Indirect inference methods for stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck processes

Computational Statistics and Data Analysis

Volumn 56, Issue 11, 2012, Pages 3260-3275

  Raknerud, Arvid ^a   Skare, Oivind ^b,c  

^a STATISTICS NORWAY   (Norway)

^b NORWEGIAN INSTITUTE OF PUBLIC HEALTH   (Norway)

^c UNIVERSITY OF BERGEN   (Norway)

Author keywords

Asymptotic variance; Exchange rate data; Indirect inference; Ornstein Uhlenbeck process; Quasi likelihood estimation; Simulation study; Stochastic volatility model

Indexed keywords

ASYMPTOTIC VARIANCE; EXCHANGE RATES; INDIRECT INFERENCE; ORNSTEIN-UHLENBECK PROCESS; QUASI-LIKELIHOOD; SIMULATION STUDIES; STOCHASTIC VOLATILITY MODEL;

ASYMPTOTIC ANALYSIS; ECONOMIC ANALYSIS; ESTIMATION; FINANCE; GAUSSIAN NOISE (ELECTRONIC); MEAN SQUARE ERROR; STABILITY CRITERIA; STATE SPACE METHODS;

COMPUTER SIMULATION;

EID: 84862010472     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2011.01.014     Document Type: Article

References (36)

1. T.G. Andersen, T. Bollerslev, F.X. Diebold, and P. Labys The distribution of realized exchange rate volatility Journal of the American Statistical Association 96 2001 42 55
2. T.G. Andersen, R.A. Davis, J.-P. Kreiss, and T. Mikosch Handbook of Financial Time Series 2009 Springer Berlin
3. T.G. Andersen, and J. Lund Estimating continuous time stochastic volatility models of the short term interest rate Journal of Econometrics 77 1997 343 378
4. O.E. Barndorff-Nielsen, T. Mikosch, and S.I. Resnick Lévy Processes: Theory and Applications 2001 Birkhäuser Boston
5. O.E. Barndorff-Nielsen, and N. Shephard Non-Gaussian Ornstein-Uhlenbeck- based models and some of their uses in financial economics Journal of the Royal Statistical Society, Series B. Statistical Methodology 63 Part 2 2001 167 207
6. O.E. Barndorff-Nielsen, and N. Shephard Econometric analysis of realized volatility and its use in estimating stochastic volatility models Journal of the Royal Statistical Society, Series B. Statistical Methodology 64 Part 2 2002 253 280
7. O.E. Barndorff-Nielsen, and N. Shephard Integrated OU processes and non-Gaussian OU-based stochastic volatility models Scandinavian Journal of Statistics 30 2003 277 295
8. L. Bondesson On the Levy measure of the lognormal and the log Cauchy distributions Methodology and Computing in Applied Probability 4 2002 243 256
9. Bolviken, E.; Benth, F.E.; 2000. Quantification of risk in Norwegian stocks via the normal inverse Gaussian distribution. In: Proceedings AFIR 2000 Colloquium. Tromso, Norway. pp. 87-98.
10. T. Bollerslev, R.F. Engle, and D.B. Nelson ARCH models R.F. Engle, D.L. McFadden, Handbook of Econometrics vol. 4 1994 North-Holland Amsterdam 2959 3038
11. R.P. Brent Algorithms for Minimization Without Derivatives 1973 Prentice-Hall Englewood Cliffs
12. L. Broze, O. Scaillet, and J.-M. Zakoian Quasi-indirect inference for diffusion processes Econometric Theory 14 1998 161 186
13. G. Calzolari, F. De Iori, and G. Fiorentini Control variants for variance reduction in indirect inference: interest rate models in continuous time Econometrics Journal 1 1998 C100 C112
14. F.X. Diebold Empirical Modeling of Exchange Rate Dynamics 1988 Springer New York
15. F.X. Diebold, and M. Nerlove The dynamics of exchange rate volatility: a multivariate latent factor ARCH model Journal of Applied Econometrics 4 1989 1 21
16. F.C. Drost, and T.E. Nijman Temporal aggregation of GARCH processes Econometrica 61 1993 909 927
17. R.F. Engle Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation Econometrica 50 1982 987 1007
18. A.R. Gallant, and J.R. Long Estimating stochastic differential equations efficiently by minimum chi-square Biometrika 84 1997 125 141
19. A.R. Gallant, and G. Tauchen Which moments to match? Econometric Theory 12 1996 657 681
20. C. Gourieroux, A. Monfort, and E. Renault Indirect inference Journal of Applied Econometrics 8 Suppl. 1993 S85 S118
21. J.E. Griffin, and M.F.J. Steel Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility Journal of Econometrics 134 2006 605 644
22. J.E. Griffin, and M.F.J. Steel Bayesian inference with stochastic volatility models using continuous superpositions of non-Gaussian Ornstein-Uhlenbeck processes Computational Statistics and Data Analysis 54 2010 2594 2608
23. A.C. Harvey, S.J. Koopman, and N. Shephard State Space and Unobserved Component Models: Theory and Applications 2004 Cambridge University Press Cambridge
24. A.C. Harvey, E. Ruiz, and N. Shephard Multivariate stochastic variance models Review of Economic Studies 61 1994 247 264
25. K. Heggland, and A. Frigessi Estimating functions in indirect inference Journal of the Royal Statistical Society, Series B. Statistical Methodology 66 2004 447 462
26. E. Jondeau, S.-H. Poon, and M. Rockinger Financial Modeling Under Non-Gaussian Distributions 2007 Springer New York
27. A.Y.C. Kuk Asymptotically unbiased estimation in generalized linear models with random effects Journal of the Royal Statistical Society, Series B. Statistical Methodology 57 1995 395 407
28. R. MacDonald Exchange rate behaviour: are fundamentals important? The Economic Journal 109 1999 673 691
29. R. Meese, and K. Rogoff The out-of-sample failure of empirical exchange rate models: sampling error or misspecification? Frenkel J.A.; Exchange Rates and International Macroeconomics 1983 National Bureau of Economic Research 67 112
30. E. Nicolato, and E. Venardos Option pricing in stochastic volatility models of the Ornstein-Uhlenbeck type Mathematical Finance 13 2003 445 466
31. S. Pastorello, E. Renault, and N. Touzi Statistical inference for random-variance option pricing Journal of Business and Economic Statistics 18 2000 358 367
32. W.H. Press, S.A. Teukolsky, W.T. Vetterling, and B.P. Flannery Numerical Recipes in C 1994 Cambridge University Press Cambridge
33. Sanderson, A.; 2010. Armadillo: an open source C++ linear algebra library for fast prototyping and computationally intensive experiments. NICTA Technical Report.
34. N. Shephard Stochastic Volatility: Selected Readings 2005 Oxford University Press Oxford
35. H. Sorensen Parametric inference for diffusion processes observed at discrete points in time: a survey Journal of Statistical Review 3 2004 337 354
36. E. Taufer, and N. Leonenko Simulations of Levy-driven Ornstein-Uhlenbeck processes with given marginal distributions Computational Statistics and Data Analysis 53 2009 2427 2437