Representations of continuoustime arma processes

Journal of Applied Probability

Volumn 41A, Issue , 2004, Pages 375-382

  Brockwell, Peter J ^a  

^a Department of Environmental and Radiological Health Sciences   (United States)

Author keywords

Continuous time ARMA process; Fractional integration; Long memory; L vy process; Stochastic volatility

Indexed keywords

EID: 25144432197     PISSN: 00219002     EISSN: None     Source Type: Journal    
DOI: 10.1239/jap/1082552212     Document Type: Article

References (7)

1. Anh, V. V., Heyde, C. C. and Leonenko, N. N. (2002). Dynamic models of long-memory processes driven by Levy noise. J. Appl. Prob. 39, 730-747.
2. Barndorff-Nielsen, O. E. and Shephard, N. (2001). Non-Gaussian Ornstein-Uhlenbeck-based models and some of their uses in financial economics. J. R. Statist. Soc. B 63, 167-241.
3. Brockwell, P. J. (2000). Heavy-tailed and non-linear continuous-time ARMA models for financial time series. In Statistics and Finance: An Interface, eds W. S. Chan, W. K. Li and H. Tong, Imperial College Press, London, pp. 3-22.
4. Brockwell, P. J. (2001). Levy-driven CARMAprocesses. Ann. Inst. Statist. Math. 53, 113-124.
5. Brockwell, P. J. and Davis, R. A. (1991). Time Series: Theory and Methods. Springer, NewYork.
6. Comte, F. and Renault, E. (1996). Long memory continuous time models. J. Econometrics 73, 101-149.
7. Doetsch, G. (1974). Introduction to the Theory and Application of the Laplace Transform. Springer, Berlin.