Conditional value-at-risk: Aspects of modeling and estimation

Empirical Economics

Volumn 26, Issue 1, 2001, Pages 271-292

  Chernozhukov, Victor ^a   Umantsev, Len ^b  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b STANFORD UNIVERSITY   (United States)

Author keywords

Extreme value theory; Quantiles; Value at risk

Indexed keywords

FINANCIAL MARKET; METHODOLOGY; RISK ASSESSMENT;

EID: 0040759670     PISSN: 03777332     EISSN: None     Source Type: Journal    
DOI: 10.1007/s001810000062     Document Type: Article

References (29)

1. Ait-Sahalia Y, Lo AW (1998) Nonparametric risk management and implied risk aversion, preprint
2. Bassett G, Chen H (1999) Quantile style: Quantiles to assess mutual fund investment styles, a Working Paper, Presented at the International Conference on Economic Applications of Quantile Regression, Konstanz, 2000
3. Bassett Jr., G, Koenker R (1978) Asymptotic theory of least absolute error regression. J Amer Statist Assoc 73(363):618-622
4. Bierens H, Ginther DK (1999) Integrated conditional moment testing of quantile regression models, a Working Paper, Presented at the International Conference on Economic Applications of Quantile Regression, Konstanz, 2000
5. Campbell J, MacKinlay C, Lo A (1997) Econometrics of financial markets. MIT
6. Chernozhukov V (1999a) Conditional extremes and near-extremes. November, Ph.D. dissertation draft, Stanford
7. Chernozhukov V (1999b) Specification and other test processes for quantile regression. August, a Working Paper, Stanford
8. Christoffersen P (1998) Evaluating interval forecasts. International Economic Review 39(4):841-862
9. Crnkovic C, Drachman J (1996) Quality control. Risk 9(9):138-144
10. Dekkers ALM, de Haan L (1989) On the estimation of the extremevalue index and large quantile estimation. Ann. Statist 17(4):1795-1832
11. Diebold FX, Gunther TA, Tay AS (1998) Evaluating density forecasts with applications to financial risk management. International Economic Review 39(4):863-883
12. Engle RF, Manganelli S (1999) CAViaR: Conditional autoregressive value at risk by regression quantiles. UCSD Economics Deaprtment Working Paper 99-20, October
13. FedReg (1996) Risk-based capital standards: Market Risk vol. 61. Federal Register
14. Fitzenberger B (1998) The moving blocks bootstrap and robust inference for linear least squares and quantile regressions. J Econometrics 82(2):235-287
15. Heiler S, Abberger K (1999) Applications of nonparametric quantile regression to financial data, a Working Paper, Presented at the International Conference on Economic Applications of Quantile Regression, Konstanz, 2000
16. Hogg RV (1975) Estimates of percentile regression lines using salary data. J Amer Statist Assoc 70(349):56-59
17. Koenker R, Bassett GS (1978) Regression quantiles. Econometrica 46:33-50
18. Koenker R, Machado J (1999) Goodness of fit and related inference processes for quantile regression, preprint
19. Koenker R, Portnoy S (1997) The gaussian hare and the laplacian tortoise. Statistical Science 12:279-300
20. Koenker R, Portnoy S (1999) Regression quantiles, preprint
21. Koenker R, Zhao Q (1996) Conditional quantile estimation and inference for ARCH models. Econometric Theory 12(5):793-813
22. Lopez JA (1998) Regulatory evaluation of value-at-risk models. Journal of Risk 1(2):37-63
23. Politis DN, Romano JP (1994) The stationary bootstrap. J Amer Statist Assoc 89(428):1303-1313
24. Portnoy S (1991) Asymptotic behavior of regression quantiles in nonstationary, dependent cases. J Multivariate Anal 38(1):100-113
25. Resnick SI (1987) Extreme values, regular variation, and point processes. Springer-Verlag, New York-Berlin
26. Taylor J (1999) A quantile regression approach to estimating the distribution of multi-period returns. J Derivatives, Fall, 64-78
27. Umantsev L, Chernozhukov V (1999) Polynomial regression quantile modeling of risk. September, a Working Paper, Stanford.
28. van der Vaart AW, Wellner JA (1996) Weak convergence and empirical processes. Springer-Verlag, New York
29. Weiss AA (1991) Estimating nonlinear dynamic models using least absolute error estimation. Econometric Theory 47:47-66