Forward-looking asset correlations in the estimation of economic capital

  1. Álvaro Chamizo 1
  2. Alexandre Fonollosa 1
  3. Alfonso Novales 2
  1. 1 BBVA
  2. 2 Universidad Complutense de Madrid
    info

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

Revista:
Documentos de Trabajo (ICAE)

ISSN: 2341-2356

Año de publicación: 2019

Número: 25

Páginas: 1-48

Tipo: Documento de Trabajo

DIALNET GOOGLE SCHOLAR lock_openDocta Complutense editor

Otras publicaciones en: Documentos de Trabajo (ICAE)

Resumen

Weanalyzewhetherthe creditmarket anticipatedthefinancial crisisbefore the regulatorsusinga methodology that combines the Merton model for the determination of economic capital with Vasicek’s factor model for asset correlation. Contrary to standard practice, we estimate the credit value at risk (VaR) and expected shortfall (ES) of a global loan portfolio using CDS spreads because credit derivat- ivesincorporate forward-looking information on future systemic shocksthat might be essential in the estimation of economic capital. We find that one-factor model can generally be a good representation of correlations in the credit market because of the high intersector correlations, although an appro- priately chosen second factor can provide additional information forrisk estimation in stressed times. We show that there were, indeed, signs of stressin the credit market that were not incorporated in the determination of economic capital during the crisis and thatsome financial institutions did not con- siderproperly. The overallimpressionisthatit is notso much thatrisk models were over-simplified to anticipate the financial crisis butrather, that they were backward-looking. A potential implication of our research is that the level of regulatory capitalshouldreacttoeventsinthe creditmarket.

€ Ver financiación

Información de financiación

Financial support by grants ECO2015-67305-P, PrometeoII/2013/015, Programa de Ayudas a la Investigación from Banco de España is gratefully acknowledged

Financiadores

Referencias bibliográficas

  • Bada, O., Liebl, D., et al., 2014. phtt: Panel data analysis with heterogeneous time trends in R. Journal of Statistical Software 59 (i06).
  • Bai, J., Ng, S., 2002. Determining the number of factors in approximate factor models. Econometrica 70 (1), 191–221.
  • BCBS, 2006. Basel II: International convergence of capital measurement and capital standards: A revised framework - comprehensive version. Basel Committee on Banking Supervision, Basel.
  • Black, F., Cox, J. C., 1976. Valuing corporate securities: Some effects of bond indenture provisions. The Journal of Finance 31 (2), 351–367.
  • Chamizo, A., Novales, A., 2016a. Credit risk decomposition for asset allocation. Journal of Financial Transformation (43), 117–123.
  • Chamizo, A., Novales, A., 2016b. Looking through systemic risk: Determinants, stress testing and market value. SSRN (2842580).
  • Crosbie, P., 1999. Global correlation factor. Moody’s KMV Company.
  • Crosbie, P., 2003. Modeling default risk. Moody’s KMV Company.
  • Daníelsson, J., Jorgensen, B. N., Samorodnitsky, G., Sarma, M., de Vries, C. G., 2013. Fat tails, var and subadditivity. Journal of econometrics 172 (2), 283–291.
  • Das, S. R., 2007. Basel II: Correlation related issues. Journal of Financial Services Research 32 (1-2), 17–38.
  • Derman, E., 2011. Metaphors, models & theories. The Quarterly Journal of Finance 1 (01), 109–126.
  • Du, D., Elkamhi, R., Ericsson, J., 2016. Time-varying asset volatility and the credit spread puzzle. Journal of Finance. Forthcoming.
  • Duffie, D., Singleton, K. J., 1999. Modeling term structures of defaultable bonds. Review of Financial studies 12 (4), 687–720.
  • Dullmann, K., Scheicher, M., Schmieder, C., 2007. Asset correlations and credit portfolio risk - an empirical analysis. Discussion Paper Series 2: Banking and Financial Studies. Deutsche Bundesbank 13.
  • Elkamhi, R., Ericsson, J., Parsons, C. A., 2012. The cost and timing of financial distress. Journal of Financial Economics 105 (1), 62–81.
  • Ericsson, J., Jacobs, K., Oviedo, R., 2009. The determinants of credit default swap premia. Journal of Financial and Quantitative Analysis 44 (01), 109–132.
  • Erlenmaier, U., Gersbach, H., 2013. Default correlations in the Merton model. Review of Finance 18 (5), 1775–1809
  • FED, 2011. Supervisory guidance on model risk management. Board of Governors of the Federal Reserve System, Office of the Comptroller of the Currency, SR Letter, 11–7.
  • Gianfrancesco, I., Curcio, D., Malinconico, A., 2011. Investigating implied asset correlation and capital requirements: empirical evidence from the italian banking system. Banks and Bank Systems 6 (2).
  • Goldberg, J., Nozawa, Y., 2018. Liquidity supply and demand in the corporate bond market. Federal Reserve Board, manuscript.
  • Gordy, M. B., Lütkebohmert, E., 2013. Granularity adjustment for regulatory capital assessment. International Journal of Central Banking 9 (3), 33–70.
  • Greenspan, A., 2008. We will never have a perfect model of risk. Financial Times.
  • Huang, J.-Z., Huang, M., 2012. How much of the corporate-treasury yield spread is due to credit risk? The Review of Asset Pricing Studies 2 (2), 153–202.
  • Hull, J., Predescu, M., White, A., 2010. The valuation of correlation-dependent credit derivatives using a structural model. The Journal of Credit Risk 6 (3), 99.
  • Hull, J., White, A., 2001. The general Hull-White model and supercalibration. Financial Analysts Journal, 34–43.
  • Jacobs, M., 2011. Empirical implementation of a 2-factor structural model for loss-given-default. Journal of Financial Transformation 31 (4), 31–43.
  • Karagozoglu, A. K., Jacobs, M., 2016. Measuring credit risk: CDS spreads vs. credit ratings. Journal of Risk Finance 17 (2), 194–217.
  • Kendall, M., Stuart, A., 1977. The advanced theory of statistics. vol. 1: Distribution theory. London: Griffin, 1977, 4th ed. 1.
  • Kinateder, H., 2016. Basel II versus III: a comparative assessment of minimum capital requirements for internal model approaches. Journal of Risk 18 (3).
  • Kinateder, H., Wagner, N., 2017. Quantitative easing and the pricing of emu sovereign debt. The Quarterly Review of Economics and Finance 66, 1–12.
  • Lando, D., 1998. On Cox processes and credit risky securities. Review of Derivatives Research 2 (2-3), 99–120.
  • Leland, H. E., 2004. Predictions of default probabilities in structural models of debt. Journal of Investement Management 2, 5–20.
  • Lopez, J. A., 2004. The empirical relationship between average asset correlation, firm probability of default, and asset size. Journal of Financial Intermediation 13 (2), 265–283.
  • Markit, 2008. Markit.com user guide. Version 14.3.
  • Markit, 2012. Markit.com user guide CDS & bonds. Version 16.
  • McGinty, L., Beinstein, E., Ahluwalia, R., Watts, M., 2004. Credit correlation: A guide. Tech. rep., JP Morgan.
  • Merton, R. C., 1974. On the pricing of corporate debt: The risk structure of interest rates. The Journal of Finance 29 (2), 449–470.
  • Novales, A., Garcia-Jorcano, L., 2018. Backtesting extreme value theory models of expected shortfall. Quantitative Finance (to appear) published online, 1–27.
  • Ou, S., Chiu, D., Wen, B., Metz, A., 2013. Annual default study: Corporate default and recovery rates, 1920-2012. Investors Service, Data Report, February 15, 2013, 1–64.
  • Oura, H., Schumacher, L. B., 2012. Macrofinancial stress testing-principles and practices. International Monetary Fund Policy Paper.
  • Schönbucher, P. J., 2000. Factor models for portofolio credit risk. Tech. rep., Bonn Econ Discussion Papers.
  • Strebulaev, I. A., 2007. Do tests of capital structure theory mean what they say? The Journal of Finance 62 (4), 1747–1787.
  • Tarashev, N., Zhu, H., 2008. The pricing of correlated default risk: Evidence from the credit derivatives market. Discussion Paper Series 2: Banking and Financial Studies. Deutsche Bundesbank 09.
  • Vasicek, O., 2002. The distribution of loan portfolio value. Risk 15 (12), 160–162.
  • Zhou, C., 2001. An analysis of default correlations and multiple defaults. The Review of Financial Studies 14 (2), 555–576.
Fuente de los datos: Dialnet