Cyclicality in catastrophic and operational risk measurements

Journal of Banking and Finance

Volumn 31, Issue 4, 2007, Pages 1191-1235

  Allen, Linda ^a   Bali, Turan G ^a  

^a CITY UNIVERSITY OF NEW YORK   (United States)

Author keywords

Catastrophic risk; Extreme value theory; Operational risk; Skewed fat tailed distribution; Value at risk

Indexed keywords

EID: 33947497147     PISSN: 03784266     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbankfin.2006.10.007     Document Type: Article

References (53)

1. Allen L., and Saunders A. Bank window dressing: Theory and evidence. Journal of Banking and Finance 16 (1992) 585-623
2. Allen L., and Saunders A. Cyclical effects in credit risk ratings and default risk. In: Ong M. (Ed). Credit Ratings: Methodologies, Rationale and Default Risk (2002), Risk Books, London 45-79
3. Allen L., and Saunders A. Incorporating systemic influences into risk measurements: A survey of the literature. Journal of Financial Services Research 26 (2004) 161-191
4. Allen L., Boudoukh J., and Saunders A. Understanding Market, Credit and Operational Risk: The Value at Risk Approach (2004), Blackwell Publishing, Oxford
5. Bali T.G. An extreme value approach to estimating volatility and value at risk. Journal of Business 76 (2003) 83-108
6. Bali T.G., and Neftci S. Disturbing extremal behavior of spot rate dynamics. Journal of Empirical Finance 10 (2003) 455-477
7. Bali, T.G., Theodossiou, P., 2004. Risk measurement performance of alternative distribution functions. Working Paper, Baruch College, City University of New York.
8. Bali, T.G., Theodossiou, P., forthcoming. A conditional-SGT-VaR approach with alternative GARCH models. Annals of Operations Research.
9. Bali T.G., Cakici N., Yan X., and Zhang Z. Does idiosyncratic risk really matter?. Journal of Finance 60 (2005) 905-929
10. Bank for International Settlements, 2001. Working Paper on the Regulatory Treatment of Operational Risk, September.
11. Basak S., and Shapiro A. Value-at-risk-based risk management: Optimal policies and asset prices. Review of Financial Studies 14 (2001) 371-405
12. Black, F., 1976. Studies in stock price volatility changes. In: Proceedings of the 1976 Business Meeting of the Business and Economic Statistics Section, American Statistical Association, pp. 177-181.
13. Bollerslev T. Generalized autoregressive conditional heteroscedasticity. Journal of Econometrics 31 (1986) 307-327
14. Box G.E.P., and Tiao G.C. A further look at robustness via Bayes's theorem. Biometrica 49 (1962) 419-432
15. Campbell J.Y., Lettau M., Malkiel B.G., and Xu Y. Have individual stocks become more volatile? An empirical exploration of idiosyncratic risk. Journal of Finance 56 (2001) 1-43
16. Chernobai A., and Rachev S. Stable modelling of operational risk. In: Cruz M. (Ed). Operational Risk Modelling and Analysis: Theory and Practice (2004), Risk Books, London 139-170
17. Currie C.V. Basel II and operational risk - an overview. In: Cruz M. (Ed). Operational Risk Modelling and Analysis: Theory and Practice (2004), Risk Books, London 59-104
18. de Fontnouvelle, P., DeJesus-Rueff, V., Jordan, J., Rosengren, E., 2003. Capital and risk: new evidence on implications of large operational losses. Working Paper, Federal Reserve Bank of Boston.
19. Ebnother S., Vanini P., McNeil A., and Antolinez P. Operational risk: A practitioner's view. Journal of Risk 5 (2003) 1-15
20. Embrechts P., Kluppelberg C., and Mikosch T. Modeling Extremal Events (1997), Springer, Berlin
21. Engle R.F. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50 (1982) 987-1007
22. Fama E.F., and French K. Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33 (1993) 3-56
23. Glosten L.R., Jagannathan R., and Runkle D.E. On the relation between the expected value and the volatility of the nominal excess return on stocks. Journal of Finance 48 (1993) 1779-1801
24. Goyal A., and Santa-Clara P. Idiosyncratic risk matters!. Journal of Finance 58 (2003) 975-1008
25. Haas M., and Kaiser T. Tackling the insufficiency of loss data for the quantification of operational risk. In: Cruz M. (Ed). Operational Risk Modelling and Analysis: Theory and Practice (2004), Risk Books, London 13-24
26. Hansen B.E. Conditional density estimation. International Economic Review 35 (1994) 705-730
27. Hsieh D. Modeling heteroskedasticity in daily foreign exchange rates. Journal of Business and Economic Statistics 7 (1989) 307-317
28. Johnson N.L. Systems of frequency curves generated by methods of translation. Biometrica 36 (1949) 149-176
29. Kalhoff A., and Haas M. Operational risk - Management based on the current loss data situation. In: Cruz M. (Ed). Operational Risk Modelling and Analysis: Theory and Practice (2004), Risk Books, London 5-12
30. Kashyap, A.K., Stein, J.C., 2004. Cyclical implications of the Basel II capital standards. In: Economic Perspectives, Federal Reserve Bank of Chicago, First Quarter, pp. 18-31.
31. Kingsley S., Rolland A., Tinney A., and Holmes P. Operational risk and financial institutions: getting started. In: Andersen A. (Ed). Operational Risk and Financial Institutions (1998), Risk Books 3-28
32. Kodres L., and Pritsker M. A rational expectation model of financial contagion. Journal of Finance 57 (2002) 769-799
33. Kuritzkes A. Operational risk capital: A problem of definition. Journal of Risk Finance Fall (2002) 1-10
34. Kyle A., and Xiong W. Contagion as a wealth effect. Journal of Finance 56 (2001) 1401-1440
35. Leadbetter M.R., Lindgren G., and Rootzen H. Extremes and Related Properties of Random Sequences and Processes (1983), Springer-Verlag, New York
36. Longin F.M. The asymptotic distribution of extreme stock market returns. Journal of Business 69 (1996) 383-408
37. Longin F.M. From value at risk to stress testing: The extreme value approach. Journal of Banking and Finance 24 (2000) 1097-1130
38. Longin F.M., and Solnik B. Extreme correlation of international equity markets. Journal of Finance 56 (2001) 649-676
39. Lowe, P., 2002. Credit risk measurement and procyclicality. BIS Working Papers, No. 116, September 2002.
40. McDonald J.B., and Newey W.K. Partially adaptive estimation of regression models via the generalized t distribution. Econometric Theory 4 (1988) 428-457
41. McDonald J.B., and Xu Y.J. A generalization of the beta distribution with applications. Journal of Econometrics 66 (1995) 133-152
42. McNeil A.J., and Frey R. Estimation of tail-related risk measures for heteroscedastic financial time series: An extreme value approach. Journal of Empirical Finance 7 (2000) 271-300
43. Merton R.C. A simple model of capital market equilibrium with incomplete information. Journal of Finance 42 (1987) 483-510
44. Nelson D.B. Conditional heteroscedasticity in asset returns: A new approach. Econometrica 59 (1991) 347-370
45. Newey W.K., and West K.D. A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55 (1987) 703-708
46. Pickands J. Statistical inference using extreme order statistics. Annals of Statistics 3 (1975) 119-131
47. Resnick S.I. Extreme Values, Regular Variation, and Point Processes (1987), Springer-Verlag, NY
48. Rigobon R., and Forbes K. No contagion, only interdependence: Measuring stock market co-movements. Journal of Finance 57 (2002) 2223-2261
49. Ronn E., and Verma A. Pricing risk-adjusted deposit insurance: An option-based model. Journal of Finance (1986) 871-895
50. Shapiro A. The investor recognition hypothesis in a dynamic general equilibrium: Theory and evidence. Review of Financial Studies 15 (2002) 97-141
51. Subbotin M.T. On the law of frequency error. Matematicheskii Sbornik 31 (1923) 296-301
52. Theodossiou P. Financial data and the skewed generalized t distribution. Management Science 44 (1998) 1650-1661
53. Young, B., 1999. Raising the standard. Operational Risk Special Report, Risk, November, pp. 10-12.