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研究生:孫國城
研究生(外文):Kuo-cheng Sun
論文名稱:風險值的估計與驗證-波羅的海指數為例
論文名稱(外文):THE EVALUATION AND VERIFICATION OF VALUE AT RISK--EMPIRICAL STUDY ON BALTIC DRY INDEX PORTFOLIO
指導教授:張簡彰程張簡彰程引用關係
指導教授(外文):Chang-cheng Chang-chien
學位類別:碩士
校院名稱:南華大學
系所名稱:財務金融學系財務管理碩士班
學門:商業及管理學門
學類:財務金融學類
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:39
中文關鍵詞:波羅的海指數風險值風險值檢定測試
外文關鍵詞:VaR Verification TestValue at RiskBaltic Dry Index
相關次數:
  • 被引用被引用:4
  • 點閱點閱:126
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
  本文比較三種估計風險值的模型(常態分配、T分配和Cornish-Fisher展開式),並考慮變異數-共變異數中三種不同的波動估計(SMA、EWMA和GARCH(1,1)),應用分析在4種信賴水準(99.5%, 99%, 95%,90%)與3種評估原則(保守性、正確性以及效率性)下的績效,提供使用者選擇較佳的風險值預測模型。本研究以倫敦波羅的海交易所(Baltic Exchange in London)中的波羅的海乾散貨指數(BDI)、波羅的海海岬型(Baltic Capesize Index,BCI)和波羅的海巴拿馬極限型(Baltic Panamax Index,BPI)等3種指數為研究對象。
 
  實證研究顯示若以巴賽爾銀行監理委員會規定內部模型之正確性評估準則,Student T分配下之分位數法相較於常態分配與Cornish-Fisher展開式的估計為佳。此外,本文之實證亦顯示風險值的估計分配模型和預測波動模型之選擇會影響風險值預測之正確性。
  This article aims to provide users with applicable Value-at-Risk (VaR) models by accommodating three types of quantiles and volatility estimations, examining VaR model performance at four confidence levels with three criteria—accuracy, efficiency and conservativeness. The sample is composed of Baltic Dry Index (BDI), Baltic Capesize Index (BCI) and Baltic Panamax Index (BPI) constructed by London''s Baltic Exchange.
 
  Based on Kupiec’s (1995) unconditional coverage test in the internal model analysis regularized by the Basel Committee, the VaR model estimated with Student’s T distribution is verified to be the most accurate measurement compared with variance-covariance method and Cornish-Fisher expansions. Furthermore, the empirical evidence shows that the quantile types and volatility proxies influence the accuracy of VaR models significantly.
論文口試委員審定書 ii
版權宣告 iii
謝辭 iv
中文摘要 v
英文摘要 vi
目錄 vii
表目錄 viii
圖目錄 ix
附錄目錄 x
 
第一章緒論1
第一節研究背景1
第二節研究動機3
第三節研究目的5
第四節論文架構6
 
第二章文獻回顧7
第一節風險值的相關機構規定7
第二節風險值文獻回顧8
 
第三章研究設計12
第一節資料來源與風險值定義12
第二節估計風險值分配假設15
第三節波動估計17
第四節風險值檢定測試20
 
第四章實證結果與分析23
第一節敘述性統計23
第二節失敗率分析24
第三節檢定分析28
 
第五章結論與建議32
第一節結論32
第二節後續研究建議33
 
參考文獻34
附錄36
1.Alexander, C. O. and C. T. Leigh (1997), “On the Covariance Matrices Used in Value at Risk Models,” Journal of Derivatives, 50-62.
 
2.Bollerslev, T.(1986), “Generalized Autoregressive Conditional Heteroscedasticity,” Journal of Econometrica, vol.38,pp.34-105.
 
3.Bali T.G., S. Gokcan and B. Liang (2007),”Value at Risk and the Cross-Section of Hedge Fund Returns,” Journal of Banking & Finance, Vol.31, pp.1135-1166.
 
4.Campbell, Rachel, Ronald Huisman, and Kees Koedijk (2001),“Optimal portfolio selection in a Value-at-Risk framework,”Journal of Banking and Finance,1789-1804.
 
5.Duffie, Darrell & Pan, Jun (1997), “An Overview of Value at Risk,” The Journal of Derivatives, spring, pp. 7-49.
 
6.Florent Pochon and Jerome Teiletche(2007), “Empirical investigation of the VaR of hedge funds using daily data, ” Derivatives Use,Trading & Regulation, Vol.12 No.4, pp.314–329.
 
7.Fama, E.F.(1965), “The behavior stock market prices,”Journal of Business, vol.38, pp.34-105.
 
8.Figlewski, S. (1994), “Forcasting Volatility Using Historical Data,” New York University Working Paper, no. 13.
 
9.Hendrick, D. (1996),“Evaluation of Value-atRisk Models Using Historical Data,” Economics Policy Review, Vol.2,pp.39-69.
 
10.Hendricks, D., and B. Hirtle. (1997), “Bank Capital Requirements for Market Risk: The Internal Models Approach”, Economic Policy Review, Federal Reserve Bank of New York 2(December), pp.1-12.
 
11.Jaschke, S. R.(2001), “The Cornish-Fisher-Expansion in the Context of Delta-Gamma-Normal Approximations,” Working paper.
 
12.Linsmeier, T. J. and N. D. Pearson (1996), “Risk Measurement: An Introduction to Value at Risk, ” University of Illinois at Urbana-Champaign.
 
13.Roland Fuss, Dieter G. Kaiser and Zeno Adams(2007)“Value at risk, GARCH modeling and the forecasting of hedge fund return volatility,”Journal of Derivatives & Hedge Funds, Vol.13 No.1,pp.2-25.
 
14.Sriananthakumar, S. and S. Silvapulle (2003), “Estimating vae at risks for short and long trading positions,” Working Paper,
 
Department of Economics and Business Statistics, Monash University, Australia.
 
15.Schwert, G.W.(1989), “Why does stock market volatility change over time?,” Journal of Finance, vol.44, pp.1115-1153.
 
16.P. H. Kupiec(1995), “Techniques for verifying the accuracy of risk measurement models,” The Journal of Derivatives, winter, pp.73-84.
 
17.Wilson, T. (1993), “Infinite Wisdom, ”Risk, Vol.6, pp.37-45.
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