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研究生:許名秀
研究生(外文):Mimg-Hsiu Hsu
論文名稱:期貨最適避險比率之EWMA族模型比較
論文名稱(外文):Optimal Hedge Ratios Estimate :Comparison Among Alternative EWMA Method
指導教授:林楚雄林楚雄引用關係
指導教授(外文):Chu-Hsiung Lin
學位類別:碩士
校院名稱:國立高雄第一科技大學
系所名稱:風險管理與保險所
學門:商業及管理學門
學類:風險管理學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:66
中文關鍵詞:指數加權移動平均冪指數加權移動平均誤差修正指數加權移動平均絕對限制最小平方估計式限制最小平方估計式最適避險比率
外文關鍵詞:A-RLSRLSOptimal hedge ratioBias-corrected EWMAPower EWMA EWMA
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本文的應用限制最小平方估計模型(RLS)、絕對限制制小平方估計模型(A-RLS)、在動態策略下易估計的EWMA模型、考量高峰厚尾分配的Power EWMA模型及保有EWMA與Power EWMA兩模型優點的Bias-Corrected EWMA等模型來對TAIFEX台灣加權股價指數期貨和MSCI摩根台股指數期貨進行最適避險比率的估計,期望能找出具有較高準確性的估計方法,有效的提升投資者的避險績效。
本研究除了使用動態避險的策略方式以及樣本外的觀點來進行估計外,另應用三種分別為避險後投資組合變異數、樣本外最適避險比率變異數及平均數不同避險績效衡量之觀點。實證結果顯示 (一) 在樣本期間下,Power EWMA模型之避險績效最佳;(二) 各模型之不同衰退因子設定對各指數期貨的避險績效並無一致性影響。
This study applies the restricted least squares estimator(RLS),the absolute restricted least squares estimator(A-RLS), and Bias-Corrected EWMA model to estimate optimal hedge ratios for stock index futures. Using for stock index futures ,we compare the optimal hedge ratios and hedge performances with EWMA mode which under normal distribution and Power EWMA model which considers the distribution of assets return is leptokutic. Empirical result shows that the (1) Two stock index futures under any of models, using the hedge performances we can find Power EWMA model is the best. (2) There is no consistency between the hedge performances and various decay factors.
目 錄
中文摘要---------------------------------------------- i
英文摘要---------------------------------------------- ii
誌謝-------------------------------------------------- iii
目錄-------------------------------------------------- iv
表目錄------------------------------------------------ vi
圖目錄------------------------------------------------ vii
第一章 緒論
第一節 研究動機 ------------------------------------ 1
第二節 研究目的與內容------------------------------- 4
第三節 研究架構------------------------------------- 6
第二章 文獻回顧------------------------------------- 8
第三章 研究方法
第一節 動態避險策略--------------------------------- 18
第二節 最適避險比率--------------------------------- 20
第三節 EWMA估計式----------------------------------- 22
第四節 Power EWMA模型------------------------------- 23
第五節 Bias-Corrected EWMA模型---------------------- 27
第六節 限制最小平方估計模型------------------------- 29
第七節 避險績效之衡量------------------------------- 31
第四章 實證研究
第一節 資料來源------------------------------------- 33
第二節 實證結果與分析------------------------------- 36
第五章 結論----------------------------------------- 49
參考文獻---------------------------------------------- 50
參考文獻
1.江佩蓁,2005,高狹峰分配下外幣期貨最適避險比率,國立高雄第一科技大學,碩士論文。
2.朱國誌,2007,台幣兌美元匯率風險之避險策略:Power EWMA 法,國立高雄第一科技大學,碩士論文。
3.沈育展,洪瑞成,邱建良。李命志,2004,“日經225 指數期貨之避險績效與最適避險策略之探討”,輔仁管理評論,第十一卷,第一期,頁153-180。
4.李秋貞,2004,高狹峰分配與最適避險比率,國立高雄第一科技大學,碩士論文。
5.邱建良,魏志良,吳佩珊,邱哲修,2004,“TAIFEX 與MSCI 台股指數期貨與貨直接避險策略之研究”,商管科技季刊,第五卷,第二期,頁169-184。
6.吳方聖,2003,運用條件Power EWMA估計式衡量風險值之績效研究,東吳大學,碩士論文。
7.陳若鈺,1999,風險值的衡量與驗證:以台灣股匯市場之實證,國立台灣大學,碩士論文。
8.陳慧吟,2004,以各種不同計量模型探討指數期貨之最適避險比率,逢甲大學,碩士論文。
9.張育達,1991,期貨契約最適避險策略之研究:以股價指數期貨為例,國立台灣大學,碩士論文。
10.黃一雄,2004,股價指數期貨避險之研究_應用Bi-GARCH 與Bi-EGARCH 模型,國立台北大學,碩士論文。
11.溫曜誌,1997,以SIMEX摩根台股指數期貨規避台灣股價指數風險之研究,國立政治大學,碩士論文。
12.劉美纓,2005,“銀行投資組合風險值估計-保守性、準確性及效率性”,財務金融學刊,第十三卷,第二期,頁97-128。
13.謝美華,2005,外匯期貨最適避險比率之估計-EWMA 法,國立高雄第一科技大學,碩士論文。
14.蘇榮斌、劉洪鈞、林東虨,2007,“限制最小平方法波動性預測能力之評價”,真理財經學報,第十七期,頁65-90。
15.羅悅芬,2007,時變避險比率之避險效能-新加坡摩根台股與TAIFEX 台股指數期貨之驗證,國立高雄第一科技大學,碩士論文。
16.Alexander, C.O. and Leigh, C.T., 1997, “On the Covariance Matrices Used in Value at Risk Models”, Journal of Derivatives, vol. 4, pp. 50-62.
17.Baillie, R. and DeGennaro , R., 1990, “Stock Returns and Volatility”, Journal of Financial and Quantitative Analysis, vol. 25, pp.203-214.
18.Baillie, R. T. and Myers, R. J., 1991, “Bivariate GARCH Estimation of Optimal Commodity Futures Hedge”, Journal of Applied Econometrics, vol. 6,pp.109-124.
19.Benet, B. A., 1992, “Hedging Period Length and Ex-ante Futures Hedging Effectiveness: the case of Foreign Exchange Risk Cross Hedges”, Journal of Futures Markets, vol. 2, pp.163-175.
20.Bollerslev, T., 1986, “Generalized Autoregressive Conditional Heteroskedasticity”, Journal of Econometrics, vol. 31, pp.307-327.
21.Bollerslev, T., 1986, “Generalized Autoregressive Conditional Heteroskedasticity”, Journal of Econometrics, vol. 31, pp.307-327.
22.Bollerslev, T. 1990, “Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Approach”, Review of Economics and Statistics, vol. 72, pp. 498-505.
23.Bollerslev, T., Engle, R.F., and Wooldridge, J. M., 1988, “A Capital Asset Pricing Model with Time-varying Covariances”, Journal of Political Economy, vol. 96, pp.116-131.
24.Bollerslev, T., Chou, R., and Kroner, K., 1992, “ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence”, Journal of Econometrics, vol. 52, pp.5-59.
25.Boudoukh, J., Richardson, M. and Whitelaw, R., 1997, “Investigation of a Class of Volatility Estimators”, Journal of Derivatives, vol. 4, pp.63-71.
26.Brooks, C. and Chong, J., 2001, “The Cross-currency Hedging Performance of Implied Versus Statistical Forecasting Models”, Journal of Futures Markets, vol.21, pp.1043-1069.
27.Brooks, C., Henry, O. T. and Persand, G., 2002, “The Effect of Asymmetries on Optimal Hedge Ratio”, Journal of Business, vol.75, pp.343-352.
28.Choudhry, T., 2004, “The Hedging Effectiveness of Constant and Time-varying Hedge Ratios Using Three Pacific Basin Stock Futures”, International Review of Economics and Finance, vol. 13, pp.371-385.
29.Ederington, L. H., 1979, “The Hedging Performance of the New Futures Markets”, Journal of Finance, vol. 34, pp.157-170.
30.Engle, R. F., Kroner, K. F., 1995, “Multivariate simultaneous generalized ARCH”, Econometric Theory, vol. 11, pp.122-150.
31.Figlewski, S., 1997, “Forecasting Volatility”, Financial Markets, Institutions and Instruments, vol. 6, pp.1-88.
32.Gray, R. W. and Rutledge, D. J. S. 1971, “The Economics of Commodity Futures Markets: A Survey”, Review of Marketing and Agricultural Economics, vol.39, pp. 57-108.
33.Guermat, C. and Harris, R. D. F., 2002, “Robust Conditional Variance Estimation and Value at Risk”, Journal of Risk, vol. 4, pp.25-41.
34.Harris, R. D. F., and Shen, J., 2003, “Robust Estimation of the Optimal Hedge Ratio”, Journal of Futures Markets, vol. 23, pp.799-816
35.Harris, R. D. F., and Shen, J., 2004, “Estimation of VaR with Bias-corrected Forecasts of Conditional Volatility”, Journal of Derivatives, vol. 11, pp.10-20.
36.Herbst, A. F., Swanson, P. E., and Caples, S. C., 1992, “A Redetermination of Hedging Strategies Using Foreign Currency Futures Contracts and Forward Markets”, Journal of Futures Markets, vol. 12, pp.93-104.
37.Hill, J. and Schneeweis, T., 1981, “A Note on the Hedging Effectiveness of Foreign Currency Futures”, The Journal of Futures Markets, vol. 1, pp.659-664.
38.Huber, P., 1981, Robust statistics, Wiley, New York.
39.Johnson, L. L., 1960, “The Theory of Hedging and Speculation in Commodity Futures”, Review of Economic Studies, vol. 27, pp. 139-151.
40.Jorion, P., 2000, Value at Risk, McGraw-Hill.
41.Koutmos, G. and Pericli, A. 1999, “Hedging GNMA Mortage-Backed Securities with T-Note Futures: Dynamic Versus Static Hedging”, Real Estate Economics,vol.27,pp. 335-336
42.Kroner, K. F. and Sultan, J. 1993, “Time Varying Distribution and Dynamic Hedging with Foreign Currency Futures”, Journal of Financial and Quantitative Analysis, vol. 28, pp. 535-551.
43.Kuen, T. Y. and Hoong, T. S., 1992, “Forecasting Volatility in the Singapore Stock Market”, Asia Pacific Journal of Management, vol. 9, pp.1-13.
44.Lien, D and Tse ,Y.K.,1999,“Fractional cointegration and futures hedging.”, Journal of Futures Markets. v19. 457-474.
45.Lopze, J., 2001, “Evaluating the Predictive Accuracy of Volatility Models.”, Journal of Forecasting, vol. 20, pp. 87-109.
46.Markowitz, H., 1952, “Portfolio Selection”, Journal of Finance, vol. 7, pp.77-91.
47.Meneu, V. and Torro, H., 2003, “Asymmetric Covariance in Spot-Futures Markets”, Journal of Futures Markets, vol.23, pp.1019-1046.
48.Morgan, J. P., 1996, Riskmetrics Technical Document, 4th ed, J. P. Morgan, New York.
49.Myers, R. J., 1991, “Estimating Time-varying Optimal Hedge Ratio on Futures Markets”, Journal of Futures Markets, vol. 11, pp.39-53.
50.Nelson, D., and Foster D., 1994, “Asymptotic Filtering Theory for Univariate Arch Models”, Economtrica, vol.62, pp. 1-41.
51.Park, T. H., and Switzer, L. N., 1995, “Bivariate GARCH Estimation of the Optimal Hedge Ratio for Stock Index Futures: A note”, Journal of Futures Markets, vol. 15, pp. 61-67.
52.Poomimars, P., Cadle, J. and Theobald, M., 2003, “Futures Hedging Using Dynamic Models of the Variance/Covariance Structure”, Journal of Futures Markets, vol. 23, pp.241-260.
53.Stein, J. L., 1961, “The Simultaneous Determination of Spot and Futures Prices”, American Economic Review, vol. 51, pp.1012-1025.
54.Taylor, J., 1999, “Evaluating Volatility and Interval Forecasts”, Journal of Forecasting, vol. 18, pp.111-128.
55.Theil, H., 1966, Applied economic forecasting, North Holland, Amsterdam.
56.Working, H., 1953, “Futures Trading and Hedging”, The American Economic Review, vol. 43, pp.314-343.
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