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Title: CoVaR風險值對金融機構風險管理之重要性─以台灣金融控股公司為例
The importance of CoVaR to financial institutions risk management from Taiwanese financial holding company’s perspective
Authors: 陳怡君
Chen, Yi Chun
Contributors: 李桐豪
Chen, Yi Chun
Keywords: VaR
Quantile Regression
Date: 2010
Issue Date: 2013-09-04 10:06:23 (UTC+8)
Abstract: 本研究欲以分量迴歸的方法估計出台灣上市櫃金融控股公司的VaR、CoVaR及其對台灣金融市場的風險溢出,做為總體審慎監理原則下具有抗景氣特色之風險衡量參考指標。我們亦透過金控公司間之CoVaR,觀察金控公司間風險交互影響程度,盼可提供各金控公司做為個體審慎監理原則下風險管理之參考指標。
In this thesis, we intend to estimate Taiwanese financial holding company’s VaR, CoVaR and risk spillover to Taiwan financial market, and apply these to macroprudential risk management. In addition, we intend to develop crossover CoVaR between financial holding companies, offering risk management referral benchmark under microprudential principle to those companies.
There are four features in this thesis. First, we use previous market data to estimate the conditional, comovement, contagion, and contributing VaR - CoVaR. Second, by ∆CoVaR of the institutions to the market, we can observe the holding companies’ systematic risk contribution. Third, we can observe the crossover effect of the holding companies. Last, we could use the characteristics of the institutions to predict future systematic risk.
We particularly use credit spread, slope of yield curve, liquidity spread, change of exchange rate, return of market stock index, change of implied volatility and holding company’s stock price, by quantile regression, to predict the VaR and CoVaR of Taiwan’s holding companies when the probability to loss is 1% and 5%. Then we calculate market systematic risk spillover, ∆CoVaR, to observe the marginal systematic risk contribution of the institutions. Moreover, we use leverage, market-to-book ratio, relative size and maturity mismatch to predict forward ∆CoVaR, offering a reference to macroprudential risk management.
Our empirical results show that in Taiwan financial market, the top four systematic risk contributors of holding companies are Esun Financial Holding, Chinatrust Financial Holding, Taishin Financial Holding and Cathay Financial Holding; the smallest ones are Waterland Financial Holding, Sino Financial Holding, First Financial Holding and Yuanta Financial Holding. We also find out that when loss probability is 1%, predicting ∆CoVaR after two seasons is better; when loss probability is 5%, predicting ∆CoVaR after three seasons is more significant. It shows that when the tail is different, the effect time is also different.
Reference: Alexander, C. O., and C. T. Leigh(1997), “On the Covariances Matrices Used in Value at Risk Models,” Journal of Derivatives, Spring 1997, Vol. 4, No. 3, pp. 50-62.
Baillie, R.T., and T. Bollerslev (1989), “The Message in Daily Exchange Rates: A Conditional Variance Tale.” Journal of Business and Economic Statistics, 1989, Vol. 7, Issue 3, pp. 297-305.
Beder, T. S. (1995), “VAR: Seductive but Dangerous”, Financial Analysts Journal, 1995, Vol. 51, No. 5, September-October, pp. 12-24.
Bollerslev, T. (1987), “A conditional heteroskedastic time series model for speculative prices and rates of returns”, Review of Economics and Statistics, 1987, Vol. 69, No. 3, pp. 542–547.
Brunnermeier, M. K. (2009), “Deciphering the Liquidity and Credit Crunch 2007-08,””Journal of Economic Perspectives, Winter 2009, Vol. 23, No. 1, pp. 77-100.
Brunnermeier, M. K., A. Crocket, G. Goodhart, A. D. Perssaud, and H. Shin (2009), “The Fundamental Principles of Financial Regulation,” 11th Geneva Report on the World Economy.
Brunnermeier, M. K., and T. Adrian (2010), “CoVaR”, 2010, Working Paper.
Chen M. Y. and J. E. Chen (2005), “Application of Quantile Regression to Estimation of Value at Risk”, Review of Financial Risk Management, Jun 2005, Vol. 1, Issue 2, pp. 1-15.
Chernozhukov, V., and L. Umantsev, (2001), “Conditional Value-at-Risk: Aspects of Modeling and Estimation,” Empirical Economics, 2001, Vol. 26, Issue 1, pp. 271-292.
Christoffersen, P., J. Hahn, and A. Inoue (2001), “Testing and comparing Value at Risk measures”, Journal of Empirical Finance, Jul 2001, Vol. 8, Issue 3, pp. 325-342.
Diamond, D. W., and R, G. Rajan (2009), “Fear of Fire Sales and the Credit Freeze”, 2009, NBER Working Paper No. 14925.
Duffee, G.R. (1996), "Treasury Yields and Corporate Bond Yield Spreads: An Empirical Analysis”, 1996, Federal Reserve Board Working paper.
Duffie, D. and J. Pan (1997), “An overview of value at risk”, Journal of Derivatives, Spring 1997, Vol. 4, No.3, pp. 7–49.
Engle, R.F. (1982), “Autoregressive Conditional Heteroscedasticity with Estimates of Variance of United Kingdom Inflation”, Econometrica, 1982, Vol. 50, Issue 4, pp. 987-1008.
Engle, R.F. and S. Manganelli (2004), “CAViaR: Conditional Value at Risk by Quantile Regression”, Journal of Business & Economic Statistics, Oct 2004, Vol. 22, Issue 4, pp. 367-381.
Estrella,A., and M. R. Turbin (2006), “The yield curve as a leading indicator: some practical issues”, Federal Reserve Bank of New York, Current Issues In Economic and Finance, July/August 2006, Vol. 12, No. 5, pp. 1-6.
Goodhart, C. A. E., and A. D. Persaud (2008a), “How to Avoid the Next Crash”, Financial Times, 2008, January 30.
── (2008b), “A Party Pooper’s Guide to Financial Stability”, Financial Times, 2008, June 5.
Hanson, S., A. K. Kashyap, and J. C. Stein (2011), “A Macroprudential Approach to Financial Regulation,” Journal of Economic Perspectives, Winter 2011, Vol. 25, Issue 1, pp. 3-28.
Harvey, C. R., and A. Siddique (1999), ‘‘Autoregressive Conditional Skewness”, Journal of Financial and Quantitative Analysis, Dec 1999, Vol. 34, No. 4, pp. 465–487.
Hendricks, D. (1996), "Evaluation of Value-at-Risk Models Using Historical Data”, Federal Reserve Bank of New York, Economic Policy Review, 1996, Issue Apr, pp. 39-69.
Hull, J. and A. White (1998), “Value at risk when daily changes in market variables are not normally distributed”, Journal of Derivatives, Spring 1998, Vol. 5, No. 3, pp. 9–19.
Jackson, P., D.J. Maude and W. Peerraudin (1997), “Bank Capital and Value at Risk”, Journal of Derivatives, 1997, Vol. 4, 73-89.
Jorion P. (2006), “Value at Risk - The New Benchmark for Managing Financial Risk”, The McGraw Hill Company, 2006, 3rd Edition.
J. P. Morgan (1996), “RiskMetrics Technical Document”, 1996, 4th edition. New York.
Koenker, R. and B. Park (1996), “An Interior Point Algorithm for Nonlinear Quantile Regression”, Journal of Econometrics, 1996, Vol. 71, Issue 1-2, pp. 265–283.
Koenker, R., and G. W. Bassett (1978), “Regression Quantiles”, Econometrica, Jan 19878, Vol. 46, Issue 1, pp. 33-50.
Kroner, K.F., K.P. Kneafsey, and S. Claessens (1995), “Forecasting Volatility in Commodity Markets”, Journal of Forecasting, 1995, Vol. 14, 77-95.
Kuester, K., S. Mittnik, and M. S. Paolella (2006), “Value-at-Risk Prediction: A Comparison of Alternative Strategies”, Journal of Financial Econometrics, 2006, Vol. 4, No. 1, pp. 53–89.
Lee, T. H., and B. Saltoglu (2004), “Evaluating Predictive Performance of Value-at-Risk Models in Emerging Markets:A Reality Check” Working paper.
Pedersen, C. S., and S. E. Satchell (1998), “An Extended Family of Financial-Risk Measures”, Geneva Papers on Risk and Insurance Theory, 1998, Vol. 23, 89–117.
Persaud A. (2009). “Macro-Prudential Regulation,” The World Bank Group, Jul 2009, Note No. 6.
Rockinger, M., and E. Jondeau (2002), “Entropy Densities with an Application to Autoregressive Conditional Skewness and Kurtosis”, Journal of Econometrics, 2002, Vol. 106, Issue 1, pp. 119–142.
Shleifer, A., and Vishny, R. W. (2010), "Unstable Banking," Journal of Financial Economics, Elsevier, Sep 2010, Vol. 97, Issue 3, pp. 306-318.
Stein, J. C. (2010), “Monetary Policy as Financial-Stability Regulation”, 2010, NBER Working Paper No. 16883.
Taylor, J. W. (1999), “A Quantile Regression Approach to Estimating the Distribution of Multiperiod Returns”, Journal of Derivatives, 1999, Vol. 7, Issue 1, 64–78.
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