Risk and Performance-the Application of VaR Adjusted Sharpe Ratio
title_sort evaluation of off-shore mutual fund risk and performance-the application of var adjusted sharpe ratio
publishDate 2002
url http://ndltd.ncl.edu.tw/handle/62725902757313665000
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