:::

詳目顯示

回上一頁
題名:壓力測試及其共容於風險值架構之設計---台灣股市1976年至2000年之實證分析
作者:王 甡
校院名稱:國立交通大學
系所名稱:經營管理研究所
指導教授:吳壽山
學位類別:博士
出版日期:2001
主題關鍵詞:壓力測試風險值回顧檢測一般化極值分配極值理論區塊極大模型
原始連結:連回原系統網址new window
相關次數:
  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:0
  • 共同引用共同引用:0
  • 點閱點閱:1
壓力測試是管理市場極端風險的重要工具。但在相關文獻中,所處理的情況不是偏向壓力損失的估計問題或相關執行面的細節,便是直接討論壓力測試在風險管理上之應用,均普遍缺乏整體執行壓力測試的架構分析。此將使壓力測試無法發揮其在風險管理中所應有之效能;另外,相關的文獻中也忽略了如何使壓力損失與風險值兩估計值有一致化的結果,這將可能使壓力損失與風險值產生不一致的現象。本文對此兩項問題進行研究。
本文認為執行壓力測試之整體架構,可按「利用風險衡量值執行風險管控」之基本架構設計之。此一基本架構設核心程序包括對市場風險衡量值及其發生機率的認定(Identification,I)、已認定之市場風險衡量對資產組合之影響效果評估(Evaluation,E),以及風險控制(Control,C)策略擬定,本文將此一核心程序定名為IEC程序。壓力測試之整體架構根據此一基本架構設計,即包括先認定市場壓力情境時可能發生多大的下跌及其發生之機率,然後評估其對於股票組合之影響,當此一衡量極端風險可能發生之損失完成後,接著發展相關的風險控制策略,以達到其所要求報酬及風險偏好組合形態。認定股票市場極端損失程序中,本文採用極值理論(Extreme Value Theory,EVT)中之區塊極大(Block Maxima,BM)模型,利用對一般化極值分配(Generalized Extreme Value,GEV)分配參數之估計值,可以清楚計算市場報酬率超過某一損失的發生機率,利用台灣股市1976年至2000年之資料,實證的結果支持BM模型適用於估計市場壓力損失。在評估市場極端損失的不正常狀況下對資產組合之影響方面,本文採用市場模型進行之,為強調壓力損失之獨立性,評估模式中係以市場報酬率超過市場風險值估計值為條件進行分析。三個風險控制策略則包括調整資產組合之成份股票、利用衍生性商品進行避險及針對極端風險設計共同保險制度。台灣股市之實證分析與個案演算亦證實其可行性與良好的績效。
壓力損失與風險值均為重要風險衡量值,且其應分別反應短期與長期風險外暴。本文進一步「利用風險衡量值執行風險管控」之基本架構,將壓力測試共容於風險值設計成為一整合架構。此架構其中最重要的問題即在於一致化估計極端市場壓力損失與一般市場之最大損失,而其所具備的基本條件至少應為:同一組資料且同一個模型下,同時估計極端市場壓力損失與一般市場之最大損失。本文將單變量GEV分配模型進一步延伸發展成為混合GEV分配模式以尋求較適當之配適模式。研究發現混合GEV分配模式在理論上具有一致化估計極端市場壓力損失與一般市場之最大損失、涵蓋性、掌握尾端轉折性等優點,而實證結果亦顯示其存在該等特性。
本文之貢獻當在對於開發中國家股市,報酬率分配存在雙尾不對稱特性而進行風險管理設計,處理重點在於提出一個壓力測試及其共容於風險值分析的有效架構,從而完備其管控資產價格變動風險機制的功能。
參考文獻
[1] 王甡,「報酬衝擊對條件波動所造成之不對稱效果 --- 台灣股票市場的實證分析」,證券市場發展季刊,第七卷第一期,125至161頁,民國八十五年。
[2] 王甡、吳壽山,「一個金融風暴下可壓力測試之風險性資產管理之解析架構」,證券金融(季刊),第六十六期,1頁至31頁,八十九年七月。
[3] 王甡、吳壽山,「金融機構資產組合壓力測試之文獻回顧、執行方法與管理意涵」,台灣金融財務季刊,第一輯,第一期,第41頁至57頁,八十九年九月。
[4] 王甡、吳壽山,「一致化風險值與壓力測試值之估計 --- 混合一般化極值分配模型分析」,風險管理學報,第三卷,第一期,即將刊出。
[5] Alexander, G. J. and Francis, J. C., Portfolio Analysis, Prentice-Hill, New Jersey, 1986.
[6] Bare, C., “Stressing Out,” Global Custodian (Fall), 1995.
[7] Bank for International Settlement, An Internal Model-based Approach to Market Risk Capital Requirements, Basle Committee on Banking Supervision, Basle, Switzerland, 1995.
[8] Bank for International Settlement, Amendment to the Capital Accord to Incorporate Market Risks, Basle Committee on Banking Supervision, Basle, Switzerland, 1996a.
[9] Bank for International Settlement, Overview of the Amendment to the Capital Accord to Incorporate Market Risks, Basle Committee on Banking Supervision, Basle, Switzerland, 1996b.
[10] Bank for International Settlement, Supervisory Framework for the Use of “Backtesting” in Conjunction with the Internal Models Approach to Market Risk Capital Requirements, Basle Committee on Banking Supervision, Basle, Switzerland, 1996c.
[11] Bank for International Settlement, Explanatory Note: Modification of the Basle Capital Accord of July 1988, Basle Committee on Banking Supervision, Basle, Switzerland, 1997.
[12] Bank for International Settlement, Performance of Models-Based Capital Charges for Market Risk --- 1 July-31 December 1998, Basle, Switzerland, 1999.
[13] Bank for International Settlement, Stress Testing by Large Financial Institutions: Current Practice and Aggregation Issues, Committee on the Global Financial System, Basle, Switzerland, 2000.
[14] Berkowitz, J., “A Coherent Framework for Stress Testing,” Finance and Economics Discussion Papers, No. 1999-29, Board of Governors of the Federal Reserve System, Washington D.C., 1999.
[15] Best, P., Implementing Value at Risk, John Wiely & Sons Ltd., New York, 1998.
[16] Best, P., “VaR versus Stress Testing,” Derivatives Week (Nov. 8th), pp. 6-7, 1999.
[17] Blanco, C., “Complementing VaR with Stress Tests,” Derivatives Week, (Aug. 9th), pp. 5-6, 1999.
[18] Breuer, T and G. Krenn, Guidelines on Market Risk Volume 5 --- Stress Testing, Austrian National Bank, Vienna, Austria, 1999.
[19] Boyer, B., M. Gibson and M. Loretan, “Pitfalls in Tests for Changes in Correlations,” International Finance Discussion Papers Series No. 597R, Board of Governors of the Federal Reserve System, Washington D.C., 1999.
[20] Canadian Imperial Bank of Commerce (CIBC), Annual Report, 1998.
[21] Chase, Annual Report, 1998.
[22] Chorafas, D., The Market Risk Amendment --- Understanding the Marking-to-Model and Value-at-Risk, McGraw-Hill, New York, 1997.
[23] CitiGroup, Annual Report, 1998.
[24] Copeland, T. and J. Weston, Financial Theory and Corporate Policy, Third edition, Addison-Wesley Publishing Company, New York, 1988.
[25] Cruz, M., R. Coleman and G. Salkin, “Modeling and Measuring Operational Risk,” Journal of Risk, 1, pp. 63-72, 1998.
[26] Derivatives Policy Group, Framework for Voluntary Oversight, New York US, 1995.
[27] Deutsche Bank, Annual Report, 1998t.
[28] Dimson, E. and P. Marsh, “Stress Tests of Capital Requirements,” Journal of Banking and Finance, 21, pp. 1515-1546, 1997.
[29] Dunbar, N. and R. Irving, “This Is the Way the World Ends,” Risk, (Dec.), pp. 28-32, 1998.
[30] Embrechts, P., C. Kluppelberg and T. Mikosch, Modelling Extremal Events for Insurance and Finance, Springer-Verlag, Berlin, 1997.
[31] Embrechts, P., S. Resnick and G. Samorodnitsky, “Living on the Edge,” Risk, (Jan.), pp. 96-100, 1998.
[32] Embrechts, P., A. McNeil and D. Straumann, “Correlationn and Dependency in Risk Management: Properties and Pitfalls,” Working Paper, ETH Zurich, 1998.
[33] Embrechts, P., A. McNeil and D. Straumann, “Correlation: Pitfalls and Alternatives,” Working Paper, ETH Zurich, 1999.
[34] Embrechts, P., “Extreme Value Theory: Potential and Limitations as an Integrated Risk Management Tool,” Working Paper, ETH Zurich, 2000.
[35] Finger, C., “A Methodology for Stress Correlations,” RiskMetrics Monitor, (Fourth Quarter), pp. 3-11, 1997.
[36] Fisher, R. and L. Tippett, “Limiting Forms of the Frequency Distribution of the Largest or Smallest Number of a Sample,” Proceedings of the Cambridge Philosophical Society, 24, pp. 180-190, 1928.
[37] Greenspan, A., 1999, “Measuring Financial Risk in the Twenty-first Century, Conference Speech,” The Office of the Comptroller of the Currency.
[38] Gavin, J., “Extreme Value Theory — An Empirical Analysis of Equity Risk,” Working Paper, UBS Warburg, London, 2000.
[39] Guldimann, T., “For Use in Extremes,” Risk, (Feb.), pp. 39, 1999.
[40] Hamilton, J., “A Quasi-Bayesian Approach to Estimating Parameters for Mixtures of Normal Distributions,” Journal of Business and Economic Statistics, 9, pp. 1779-1801, 1991.
[41] Hamilton, J., Time Series Analysis, Princeton University Press, New Jersey, 1994.
[42] Hendricks, D. and B. Hirtle, “Bank Capital Requirements for Market Risk: The Internal Model Approach,” Economic Policy Review, (Dec.), pp. 1-12, Federal Reserve Bank of New York, 1997.
[43] Ho, L., P. Burridge, J. Cadle and M. Theobold, “Value-at-Risk: Applying the Extreme Value Approach to Asia Markets in the Recent Financial Turmoil,” Pacific-Basin Finance Journal, 8, pp. 249-275, 2000.
[44] Hosking, J., “Maximum-likelihood Estimation of the Parameters of the Generalized Extreme-value Distribution,” Journal of the Royal of Statistical Society, Series C, 34, pp. 301-310, 1985.
[45] International Organization of Securities Commissions, The Implications for Securities Regulators of the Increased Use of Value at Risk Models by Securities Firms, Technical Committee, Montreal, Canada, 1995.
[46] International Organization of Securities Commissions, 1998, Methodologies for Determining Minimum Capital Standards for Internationally Active Securities Firms Which Permit Use of Models under Prescribed Conditions, Technical Committee, Montreal, Canada, 1998.
[47] International Organization of Securities Commissions, Recognizing A Firm’s Internal Market Risk Model for the Purposes of Calculating Required Regulatory Capital: Guidance to Supervisors, Technical Committee, Montreal, Canada, 1999.
[48] Joe, H., Multivariate Models and Dependence Concepts, Chapman & Hall, London, 1997.
[49] Jondeau, E. and M. Rockinger, “The Tails Behavior of Stock Returns: Emerging versus Mature Markets,” Working Paper, 1999.
[50] Kim, J. and C. Finger, “A Stress Test to Incorporate Correlation Breakdown,” Working Paper, RiskMetrics Group, 1999.
[51] Kimball, R., “Failure in Risk Management,” New England Economic Review, (Jan./Feb.), pp. 3-12, 2000.
[52] Kupiec, P., “Stress Testing in a Value at Risk Framework,” Journal of Derivatives, (Fall), pp. 7-24, 1998.
[53] Longin, “From Value at Risk to Stress Testing: The Extreme Value Approach,” Journal of Banking and Finance, 24, pp. 1097-1130, 2000.
[54] Loretan, M., and W. English, Evaluating “Correlation Breakdowns During Periods of Market Volatility,” International Finance Discussion Paper Series, No. 658, Board of Governors of the Federal Reserve System, Washington D.C., 2000.
[55] MACFIN Management Consultants, Risk Management Organization in Banking, Report Summary, 1999.
[56] McNeil, A., “Historical Repeating,” Risk, 10 (Jan.), pp. 26-27, 1997.
[57] McNeil, A., “Calculating Quantile Risk Measures for Financial Return Series Using Extreme Value Theory,” Working Paper, ETH Zurich, 1998.
[58] McNeil, A., “Extreme Value Theory for Risk Managers,” Working Paper, ETH Zurich, 1999.
[59] Mezich, A., “Stress Testing,” Derivatives Week, (Jul. 27th), pp. 7-8, 1998.
[60] Nagarajan, S., “Taking the Stress out of Stress Testing,” Derivatives Strategy, (Feb.), pp. 62-63, 1999.
[61] Nelsen, R., An Introduction to Copulas, Springer, New York, 1998.
[62] Reiss, R. and M. Thomas, Statistical Analysis of Extreme Values, Birkhauser, Basle, 1997.
[63] RiskMetrics Group, Risk Management --- A Practical Guide, RiskMetrics Group, New York, 1999.
[64] Smith, R., “Maximum Likelihood Estimation in a Class of Non-regular Cases,” Biometrika, 72, pp. 67-90, 1985.
[65] Schachter, B., “The Value of Stress Testing in Market Risk Management,” Derivatives Risk Management Service, (March), pp. 2-10, 1998.
[66] Schachter, B., “Stringent Stress Tests,” Risk, 13 (Dec.), pp. s22-24, 2000. (Enterprise-wide risk management special issue)
[67] Sharpe, W., “A Simplified Model for Portfolio Analysis,” Management Science, 9, pp. 277-293, 1963.
[68] Street, A., “Risk Management and Regulation,” Electronic Journal of Financial Risk, 1, 1998. (http://www.netexposure.co.uk)
[69] United Bank of Switzerland (UBS), Annual Report, 1998.
[70] Venkataraman, B., “Value at Risk for a Mixture of Normal Distributions: The Use of Quaisi-Bayesian Estimation Technique,” Economic Prospective, (Mar/Apr), Federal Reserve Bank of Chicago, pp. 2-13, 1997.
[71] Wang, S., S. Wu and H. Chung, “A New Approach of Stress Testing for Stock Portfolios and its Application to the Taiwan Stock Market,” Asian Pacific Journal of Economics and Business, 4, 2001, Forthcoming.
[72] Zangari, P., “Catering for an Event,” Risk 10 (Jul.), pp. 34-36, 1997.
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
QR Code
QRCODE