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Modelos VaR para calcular el capital mínimo regulatorio por riesgo de mercado

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2015
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Instituto Complutense de Estudios Internacionales (ICEI)
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La revisión de la regulación del riesgo de mercado de Basilea III contempla reemplazar los modelos VaR con una nueva métrica para el cómputo de los requerimientos mínimos de capital. En este trabajo se calcularán los requerimientos de capital por riesgo de mercado para una cartera de acciones del índice S&P500, entre el periodo 2000-2014 en base a la metodología RiskMetrics y alternativamente con modelos GARCH(1,1). Los resultados obtenidos muestran que el capital regulatorio calculado en base a las normas de Basilea II cubre en todo momento las pérdidas de la cartera.
The undergoing overhaul of the Basel III market risk regulatory framework addresses the possibility of replacing VaR models with an alternative method for calculating minimum capital requirements. This paper will calculate the regulatory capital for a hypothetical equity portfolio of 20 of the main stocks in the S&P500, between 2000 and 2014. The RiskMetrics methodology and GARCH(1,1) models are used to estimate volatilities, covariances and correlations. Our results show that the regulatory capital calculated using Basel II rules is at all times above realized portfolio losses.
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Número monográfico: La Crisis en la UEM
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Acerbi, C., Nordio, C., & Sirtori, C. (2008). Expected Shortfall as a Tool for Financial Risk Management. arXiv:cond-mat/0102304. Recuperado a partir de http://arxiv.org/abs/cond-mat/0102304. Acerbi, C., & Tasche, D. (2002). Expected Shortfall: a natural coherent alternative to Value at Risk. Journal of Banking and Finance, 26(7), 1505-1518. http://doi.org/http://dx.doi.org/10.1016/S0378-4266(02)00283-2. Alexander, C. (2008). Value-at-Risk Models (Vol. 4). John Wiley & Sons. Angelidis, T., Benos, A., & Degiannakis, S. A. (2004). The Use of GARCH Models in VaR Estimation. Statistical Methodology, 1(2), 105-128. Ball, J., & Fang, V. (2006). A survey of value-at-risk and its role in the banking industry. Journal of Financial Education, 32, 1-31. Barone-Adesi, G., Giannopoulos, K., & Vosper, L. (2002). Backtesting Derivative Portfolios with Filtered Historical Simulation (FHS). European Financial Management, 8(1), 31-58. http://doi.org/10.1111/1468-036X.00175. Bera, A. K., & Higgins, M. L. (1993). Arch Models: Properties, Estimation and Testing. Journal of Economic Surveys, 7(4), 305-366. http://doi.org/10.1111/j.1467-6419.1993.tb00170.x. Berkowitz, J., & O’Brien, J. (2002). How Accurate Are Value-at-Risk Models at Commercial Banks? The Journal of Finance, 57(3), 1093-1111. http://doi.org/10.1111/1540-6261.00455. Bhattacharyya, M. (2012). A Comparison of VaR Estimation Procedures for Leptokurtic Equity Index Returns. Journal of Mathematical Finance, 02(01), 13-30. http://doi.org/10.4236/jmf.2012.21002. CBSB. Amendment to the capital accord to incorporate market risks (1996). Recuperado a partir de http://www.bis.org/publ/bcbs24.htm. CBSB. Supervisory framework for the use of «backtesting» in conjunction with the internal models approach to market risk capital requirements (1996). Recuperado a partir de http://www.bis.org/publ/bcbs22.htm. CBSB. (1998, septiembre 16). Performance of Models-Based Capital Charges for Market Risk: 1 July-31 December 1998. Recuperado a partir de http://www.bis.org/publ/bcbs57.htm. CBSB. (2003). Trends in risk integration and aggregation. Recuperado a partir de http://www.bis.org/publ/joint07.htm. CBSB. Amendment to the capital accord to incorporate market risks (2005). Recuperado a partir de http://www.bis.org/publ/bcbs119.htm. CBSB. (2005b, abril 11). Trading Book Survey: A Summary of Responses. Recuperado a partir de http://www.bis.org/publ/bcbs112.htm. CBSB. Convergencia internacional de medidas y normas de capital - Marco revisado. Versión integral (2006). Recuperado a partir de http://www.bis.org/publ/bcbs128.htm. CBSB. (2006b, mayo). Regulatory and market differences: issues and observations. Recuperado a partir de http://www.bis.org/publ/joint15.htm. CBSB. (2012, mayo). Fundamental review of the trading book - consultative document. Recuperado a partir de http://www.bis.org/publ/bcbs219.htm. CGFS. (2001). A survey of stress tests and current practice at major financial institutions. Recuperado a partir de http://www.bis.org/publ/cgfs18.htm. Coleman, T. F., Alexander, S., & Li, Y. (2006). Minimizing CVaR and VaR for a portfolio of derivatives. Journal of Banking & Finance, 30(2), 583-605. http://doi.org/10.1016/j.jbankfin.2005.04.012. Engle, R. (2001). GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics. Journal of Economic Perspectives, 15(4), 157-168. http://doi.org/10.1257/jep.15.4.157. Finger, C. C. (2006). How historical simulation made me lazy. RiskMetrics Group. Recuperado a partir de http://gloria-mundi.com/UploadFile/2010-2/ccf_hhs.pdf. González, M., & Nave, J. M. (2010). Efficiency in market risk measures techniques face to crisis situations. Spanish Journal of Finance and Accounting / Revista Española de Financiación y Contabilidad, 39(145), 41-64. http://doi.org/10.1080/02102412.2010.10779678. Hendricks, D. (1996). Evaluation of Value-at-Risk Models Using Historical Data. Economic Policy Review 1996 - Federal Reserve Bank of New York, 2(1), 39-70. Holton, G. A. (2014). Value-at-Risk: Theory and Practice (2.a ed.). Recuperado a partir de http://value-at-risk.net/. Hull, J. C., & White, A. D. (1998). Value at Risk When Daily Changes in Market Variables are not Normally Distributed. The Journal of Derivatives, 5(3), 9-19. http://doi.org/10.3905/jod.1998.407998. Jorion, P. (1997). In Defense of VaR. Derivatives Strategy, 2(4). Recuperado a partir de http://www.derivativesstrategy.com/magazine/archive/1997/0497fea2.asp. Jorion, P. (2007). Value at risk: the new benchmark for managing financial risk (3.a ed.). New York: McGraw-Hill. Jorion, P. (2009). Risk Management Lessons from the Credit Crisis. European Financial Management, 15(5), 923-933. http://doi.org/10.1111/j.1468-036X.2009.00507.x. J.P.Morgan/Reuters. (1996). 1996 RiskMetrics Technical Document. Recuperado a partir de http://www.msci.com/resources/research_papers/technical_doc/1996_riskmetrics_technical_document.html. Kuester, K., Mittnik, S., & Paolella, M. S. (2006). Value-at-Risk Prediction: A Comparison of Alternative Strategies. Journal of Financial Econometrics, 4(1), 53-89. http://doi.org/10.1093/jjfinec/nbj002. Kupiec, P. H. (1995). Techniques for Verifying the Accuracy of Risk Measurement Models. The Journal of Derivatives, 3(2), 73-84. http://doi.org/10.3905/jod.1995.407942. Lee, C.-F., & Su, J.-B. (2012). Alternative statistical distributions for estimating valueat-risk: theory and evidence. Review of Quantitative Finance and Accounting, 39(3), 309-331. http://doi.org/10.1007/s11156-011-0256-x. McMillan, D. G., & Kambouroudis, D. (2009). Are RiskMetrics forecasts good enough? Evidence from 31 stock markets. International Review of Financial Analysis, 18(3), 117-124. http://doi.org/10.1016/j.irfa.2009.03.006. Mina, J., & Xiao, J. (2001). Return to RiskMetrics: The Evolution of a Standard. RiskMetrics Group. Recuperado a partir de http://www.wu.ac.at/pmg/banking/sbwl/lvs_ws/vk4/rrmfinal.pdf. Pafka, S., & Kondor, I. (2001). Evaluating the RiskMetrics Methodology in Measuring Volatility and Value-at-Risk in Financial Markets. Physica A: Statistical Mechanics and its Applications, 299(1-2), 305-310. http://doi.org/10.1016/S0378-4371(01)00310-7. Rowe, D. (2013). Risk Management Beyond VaR. Presentado en Federal Reserve Bank of Atlanta, 2013 Financial Markets Conference «Maintaining Financial Stability: Holding a Tiger by the Tail», Atlanta;Georgia. Recuperado a partir de https://www.frbatlanta.org/documents/news/conferences/13fmc_rowe.pdf. Roy, I. (2011). Estimating Value at Risk using Filtered Historical Simulation in the Indian capital market. Reserve Banks of INdia Occasional Papers, 32(2). Recuperado a partir de http://rbidocs.rbi.org.in/rdocs/Content/PDFs/OCIEVR261012_A3.pdf. Sollis, R. (2009). Value at risk: a critical overview. Journal of Financial Regulation and Compliance, 17(4), 398-414. http://doi.org/http://0-dx.doi.org.cisne.sim.ucm.es/10.1108/13581980911004370. So, M. K. P., & Yu, P. L. H. (2006). Empirical analysis of GARCH models in value at risk estimation. Journal of International Financial Markets, Institutions and Money, 16(2), 180-197. http://doi.org/10.1016/j.intfin.2005.02.001. Taleb, N. (1997, enero). The World According to Nassim Taleb [Derivatives Strategy]. Recuperado a partir de http://www.derivativesstrategy.com/magazine/archive/1997/1296qa.asp. Taleb, N. (2010). The Black Swan: Second Edition: The Impact of the Highly Improbable (2 edition). New York: Random House Trade Paperbacks. UBS. (2008). Shareholder Report on UBS’s Write-Downs. Zurich: UBS. Recuperado a partir de http://maths-fi.com/ubs-shareholder-report.pdf. UBS. (2010). Transparency Report to the Shareholders of UBS AG. Zurich: UBS AG. Recuperado a partir de http://www.ubs.com/global/en/about_ubs/transparencyreport.html. Vilariño, Á. (2011). Análisis de los modelos generalmente aceptados para la estimación del valor razonable de los instrumentos financieros en condiciones normales y de estrés (Tésis inédita). Universidad Complutense de Madrid, Madrid. Zumbach, G. (2006). Backtesting risk methodologies from one day to one year. Jorurnal of Risk, 9(2), 55-91.
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