Asymmetric multivariate normal mixture GARCH

Computational Statistics and Data Analysis

Volumn 53, Issue 6, 2009, Pages 2129-2154

  Haas, Markus ^a   Mittnik, Stefan ^a,b,c   Paolella, Marc S ^d  

^a UNIVERSITY OF MUNICH   (Germany)

^b Center for Financial Studies   (Germany)

^c IFO INSTITUTE   (Germany)

^d UNIVERSITY OF ZURICH   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

RISK ASSESSMENT;

DISAGGREGATION; DYNAMIC CORRELATIONS; GARCH MODELS; MULTIVARIATE NORMALS; NORMAL MIXTURES; PARAMETRIZATION; STATIONARITY; STOCK MARKETS; VALUE AT RISKS;

RISK PERCEPTION;

EID: 61549116920     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2007.12.018     Document Type: Article

References (61)

1. Akaike H. Information theory and an extension of the maximum likelihood principle. In: Petrov B.N., and Csaki F. (Eds). 2nd International Symposium on Information Theory (1973), Akademiai Kiado, Budapest 267-281
2. Alexander C. Orthogonal GARCH. Mastering Risk vol. 2 (2001), FT Prentice Hall, London 21-38
3. Alexander C. Principal component models for generating large GARCH covariance matrices. Economic Notes 31 (2002) 337-359
4. Alexander, C., Chibumba, A.M., 1997. Multivariate Orthogonal Factor GARCH. Mimeo, University of Sussex
5. Alexander, C., Lazar, E., 2005. Asymmetries and Volatility Regimes in the European Equity Market. ICMA Centre Discussion Papers in Finance 2005-14, The Business School for Financial Markets at the University of Reading
6. Alexander C., and Lazar E. Normal mixture GARCH(1, 1). Applications to exchange rate modelling. Journal of Applied Econometrics 21 (2006) 307-336
7. Ané T. An analysis of the flexibility of asymmetric power GARCH models. Computational Statistics and Data Analysis 51 (2006) 1293-1311
8. Ang A., and Chen J. Asymmetric correlations of equity portfolios. Journal of Financial Economics 63 (2002) 443-494
9. Ausin M.C., and Galeano P. Bayesian estimation of the Gaussian mixture GARCH model. Computational Statistics and Data Analysis 51 (2007) 2636-2652
10. Balestra, P., Holly, A., 1990. A General Kronecker Formula for the Moments of the Multivariate Normal Distribution. Cahiers de recherches économiques 9002, Département d'économétrie et d'économie politique, Université de Lausanne
11. Bauwens L., Hafner C.M., and Rombouts J.V.K. Multivariate mixed normal conditional heteroskedasticity. Computational Statistics and Data Analysis 51 (2007) 3551-3566
12. Bauwens L., Laurent S., and Rombouts J.V.K. Multivariate GARCH models: A survey. Journal of Applied Econometrics 21 (2006) 79-109
13. Bauwens L., and Rombouts J.V.K. Bayesian inference for the mixed conditional heteroskedasticity model. Econometrics Journal 10 (2007) 408-425
14. Bauwens, L., Storti, G., 2007. A Component GARCH Model with Time-varying Weights. CORE Discussion Paper 2007/19, Center for Operations Research and Econometrics, Université Catholique de Louvain
15. Bertholon, H., Monfort, A., Pegoraro, F., 2006. Pricing and Inference with Mixtures of Conditionally Normal Processes. Working paper, Centre de Recherche en Economie et Statistique (CREST), Laboratoire der Finance-Assurance
16. Bollerslev T. Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics 31 (1986) 307-327
17. Bollerslev T., and Engle R.F. Common persistence in conditional variances. Econometrica 61 (1993) 167-186
18. Broto C., and Ruiz E. Unobserved component models with asymmetric conditional variances. Computational Statistics and Data Analysis 50 (2006) 2146-2166
19. Cappiello L., Engle R.F., and Sheppard K. Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics 4 (2006) 537-572
20. Christoffersen P.F. Evaluating interval forecasts. International Economic Review 4 (1998) 841-862
21. Christoffersen P.F., and Pelletier D. Backtesting value-at-risk: A duration-based approach. Journal of Financial Econometrics 2 (2004) 84-108
22. Cohen A.C. Estimation in mixtures of two normal distributions. Technometrics 9 (1967) 15-28
23. Diebold F.X., Hahn J., and Tay A.S. Multivariate density forecast evaluation and calibration in financial risk management: High-frequency returns on foreign exchange. Review of Economics and Statistics 81 (1999) 661-673
24. Ding Z., and Granger C.W.J. Modeling volatility persistence of speculative returns: A new approach. Journal of Econometrics 73 (1996) 185-215
25. Ding Z., Granger C.W.J., and Engle R.F. A long memory property of stock market returns and a new model. Journal of Empirical Finance 1 (1993) 83-106
26. Dufour J.-M. Monte Carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics. Journal of Econometrics 133 (2006) 443-477
27. Engle R.F. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50 (1982) 987-1008
28. Engle R.F. Stock volatility and the crash of '87: Discussion. Review of Financial Studies 3 (1990) 103-106
29. Engle R.F., and Kroner K.F. Multivariate simultaneous generalized ARCH. Econometric Theory 11 (1995) 122-150
30. Fama E.F. Foundations of Finance (1976), Basic Books, New York
31. Giannikis D., Vrontos I.D., and Dellaportas P. Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models. Computational Statistics and Data Analysis 52 (2008) 1549-1571
32. Haas M. Improved duration-based backtesting of value-at-risk. Journal of Risk 8 (2006) 17-38
33. Haas M. Volatility components and long memory-effects revisited. Studies in Nonlinear Dynamics & Econometrics 11 2 (2007) Article 3
34. Haas M., Mittnik S., and Paolella M.S. Mixed normal conditional heteroskedasticity. Journal of Financial Econometrics 2 (2004) 211-250
35. Haas M., Mittnik S., and Mizrach B. Assessing central bank credibility during the EMS crises: Comparing option and spot market-based forecasts. Journal of Financial Stability 2 (2006) 28-54
36. Haas, M., Mittnik, S., Paolella, M.S., 2006b. Multivariate Normal Mixture GARCH. CFS Working Paper 2006/9. Center for Financial Studies
37. Hafner C.M. Fourth moment structure of multivariate GARCH models. Journal of Financial Econometrics 1 (2003) 26-54
38. Jorion P. Fallacies about the effects of market risk management systems. Journal of Risk 5 (2002) 75-96
39. JP Morgan, 1996. RiskMetrics-Technical Document. New York
40. Kass R.E., and Raftery A.E. Bayes factors. Journal of the American Statistical Association 90 (1995) 773-795
41. Kiefer N.M. Economic duration data and hazard functions. Journal of Economic Literature 26 (1988) 646-679
42. Kupiec P.H. Techniques for verifying the accuracy of risk management models. Journal of Derivatives 3 (1995) 73-84
43. Lopez J.A. Regulatory evaluation of value-at-risk models. Journal of Risk 1 (1999) 37-64
44. Loudon G.F., Watt W.H., and Yadav P.K. An empirical analysis of alternative parametric ARCH models. Journal of Applied Econometrics 15 (2000) 117-136
45. Magnus J.R. Linear Structures (1988), Griffin, London
46. Magnus J.R., and Neudecker H. The commutation matrix: Some properties and applications. Annals of Statistics 7 (1979) 381-394
47. Maheu J. Can GARCH models capture long-range dependence?. Studies in Nonlinear Dynamics & Econometrics 9 4 (2005) Article 1
48. McLachlan G.J., and Peel D. Finite Mixture Models (2000), John Wiley & Sons, New York
49. Nakagawa T., and Osaki S. The discrete weibull distribution. IEEE Transactions on Reliability 24 (1975) 300-301
50. Patton A.J. On the out-of-sample importance of skewness and asymmetric dependence for asset allocation. Journal of Financial Econometrics 2 (2004) 130-168
51. Rohatgi V.K. An Introduction to Probability Theory and Mathematical Statistics (1976), John Wiley and Sons, New York
52. Ruppert D. What is kurtosis? An influence function approach. American Statistician 41 (1987) 1-5
53. Schwarz G. Estimating the dimension of a model. Annals of Statistics 6 (1978) 461-464
54. Sentana E. Quadratic ARCH models. Review of Economic Studies 62 (1995) 639-661
55. Silverman B.W. Density Estimation for Statistics and Data Analysis (1986), Chapman & Hall, London
56. Teicher H. Identifiability of finite mixtures. Annals of Mathematical Statistics 34 (1963) 1265-1269
57. Vlaar P.J.G., and Palm F.C. The message in weekly exchange rates in the European monetary system: Mean reversion, conditional heteroscedasticity, and jumps. Journal of Business and Economic Statistics 11 (1993) 351-360
58. Wilkins J.E. A note on skewness and kurtosis. Annals of Mathematical Statistics 15 (1944) 333-335
59. Wong C.S., and Li W.K. On a mixture autoregressive conditional heteroscedastic model. Journal of the American Statistical Association 96 (2001) 982-985
60. Wu C., and Lee J.C. Estimation of a utility-based asset pricing model using normal mixture GARCH(1, 1). Economic Modelling 24 (2007) 329-349
61. Yakowitz S.J., and Spragins J.D. On the identifiability of finite mixtures. Annals of Mathematical Statistics 39 (1968) 209-214