Análisis comparativo de técnicas (IMA) para determinar capitales mínimos regulados por Basilea, ante crisis en mercados emergentes
Análisis comparativo de técnicas (IMA) para determinar capitales mínimos regulados por Basilea, ante crisis en mercados emergentes
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Álvarez, V.A. y Rossignolo, A.F. 2014. Análisis comparativo de técnicas (IMA) para determinar capitales mínimos regulados por Basilea, ante crisis en mercados emergentes. ODEON. 8 (dic. 2014).
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Dec 20, 2014
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Una alternativa sugerida por normas de Basilea para estimar el Valor en Riesgo (VaR) como medida del riesgo de mercado es el método de modelos internos (IMA), que permite a las instituciones reguladas calcularlo utilizando metodologías propias, resultando que desarrollar técnicas precisas para estimar el VaR adquiere especial relevancia. Un método de estimación de cuantiles extremos, que considera circunstancias extraordinarias e inusuales, utiliza la Teoría de Valores Extremos (EVT). Este trabajo intenta evaluar empíricamente, en escenarios de crisis financieras, la aptitud del método EVT, comparándolo con otros métodos de estimación del VaR y estudiando su aplicabilidad en mercados desarrollados y emergentes. Se concluye que los métodos basados en EVT pueden ayudar a las instituciones a evitar grandes pérdidas ante desastres del mercado. La constitución del “Capital Mínimo Regulatorio” exigido por las normas de Basilea ilustra las ventajas del EVT. Aparte, no se aprecian diferencias significativas entre mercados desarrollados y emergentes.
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Referencias (VER)
Alexander, C. (2008). Market Risk Analysis Volume IV: Value-at-Risk Models, John Wiley & Sons Ltd., The Atrium, Southern Gate, Chichester, West Sussex, United Kingdom.
Balkema, A.A. and DeHaan, L. (1974). Residual lifetime at great age, Annals of Probability 2, pp.792-804.
Bao, L., Lee, T-H., and Salto?lu, B. (November 2004). Evaluating Predictive Performance of Value-at-Risk Models in Emerging Markets: A Reality Check, available at http://www.gloriamundi.org.
Basel Committee On Banking Supervision, (1996), Amendment to the Capital Accord to Incorporate Market Risks, Bank for International Settlements, Basel, Switzerland.
Basel Committee On Banking Supervision, (June 2004), International Convergence of Capital Measurement and Capital Standards, Bank for International Settlements, Basel, Switzerland.
Beder, T. S. (1995). VaR: Seductive but Dangerous, Financial Analyst Journal, September-October, pp. 12-24.
Beirlant, J., Vynckier, P., and Teugels, J.L. (1996). Tail Index Estimation, Pareto QuantilePlots and Regression Diagnostics, Journal of the American Statistical Association 91 (436), pp. 1659-1667.
Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity, Journal of Econometrics, 31, pp. 307-327.
Bollerslev, T., Engle, R. F., and Nelson, D. (1994). arch Models, in R. F. Engle and D. L. McFadden Eds., Handbook of Econometrics, Vol. 4, pp. 2959-3038, North Holland, Amsterdam, Netherlands.
Brooks, C., Clare, A. D., and Persand, G. (2000). An EVT Approach to Calculating Risk Capital Requirements, Discussion Papers in Finance 2000-2007, Isma Centre, University of Reading, Reading, United Kingdom.
Brooks, C., Clare, A. D.,DallaMolle, J. W., and Persand, G. (December 2003). A Comparison of Extreme Value Theory Approaches for Determining Value at Risk, Forthcoming, Journal of Empirical Finance.
Campbell, J. Y., and Hentschel, L. (1992). No News is Good News: An Asymmetric Model of Changing Volatility in Stock Returns, Journal of Financial Economics, 312, pp. 281-318.
Christoffersen, P. (2003). Elements of Financial Risk Management, Academic Press, New York, United States.
Christoffersen, P. F. (2003). Elements of Financial Risk Management, First Edition, Academic Press, New Jersey, United States.
Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values, Springer Series in Statistics, Springer-Verlag London Limited, Berlin, Germany.
Coronel-Brinzio, H. F., and Hernandez-Montoya, A. R. (November 2004). On fitting the Pareto-Levy distribution to stock market index data: selecting a suitable cutoff value, Facultad de Física e Inteligencia Artificial, Universidad Veracruzana, Xalapa, Veracruz, Mexico.
Da Costa Lewis, N. (2003). Market Risk Modelling, RISK Books, Risk Waters Group Ltd., London, United Kingdom.
Danielsson, J. and DeVries, C. (September 1997) Value-at-Risk and Extreme Returns,available at http://www.gloriamundi.org.
Danielsson, J., P. Hartmann y C. DeVries. (1998). The Cost of Conservatism: Extreme Returns, Value-at-Risk and the Basel ‘Multiplication Factor’. January 1998 issueof risk.
Danielsson, J., Hartmann, P. and DeVries, C. (January 1998). The Cost of Conservatism:Extreme Returns, Value-at-Risk and the Basle ‘Multiplication Factor’, January 1998issue of risk, also available at http://www.gloriamundi.org.
Danielsson, J. and DeVries, C. (August 1999). Using a Bootstrap Method to Choose the Sample Fraction in Tail Index Estimation, available at http://www.gloriamundi.org.
Danielsson, J., P. Embrechts, C. Goodhart, C. Keating, F. Muennich, O. Renault y H. S.Shin. (2001). An Academic Response to Basel ii, Special Paper N.o 30, lse Financial Markets Group, esrc Centre, London, United Kingdom.
Danielsson, J. (2004). The Emperor has no Clothes: Limits to Risk Modelling, in SZEGÖ, G., (ed.). Risk Measures for the 21.t century, John Wiley & Sons, West Sussex, United Kingdom.
Danielsson, J., and Zigrand, J. P. (July 2005). On time-scaling of risk and the square rootof-time rule, Department of Accounting and Finance and Financial Markets Group, London School of Economics, London, United Kingdom.
Donnelly, C. and Embrechts, P. (2010). The devil is in the tails: actuarial mathematics andthe subprime mortgage crisis, Astin Bulletin 40(1), pp. 1-33.
Dowd, K. (1998). Beyond value at risk: the new science of risk management, Wiley seriesin Frontiers in Finance, John Wiley & Sons Ltd., Chichester, West Sussex, United Kingdom.
Dowd, K. (2005). Measuring Market Risk, Second Edition, Wiley series in Frontiers inFinance, JohnWiley & Sons Ltd, Chichester, West Sussex, United Kingdom.
Embrechts, P., Klüppelberg, C., and Mikosch, T., (1997), Modelling Extremal Events for Insurance and Finance, Springer-Verlag, Berlin Heidelberg, Berlin, Germany.
Fama, E. F. (1965). The Behavior of Stock Market Prices,Journal of Business, 38, pp. 34-105.
Fisher, R., and Tippet, L. (1928). Limiting Forms of the Frequency Distribution of the Largest or Smallest Member of a Sample, Proceedings of the Cambridge Philosophical Society 24, pp. 180-190.
Gujarati, D. N. (1997). Econometría básica, 3ra Edición, McGraw-Hill, New York, United States.
Hansen, P. and Lunde, A. (2005). A Forecast Comparison of Volatility Models: Does anything beat a GARCH(1;1)?, Journal of Applied Econometrics, 20, pp. 873-889.
Jackson, P., Maude, D. J., and Perraudin, W. (1998). Bank Capital and Value at Risk, Working Paper, Bank of England, London, United Kingdom.
Jondeau, E., and Rockinger, M. (2003). Testing for differences in the tails of stock-marketreturns, Journal of Empirical Finance 209, pp. 1-23.
Jondeau, E., and Rockinger, M. (April 1999). The Behaviour of Stock Returns: Emerging versus Mature Markets, Paper 66, Banque de France, Paris, France.
Jorion, P. (1999). Valor en riesgo, Editorial Limusa, México DF, Mexico.
JP Morgan.(1994). Doc. Técnico RiskMetrics., http://www.riskmetrics.com.
JP Morgan and Reuters. (1996). Risk Metrics Technical Document, Fourth Edition, NewYork, United States.
Kupiec, P. (1995). Techniques for Verifying the Accuracy of Risk Measurement Models, Journal of Derivatives 3, pp. 73-84.
Mandelbrot, B. (1963). The Variation of Certain Speculative Prices,Journal of Business, 36, pp. 394-419.
Manganelli, S. and Engle, R. (2004). A Comparison of Value-at-Risk Models in Finance, Risk Measures for the 21st Century edited by G. Szegö, (2004), John Wiley & SonsLtd., Chichester, West Sussex,United Kingdom.
Manganelli, S., and Engle, R. (August 2001). Value at Risk Models in Finance, Working Paper N.° 75, Working Paper Series, European Central Bank.
MAPA, D. (s/d viewed December 2007). A Range-Based Generalized Auto Regressive Conditional Heteroskedasticity Model for Forecasting Financial Volatility, availableat http://www.gloriamundi.org.
McNeil, A., J., and Frey, R., (June 1999). Estimation of Tail-Related Risk Measures for Heteroscedastic Financial Time Series: an Extreme Value Approach, available at http://www.gloriamundi.org.
McNeil, A. J., Frey, R., and Embrechts, P. (2005). Quantitative Risk Management, Princeton University Press, Princeton, New Jersey, United States.
McNeil, A., and Saladin, T. (1997). The Peaks Over Thresholds Methods for Estimating High Quantiles for Loss Distributions, Proceedings of the XXVIIIth International Astin Colloquium, Cairns, pp. 23-43.
Neftci, S. (Spring 2000). Value at Risk Calculations, Extreme Events, and Tail Estimation,available at http://www.gloriamundi.org.
Osterreischische National Bank (ONB) (September 1999). “Stress Testing”, Guidelines on Market Risk Volume 5, Vienna, Austria.
Penza, P., and Bansal, V. (2001). Measuring Market Risk with Value at Risk, Financial Engineering Series, John Wiley and Sons, New York, United States.
Pickands, J. (1975). Statistical Inference Using Extreme Order Statistics, Annals of Statistics 3, pp. 119-131.
Rachev, S., Menn, C. and Fabozzi, F. (2005) Fat-Tailed and Skewed Asset Return Distributions, John Wiley & Sons, New Jersey, United States.
Reiss, R.-D., and Thomas, M. (2007). Statistical Analysis of Extreme Values with Applications to Insurance, Finance, Hydrology and Other Fields, Birkhäuser Verlag, AG, Berlin, Germany.
Balkema, A.A. and DeHaan, L. (1974). Residual lifetime at great age, Annals of Probability 2, pp.792-804.
Bao, L., Lee, T-H., and Salto?lu, B. (November 2004). Evaluating Predictive Performance of Value-at-Risk Models in Emerging Markets: A Reality Check, available at http://www.gloriamundi.org.
Basel Committee On Banking Supervision, (1996), Amendment to the Capital Accord to Incorporate Market Risks, Bank for International Settlements, Basel, Switzerland.
Basel Committee On Banking Supervision, (June 2004), International Convergence of Capital Measurement and Capital Standards, Bank for International Settlements, Basel, Switzerland.
Beder, T. S. (1995). VaR: Seductive but Dangerous, Financial Analyst Journal, September-October, pp. 12-24.
Beirlant, J., Vynckier, P., and Teugels, J.L. (1996). Tail Index Estimation, Pareto QuantilePlots and Regression Diagnostics, Journal of the American Statistical Association 91 (436), pp. 1659-1667.
Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity, Journal of Econometrics, 31, pp. 307-327.
Bollerslev, T., Engle, R. F., and Nelson, D. (1994). arch Models, in R. F. Engle and D. L. McFadden Eds., Handbook of Econometrics, Vol. 4, pp. 2959-3038, North Holland, Amsterdam, Netherlands.
Brooks, C., Clare, A. D., and Persand, G. (2000). An EVT Approach to Calculating Risk Capital Requirements, Discussion Papers in Finance 2000-2007, Isma Centre, University of Reading, Reading, United Kingdom.
Brooks, C., Clare, A. D.,DallaMolle, J. W., and Persand, G. (December 2003). A Comparison of Extreme Value Theory Approaches for Determining Value at Risk, Forthcoming, Journal of Empirical Finance.
Campbell, J. Y., and Hentschel, L. (1992). No News is Good News: An Asymmetric Model of Changing Volatility in Stock Returns, Journal of Financial Economics, 312, pp. 281-318.
Christoffersen, P. (2003). Elements of Financial Risk Management, Academic Press, New York, United States.
Christoffersen, P. F. (2003). Elements of Financial Risk Management, First Edition, Academic Press, New Jersey, United States.
Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values, Springer Series in Statistics, Springer-Verlag London Limited, Berlin, Germany.
Coronel-Brinzio, H. F., and Hernandez-Montoya, A. R. (November 2004). On fitting the Pareto-Levy distribution to stock market index data: selecting a suitable cutoff value, Facultad de Física e Inteligencia Artificial, Universidad Veracruzana, Xalapa, Veracruz, Mexico.
Da Costa Lewis, N. (2003). Market Risk Modelling, RISK Books, Risk Waters Group Ltd., London, United Kingdom.
Danielsson, J. and DeVries, C. (September 1997) Value-at-Risk and Extreme Returns,available at http://www.gloriamundi.org.
Danielsson, J., P. Hartmann y C. DeVries. (1998). The Cost of Conservatism: Extreme Returns, Value-at-Risk and the Basel ‘Multiplication Factor’. January 1998 issueof risk.
Danielsson, J., Hartmann, P. and DeVries, C. (January 1998). The Cost of Conservatism:Extreme Returns, Value-at-Risk and the Basle ‘Multiplication Factor’, January 1998issue of risk, also available at http://www.gloriamundi.org.
Danielsson, J. and DeVries, C. (August 1999). Using a Bootstrap Method to Choose the Sample Fraction in Tail Index Estimation, available at http://www.gloriamundi.org.
Danielsson, J., P. Embrechts, C. Goodhart, C. Keating, F. Muennich, O. Renault y H. S.Shin. (2001). An Academic Response to Basel ii, Special Paper N.o 30, lse Financial Markets Group, esrc Centre, London, United Kingdom.
Danielsson, J. (2004). The Emperor has no Clothes: Limits to Risk Modelling, in SZEGÖ, G., (ed.). Risk Measures for the 21.t century, John Wiley & Sons, West Sussex, United Kingdom.
Danielsson, J., and Zigrand, J. P. (July 2005). On time-scaling of risk and the square rootof-time rule, Department of Accounting and Finance and Financial Markets Group, London School of Economics, London, United Kingdom.
Donnelly, C. and Embrechts, P. (2010). The devil is in the tails: actuarial mathematics andthe subprime mortgage crisis, Astin Bulletin 40(1), pp. 1-33.
Dowd, K. (1998). Beyond value at risk: the new science of risk management, Wiley seriesin Frontiers in Finance, John Wiley & Sons Ltd., Chichester, West Sussex, United Kingdom.
Dowd, K. (2005). Measuring Market Risk, Second Edition, Wiley series in Frontiers inFinance, JohnWiley & Sons Ltd, Chichester, West Sussex, United Kingdom.
Embrechts, P., Klüppelberg, C., and Mikosch, T., (1997), Modelling Extremal Events for Insurance and Finance, Springer-Verlag, Berlin Heidelberg, Berlin, Germany.
Fama, E. F. (1965). The Behavior of Stock Market Prices,Journal of Business, 38, pp. 34-105.
Fisher, R., and Tippet, L. (1928). Limiting Forms of the Frequency Distribution of the Largest or Smallest Member of a Sample, Proceedings of the Cambridge Philosophical Society 24, pp. 180-190.
Gujarati, D. N. (1997). Econometría básica, 3ra Edición, McGraw-Hill, New York, United States.
Hansen, P. and Lunde, A. (2005). A Forecast Comparison of Volatility Models: Does anything beat a GARCH(1;1)?, Journal of Applied Econometrics, 20, pp. 873-889.
Jackson, P., Maude, D. J., and Perraudin, W. (1998). Bank Capital and Value at Risk, Working Paper, Bank of England, London, United Kingdom.
Jondeau, E., and Rockinger, M. (2003). Testing for differences in the tails of stock-marketreturns, Journal of Empirical Finance 209, pp. 1-23.
Jondeau, E., and Rockinger, M. (April 1999). The Behaviour of Stock Returns: Emerging versus Mature Markets, Paper 66, Banque de France, Paris, France.
Jorion, P. (1999). Valor en riesgo, Editorial Limusa, México DF, Mexico.
JP Morgan.(1994). Doc. Técnico RiskMetrics., http://www.riskmetrics.com.
JP Morgan and Reuters. (1996). Risk Metrics Technical Document, Fourth Edition, NewYork, United States.
Kupiec, P. (1995). Techniques for Verifying the Accuracy of Risk Measurement Models, Journal of Derivatives 3, pp. 73-84.
Mandelbrot, B. (1963). The Variation of Certain Speculative Prices,Journal of Business, 36, pp. 394-419.
Manganelli, S. and Engle, R. (2004). A Comparison of Value-at-Risk Models in Finance, Risk Measures for the 21st Century edited by G. Szegö, (2004), John Wiley & SonsLtd., Chichester, West Sussex,United Kingdom.
Manganelli, S., and Engle, R. (August 2001). Value at Risk Models in Finance, Working Paper N.° 75, Working Paper Series, European Central Bank.
MAPA, D. (s/d viewed December 2007). A Range-Based Generalized Auto Regressive Conditional Heteroskedasticity Model for Forecasting Financial Volatility, availableat http://www.gloriamundi.org.
McNeil, A., J., and Frey, R., (June 1999). Estimation of Tail-Related Risk Measures for Heteroscedastic Financial Time Series: an Extreme Value Approach, available at http://www.gloriamundi.org.
McNeil, A. J., Frey, R., and Embrechts, P. (2005). Quantitative Risk Management, Princeton University Press, Princeton, New Jersey, United States.
McNeil, A., and Saladin, T. (1997). The Peaks Over Thresholds Methods for Estimating High Quantiles for Loss Distributions, Proceedings of the XXVIIIth International Astin Colloquium, Cairns, pp. 23-43.
Neftci, S. (Spring 2000). Value at Risk Calculations, Extreme Events, and Tail Estimation,available at http://www.gloriamundi.org.
Osterreischische National Bank (ONB) (September 1999). “Stress Testing”, Guidelines on Market Risk Volume 5, Vienna, Austria.
Penza, P., and Bansal, V. (2001). Measuring Market Risk with Value at Risk, Financial Engineering Series, John Wiley and Sons, New York, United States.
Pickands, J. (1975). Statistical Inference Using Extreme Order Statistics, Annals of Statistics 3, pp. 119-131.
Rachev, S., Menn, C. and Fabozzi, F. (2005) Fat-Tailed and Skewed Asset Return Distributions, John Wiley & Sons, New Jersey, United States.
Reiss, R.-D., and Thomas, M. (2007). Statistical Analysis of Extreme Values with Applications to Insurance, Finance, Hydrology and Other Fields, Birkhäuser Verlag, AG, Berlin, Germany.