避險基金指數之風險值探討__臺灣人文及社會科學引文索引資料庫

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題名：	避險基金指數之風險值探討
書刊名：	商管科技季刊
作者：	黃聖志／蘇欣玫／杜國賓
作者(外文)：	Huang, Sheng-shih／Su, Hsin-mei／Tu, Kuo-pin
出版日期：	2008
卷期：	9:3
頁次：	頁277-299
主題關鍵詞：	風險值；RiskMetrics；GARCH；VaR
原始連結：	連回原系統網址
相關次數：	被引用次數:期刊(2) 博士論文(0) 專書(0) 專書論文(0) 排除自我引用:2 共同引用:0 點閱:43

　　本文採用RiskMetrics 模型與GARCH 模型及馬可夫轉換模型估算避險基金指數之風險值，並進一步以RiskMetrics 模型與GARCH 模型及馬可夫轉換模型所估出之風險值進行比較，用以探討何種模型有較佳的預測能力及績效，使投資大眾於面臨風險時，能正確的評估與控管，以避免承擔超過預期的損失。實證結果如下：1、由回溯測試的結果可知， RiskMetrics 模型與GARCH 模型及馬可夫轉換模型都能有效的估計風險值，風險控管能力均有一定的水準，其中又以馬可夫轉換模型在信心水準99%表現最佳。2、就資金使用效率的角度觀察，馬可夫轉換模型的表現為三模型中最優異的，推斷其原因為馬可夫模型採用馬可夫鍊做為狀態轉換的機制，相較於RískMetrics 模型與GARCH 模型，更能夠考慮資料序列前後期狀態與相關訊息，進而對報酬分配有較精確的掌握。3、RiskMetrics 模型與GARCH 模型及馬可夫轉換模型進行回溯測驗及資金使用效率測驗時發現，穿透次數與均方根誤差存在有抵換關係。

以文找文

　　This paper investigates the Value-at-Risk (VaR) of returns on hedge fund index using RiskMetrics model, GARCH model and Markov Switching Model. Furthermore, we compare with Valu-at-Risk (VaR) by RiskMetrics model, GARCH model and Markov Switching Model. The purpose is to find out which of three models has better prediction and performance for investors to evaluate and to take control in order to avoid unexpected lost while minimizing damage. The result of this study shows the following: (l)The back-test shows that the RiskMetrics model, the GARCH model and the Markov Switching Model can estimate Valu-at-Risk (VaR) effectively which proves that the ability to control risk is at good standard. Besides, the empirical results show Markov Switching Model can capture the distribution better than others in 99% confidence level under the back-test. (2)According to the efficiency of capital usage, the Markov Switching Model performs better than either the GARCH model or the RiskMetrics model. We infer that the Markov Switching Model can capture the distribution well resulting from it adopts the transformation mechanism of Markov chain. The Markov chain contains more relative information of time serial data than other models do. (3)All three models have the trade off between the back-test and efficiency of capital usage effectively.

以文找文

期刊論文
1.	Giot, Pierre、Laurent, Sébastien(2003)。Value-at-Risk for Long and Short Trading Positions。Journal of Applied Econometrics，18(6)，641-663。
2.	Huang, Yu-Chuan、Lin, Bor-jing(2004)。Value-at-Risk Analysis for Taiwan Stock Index Futures: Fat Tails and Conditional Asymmetries in Return Innovations。Review of Quantitative Finance and Accounting，22(2)，79-95。
3.	Chiu, C. L.、Lee, M. C.、Hung, J. C.(2005)。Estimation of Value-at-Risk under Jump Dynamics and Asymmetric Information。Applied Financial Economics，15(15)，1095-1106。
4.	Giot, P.、Laurent, S.(2004)。Modeling Daily Value-at-Risk using Realized Volatility and ARCH type Models。Journal of Empirical Finance，11，379-398。
5.	Alizadeh, A.、Nomikos, N.(2004)。A Markov Regime Switching Approach for Hedging Stock Indices。The Journal of Futures Markets，24(7)，649-674。
6.	Brooks, C.、Persand, G.(2002)。Model Choice and Value-at-Risk Performance。Financial Analysts Journal，58(5)，87-97。
7.	Filardo, A. J.(1994)。Business-cycle phases and their transitional dynamics。Journal of Business and Economic Statistics，12，299-308。
8.	Engle, R. F.(1982)。Autoregressive Conditional Heteroske- dasticity with Estimates of the Variance of U.K. Inflation。Econometrica，50(4)，987-1008。
9.	Hansen, P. R.、Lunde, A.(2005)。A forecast comparison of volatility models: Does anything beat a GARCH(1,1)?。Journal of Applied Econometrics，20(7)，873-889。
10.	Jorion, P.(1996)。Risk 2: measuring the risk in value at risk。Financial Analysts Journal，52(6)，47-56。
11.	Alexander, C. O.、Leigh, C. T.(1997)。On the Covariance Matrices Used in Value at Risk Models。Journal of Derivatives，4(3)，50-62。
12.	Hendricks, Darryll(1996)。Evaluation of Value-at-Risk Models Using Historical Data。Federal Reserve Bank of New York Economic Policy Review，2(1)，39-69。
13.	Campbell, R.、Huisman, R.、Koedijk, K.(2001)。Optimal Portfolio Selection in a Value-at-Risk Framework。Journal of Banking and Finance，25(9)，1789-1804。
14.	Bollerslev, Tim(1986)。Generalized Autoregressive Conditional Heteroskedasticity。Journal of Econometrics，31(3)，307-327。
15.	Hamilton, James D.(1989)。A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle。Econometrica: Journal of the Econometric Society，57(2)，357-384。
16.	Chen, Songxi、Tang, Chengyong(2005)。Nonparametric inference of value-at-risk for dependent financial returns。Journal of Financial Econometrics，3(2)，227-255。
17.	Kupiec, Paul H.(1995)。Techniques for Verifying the Accuracy of Risk Measurement Models。Journal of Derivatives，3(2)，73-84。
18.	McNeil, A. J.、Frey, R.(2000)。Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach。Journal of Empirical Finance，7(3/4)=56，271-300。
19.	洪瑞成、劉洪鈞(2006)。厚尾 GARCH模型之波動性預測績效。計量管理期刊，3(2)，161-174。延伸查詢
20.	Alexander, C.(2005)。The present and future of financial risk management。Journal of Financial Econometrics，3(1)，3-25。
21.	Burns, P.(2002)。The quality of Value at Risk via univariate GARCH。Burns Statistics，October，1-19。
22.	Durland, J. M.,、McCurdy, T. H.(1994)。Duration-dependent transitions in a Markov model of U.S.GNP growth。Journal of Business and Economic Statistics，12，279-288。
23.	Fong, W. M.、See, K. H.(2002)。A markov switching model of the conditional volatility of crude oil futures prices。Energy Economics，24，71-95。
24.	Morgan, J. P.(1996)。RiskMetrics Technical Document.Fourth Edition。
25.	Vlaar, P. J. G.(2000)。Value at Risk for Dutch bond portfolios。Journal of Banking &Finance，24，1131-1154。

研究報告
1.	Aussenegg, W.,、Pichler, S.(1997)。Empirical evaluation of simple model to calculate Value-at-Risk of fixed income instrument。Vienna University of Technology。
2.	Peersman, G.,、Smets, F.(2001)。Are the effects of monetary policy in the Euro area greater in recessions than in booms?。

圖書
1.	Jorion, Philippe(2000)。Value at Risk: The New Benchmark for Managing Financial Risk。Irvine：University of California。

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