References

Alexander, C. and Barbosa, A. (2007) Effectiveness of minimum variance hedging. Journal of Portfolio Management 33, 46–59.

Alexander, C. and Sheedy, E. (2008) Developing a stress testing framework based on market risk models. Journal of Banking and Finance 32(10), 2220–2236.

Alexander, C., Lazar, E. and Stanescu, S. (2008) Analytic moments for conditional and aggregated GARCH variances and returns. ICMA Discussion Papers in Finance DP2008–08.

Alexander, C., Lazar, E. and Stanescu, S. (2009) Analytic approximations to VaR in a GARCH framework. ICMA Discussion Papers in Finance.

Angelidis, T., Benos, A. and Degiannakis, S. (2004) The use of GARCH models in VaR estimation. Statistical Methodology 1, 105–128.

Aragones, J., Blanco, C. and Dowd, K. (2001) Incorporating stress tests into market risk modeling. Derivatives Quarterly 7(3), 44–49.

Artzner, P., Delbaen, F., Eber, J. and Heath, D. (1999) Coherent measures of risk. Mathematical Finance 9, 203–228.

Bangia, A., Diebold, F.X., Schuermann, T. and Stroughair, J.D. (2002) Modeling liquidity risk, with implications for traditional market risk measurement and management. In S. Figlewski and R.M. Levich (eds), Risk Management: The State of the Art. Kluwer Academic, Boston.

Barone-Adesi, G., Bourgoin, F. and Giannopoulos, K. (1998) Don't look back. Risk 11, 100–103.

Barone-Adesi, G., Giannopoulos, K. and Vosper, L. (1999) VaR without correlations for nonlinear portfolios. Journal of Futures Markets 19, 583–602.

Basel Committee on Banking Supervision (1996) Amendment to the capital accord to incorporate market risks. Available from http://www.bis.org (accessed August 2008).

Basel Committee on Banking Supervision (2005) Amendment to the capital accord to incorporate market risks (Updated). Available from http://www.bis.org (accessed August 2008).

Basel Committee on Banking Supervision (2006) International convergence of capital measurement and capital standards: A revised framework (Comprehensive version). Available from http://www.bis.org (accessed August 2008).

Basel Committee on Banking Supervision (2008) Guidelines for computing capital for incremental risk in the trading book. Available from http://www.bis.org (accessed August 2008).

Berkowitz, J. (1999) A coherent framework for stress-testing. Journal of Risk 2(2), 1–11.

Berkowitz, J. and O'Brien, J. (2002) How accurate are value-at-risk models at commercial banks? Journal of Finance 57, 1093–1111.

Berkowitz, J., Christoffersen, P. and Pelletier, D. (2006) Evaluating VaR models with desk-level data. Working paper, McGill University.

Borio, C. (2000) Market liquidity and stress: selected issues and policy implications. BIS Quarterly Review, 38–51.

Boudoukh, J., Richardson, M. and Whitelaw, R. (1998) The best of both worlds. Risk 11(5), 64–67.

Butler, C. (1999) Mastering Value at Risk: A Step-by-Step Guide to Understanding and Applying VaR. Financial Times Pitman, London.

Butler, J.S. and Schachter, B. (1998) Estimating VaR with a precision measure by combining kernel estimation with historical simulation. Review of Derivatives Research 1, 371–390.

Chen, S. and Tang, C. (2005) Nonparametric inference of value-at-risk for dependent financial returns. Journal of Financial Econometrics 3, 227–255.

Christoffersen, P. (1998) Evaluating interval forecasts. International Economic Review 39, 841–862.

Christoffersen, P. (2003) Elements of Financial Risk Management. Academic Press, Boston.

Committee on the Global Financial System (2005) Stress testing at major financial institutions: survey results and practice. CGFS Publications No. 24. Available from http://www.bis.org/publ/cgfs24.htm (accessed August 2008).

Connor, G. (2000) Robust confidence intervals for the bias test of risk forecasts. Technical report, MSCI Barra.

Cornish, E.A. and Fisher, R.A. (1937) Moments and cumulants in the specification of distributions. Review of the International Statistical Institute 5, 307–320.

Danielsson, J. (2007) The Value-at-Risk Reference: Key Issues in the Implementation of Market Risk. Risk Publications, London.

Derivatives Policy Group (1995) Framework for voluntary oversight: the OTC derivatives activities of securities firm affiliates to promote confidence and stability in financial markets. http://riskinstitute.ch/137790.htm (accessed August 2008).

Dowd, K. (2005) Measuring Market Risk, 2nd edition. John Wiley & Sons, Ltd, Chichester.

Duffie, D. and Pan, J. (1997) An overview of value at risk. Journal of Derivatives, Spring, 7–49. Reprinted (2001) in G. Constantinides and A.G. Malliaris (eds), Options Markets. Edward Elgar, Cheltenham.

Garman, M. (1996) Improving on VaR. Risk, 9(5), 61–63

Gencay, R. and Selcuk, F. (2004) Extreme value theory and VaR: Relative performance in emerging markets. International Journal of Forecasting 20, 287–303.

Giot, P. and Laurent, S. (2003) Value-at-risk for long and short trading positions. Journal of Applied Econometrics 18, 641–664.

Glasserman, P. (2004) Monte Carlo Methods in Financial Engineering. Springer-Verlag, New York.

Glasserman, P., Heidelberger, P. and Shahabuddin, P. (2000) Variance reduction techniques for estimating value-at-risk. Management Science 46, 1349–1364.

Holton, G. (2003) Value-at-Risk: Theory and Practice. Academic Press, Amsterdam.

Huisman, R., Koedijk, K.G. and Pownall, R.A.J. (1998) VaR-x: Fat tails in financial risk management. Journal of Risk 1(1), 47–61.

Hull, J. and White, A. (1998) Incorporating volatility updating into the historical simulation method for value-at-risk. Journal of Risk 1(1), 5–19.

Johnson, N.L. (1954) Systems of frequency curves derived from the first law of Laplace. Trabajos de Estadística 5, 283–291.

Jorion, P. (2006) Value-at-Risk, 3rd edition. McGraw-Hill, New York.

Kendall, M.G. (1940) Note on the distribution of quantiles for large samples. Supplement to the Journal of the Royal Statistical Society 7(1), 83–85.

Kupiec, P. (1995) Techniques for verifying the accuracy of risk measurement models. Journal of Derivatives 2, 173–184.

Longin, F. (2000) From value at risk to stress testing: The extreme value approach. Journal of Banking and Finance 24, 1097–1130.

Longin, F. (2005) The choice of the distribution of asset returns: How extreme value theory can help. Journal of Banking and Finance 29, 1017–1035.

Markowitz, H. (1959) Portfolio Selection. John Wiley & Sons, Inc., New York.

Matten, C. (2000) Managing Bank Capital: Capital Allocation and Performance Measurement, 2nd edition. John Wiley & Sons, Ltd, Chichester.

McNeil, A. and R. Frey (2000) Estimation of tail-related risk measures for heteroscedastic financial time series: An extreme value approach. Journal of Empirical Finance 7, 271–300.

McNeil, A., Frey, R. and Embrechts, P. (2005) Quantitative Risk Management. Princeton University Press, Princeton, NJ.

Mina, J. and A. Ulmer (1999) Delta-gamma four ways. RiskMetrics Working Paper. http://www.riskmetrics.com/publications/working_papers.html (accessed August 2008).

Mittnik, S. and Paolella, M. (2000) Conditional density and value-at-risk prediction of Asian currency exchange rates. Journal of Forecasting 19, 313–333.

Patton, A. (2008) Copula-based models for financial time series. In T.G. Andersen, R.A. Davis, J.-P. Kreiss and T. Mikosch (eds), Handbook of Financial Time Series. Springer-Verlag, Berlin.

Perignon, C. and Smith, D. (2006) The level and quality of value-at-risk disclosure by commercial banks. Working paper, Simon Fraser University, Vancouver.

Pritsker, M. (2006) The hidden dangers of historical simulation. Journal of Banking and Finance 30, 561–582.

Sharpe, W.F. (1994) The Sharpe ratio. Journal of Portfolio Management 21, 49–59.

Sheather, S. and Marron, J.S. (1990) Kernel quantile estimators. Journal of the American Statistical Association 85, 410–416.

Silverman, B.W. (1986) Density Estimation for Statistics and Data Analysis. Chapman & Hall, London.

So, M. and Yu, P. (2006) Empirical analysis of GARCH models in value at risk estimation. International Financial Markets, Institutions & Money 16, 180–197.

Spetzler, C. and Staël von Holstein, C.-A. (1977) Probability encoding in decision analysis. In R. Howard and J.E. Matheson (eds), Readings in Decision Analysis, 2nd edition. Stanford Research Institute, Menlo Park, CA.

Studer, G. and Lüthi, H.-J. (1997) Quadratic maximum loss for risk measurement of portfolios. Risklab report. http://citeseerx.ist.psu.edu/viewdoc/summary? doi=10.1.1.17.2585 (accessed August 2008).

Szegö, G. (ed.) (2004) Risk Measures for the 21st Century. John Wiley & Sons, Ltd, Chichester.

Tuenter, H. (2001) An algorithm to determine the parameters of SU curves in the Johnson system of probability distributions by moment matching. Journal of Statistical Computation and Simulation 70(4), 325–347.

Venter, J. and de Jongh, P. (2002) Risk estimation using the normal inverse Gaussian distribution. Journal of Risk 4(2), 1–24.