Estimation of the stochastic volatility model by the empirical characteristic function method

Australian and New Zealand Journal of Statistics

Volumn 44, Issue 3, 2002, Pages 319-335

  Knight, John L ^a   Satchell, Stephen E ^b   Yu, Jun ^b  

^a UNIVERSITY OF WESTERN ONTARIO   (Canada)

^b TRINITY COLLEGE   (United Kingdom)

Author keywords

Empirical characteristic function; Financial data; Stochastic volatility

Indexed keywords

EID: 0036021925     PISSN: 13691473     EISSN: None     Source Type: Journal    
DOI: 10.1111/1467-842X.00234     Document Type: Article

References (30)

1. Andersen, T. & Sorensen, B. (1996). GMM estimation of a stochastic volatility model: A Monte Carlo study. J. Bus. Econom. Statist. 14, 329-352.
2. Andersen, T., Bollerslev, T., Diebold, F. & Labys, P. (2001). The distribution of exchange rate volatility. J. Amer. Statist. Assoc. 96, 42-55.
3. Breidt, F.J., Crato, N. & De Lima, P. (1998). The detection and estimation of long memory in stochastic volatility. J. Econometrics 83, 325-348.
4. Chacko, G. & Viceira, L.M. (2001). Spectral GMM estimation of continuous-time processes. Working Paper, Harvard University, http://www.people.hbs.edu/lviceira/cf62.pdf.
5. Csörgo, S. (1981). Limit behaviour of the empirical characteristic function. Ann. Probab. 9, 130-144.
6. Danielsson, J. (1994). Stochastic volatility in asset prices: Estimation with simulated maximum likelihood. J. Econometrics 64, 375-400.
7. Duffie, D., Pan, J. & Singleton, K.J. (2000). Transform analysis and asset pricing for affine jump-diffusions. Econometrica 68, 1343-1376.
8. Durbin, J. (2000). The state space approach to time series analysis and its potential for official statistics (with discussion). Aust. N. Z. J. Stat. 42, 1-23.
9. Durbin, J. & Koopman, S.J. (2000). Time series analysis of non-Gaussian observations based on state space models from both classical and Bayesian perspectives (with discussion). J. Roy. Stat. Soc. Ser. B 62, 3-56.
10. Engle, R.F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50, 987-1007.
11. Feuerverger, A. (1990). An efficiency result for the empirical characteristic function in stationary time-series models. Canad. J. Statist. 18, 155-161.
12. Feuerverger, A. & Mureika, R.A. (1977). The empirical characteristic function and its applications. Ann. Statist. 5, 88-97.
13. Frühwirth-Schnatter, S. (1994). Applied state space modelling of non-Gassian time series using integration-based Kalman filtering. Statist. Comput. 4, 259-269.
14. Ghysels, E., Harvey, A.C. & Renault, E. (1996). Stochastic volatility. In Handbook of Statistics, Vol. 14, Statistical Methods in Finance, eds G.S. Maddala & C.R. Rao, pp. 119-191. Amsterdam: North-Holland.
15. Hansen, L.P. & Scheinkman, J.A. (1995). Back to future: Generating moment implications for continuous-time Markov processes. Econometrica 63, 767-804.
16. Harvey, A.C. (1998). Long memory in stochastic volatility. In Forecasting Volatility in the Financial Markets, eds J.L. Knight & S.E. Satchell, pp. 307-320. Oxford: Butterworth-Heineman.
17. Harvey, A.C., Ruiz, E. & Shephard, N. (1994). Multivariate stochastic variance models. Rev. Economic Stud. 61, 247-264.
18. Jacquier, E., Polson, N.G. & Rossi, P.E. (1994). Bayesian analysis of stochastic volatility models. J. Bus. Econom. Statist. 12, 371-389.
19. Jiang, G. & Knight, J.L. (2002). Estimation of continuous time processes via the empirical characteristic function. J. Bus. Econom. Statist. 12, 198-212.
20. Kim, S., Shephard, N. & Chib, S. (1998). Stochastic volatility: Likelihood inference and comparison with ARCH models. Rev. Economic Stud. 65, 361-393.
21. Knight, J.L. & Satchell, S.E. (1997). The cumulant generating function estimation method. Econom. Theory 13, 170-184.
22. Knight, J.L. & Yu, J. (2002). The empirical characteristic function in time series estimation. Econom. Theory 18, 691-721.
23. Melino, A. & Turnbull, S.M. (1990). Pricing foreign currency options with stochastic volatility. J. Econometrics 45, 239-265.
24. Nelson, D.B. (1988). Time Series Behavior of Stock Market Volatility and Returns. PhD Dissertation, Massachusetts Institute of Tehnology.
25. Powell, M.J.D. (1964). An efficient method for finding the minimum of a function of several variables without calculating derivatives. Comput. J. 7, 155-162.
26. Quandt, R.E. & Ramsey, J.B. (1978). Estimating mixtures of normal distributions and switching regressions. J. Amer. Statist. Assoc. 73, 730-738.
27. Ruiz, E. (1994). Quasi-maximum likelihood estimation of stochastic volatility models. J. Econometrics 63, 289-306.
28. Singleton, K.J. (2001). Estimation of affine asset pricing models using the empirical characteristic function. J. Econometrics 102, 111-141.
29. Tran, K.C. (1998). Estimating mixtures of normal distributions via empirical characteristic function. Econom. Rev. 17, 167-83.
30. Yu, J. (1998). The Empirical Characteristic Function in Time-Series Estimation. PhD Dissertation, The University of Western Ontario.