Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-24T02:46:55.986Z Has data issue: false hasContentIssue false

An Exponential Continuous-Time GARCH Process

Published online by Cambridge University Press:  14 July 2016

Stephan Haug*
Affiliation:
Munich University of Technology
Claudia Czado*
Affiliation:
Munich University of Technology
*
Postal address: Center for Mathematical Sciences, Munich University of Technology, D-85747 Garching, Germany.
Postal address: Center for Mathematical Sciences, Munich University of Technology, D-85747 Garching, Germany.
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In this paper we introduce an exponential continuous-time GARCH(p, q) process. It is defined in such a way that it is a continuous-time extension of the discrete-time EGARCH(p, q) process. We investigate stationarity, mixing, and moment properties of the new model. An instantaneous leverage effect can be shown for the exponential continuous-time GARCH(p, p) model.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 2007 

References

[1] Applebaum, D. (2004). Lévy Processes and Stochastic Calculus. Cambridge University Press.CrossRefGoogle Scholar
[2] Bertoin, J. (1996). Lévy Processes. Cambrige University Press.Google Scholar
[3] Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. J. Econometrics 31, 307327.CrossRefGoogle Scholar
[4] Brockwell, P. J. (2001). Lévy driven CARMA processes. Ann. Inst. Statist. Math. 53, 113124.CrossRefGoogle Scholar
[5] Brockwell, P. J. and Marquardt, T. (2005). Lévy-driven and fractionally integrated ARMA processes with continuous time parameter. Statist. Sinica 15, 477494.Google Scholar
[6] Brockwell, P. J., Chadraa, E. and Lindner, A. M. (2006). Continuous time GARCH processes. Ann. Appl. Prob. 16, 790826.CrossRefGoogle Scholar
[7] Davydov, Y. A. (1973). Mixing conditions for Markov chains. Theory Prob. Appl. 18, 312328.CrossRefGoogle Scholar
[8] Doukhan, P. (1994). Mixing: Properties and Examples (Lecture Notes Statist. 85). Springer, New York.CrossRefGoogle Scholar
[9] Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of UK inflation. Econometrica 50, 9871008.CrossRefGoogle Scholar
[10] Giraitis, L., Leipus, R., Robinson, P. M. and Surgailis, D. (2004). LARCH, leverage, and long memory. J. Financial Econometrics 2, 177210.CrossRefGoogle Scholar
[11] Haug, S. and Czado, C. (2006). A fractionally integrated ECOGARCH process. Discussion paper 484, SFB386.Google Scholar
[12] Haug, S., Klüppelberg, C., Lindner, A. M. and Zapp, M. (2007). Method of moment estimation in the COGARCH}(1,1) model. Econometrics J. 10, 320341.CrossRefGoogle Scholar
[13] Klüppelberg, C., Lindner, A. and Maller, R. (2004). A continuous time GARCH process driven by a Lévy process: stationarity and second-order behaviour. J. Appl. Prob. 41, 601622.CrossRefGoogle Scholar
[14] Kusuoka, S. and Yoshida, N. (2000). Malliavin calculus, geometric mixing, and expansion of diffusion functionals. Prob. Theory Relat. Fields 116, 457484.CrossRefGoogle Scholar
[15] Masuda, H. (2004). On multidimensional Ornstein–Uhlenbeck processes driven by a general Lévy process. Bernoulli 10, 97120.CrossRefGoogle Scholar
[16] Masuda, H. (2005). Classical method of moments for partially and discretely observed ergodic models. Statist. Infer. Stoch. Process. 8, 2550.CrossRefGoogle Scholar
[17] McLeish, D. L. (1975). Invariance principles for dependent variables. Z. Wahrscheinlichkeitsth. 32, 165175.CrossRefGoogle Scholar
[18] Nelson, D. B. (1990). ARCH models as diffusion approximations. J. Econometrics 45, 738.CrossRefGoogle Scholar
[19] Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: a new approach. Econometrica 59, 347370.CrossRefGoogle Scholar
[20] Rajput, B. S. and Rosiński, J. (1989). Spectral representations of infinitely divisible processes. Prob. Theory Relat. Fields 82, 451487.CrossRefGoogle Scholar
[21] Robinson, P. M. (1991). Testing for strong serial correlation and dynamic conditional heteroskedasticity in multiple regression. J. Econometrics 47, 6784.CrossRefGoogle Scholar
[22] Sato, K. (1999). Lévy Processes and Infinitely Divisible Distributions. Cambridge University Press.Google Scholar
[23] Surgailis, D. and Viano, M. C. (2002). Long memory properties and covariance structure of the EGARCH model. ESAIM Prob. Statist. 6, 311329.CrossRefGoogle Scholar