Subsampling for heteroskedastic time series

Journal of Econometrics

Volumn 81, Issue 2, 1997, Pages 281-317

  Politis, D N ^a   Romano, Joseph P ^b   Wolf, Michael ^b  

^a PURDUE UNIVERSITY   (United States)

^b STANFORD UNIVERSITY   (United States)

Author keywords

Heteroskedasticity; Moving blocks bootstrap; Subsampling; Time series

Indexed keywords

EID: 0001232820     PISSN: 03044076     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-4076(97)86569-4     Document Type: Article

References (46)

1. Andrews, D.W.K., 1991. Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica 59, 817-858.
2. Andrews, D.W.K., Monahan, J.C., 1992. An improved heteroskedasticity and autocorrelation consistent covariance matrix estimator. Econometrica 60, 953-966.
3. Babu, G.J., 1986. Bootstrapping statistics with linear combinations of Chi-squares as weak limrm. Sankhya Ser A. 56, 85-93.
4. Beran, R., 1984. Bootstrap methods in statistics. Jber. d. Dt. Math.-Vereins 86, 14-30.
5. Bernstein, S., 1927. Sur l'extension du théorème du calcul des probabilités aux sommes de quantités dependantes. Mathematische Annalen 97, 1-59.
6. Billingsley, P., 1968. Convergence of Probability Measures. John Wiley, New York.
7. Billingsley, P., 1986. Probability and Measure, 2nd ed. Wiley, New York.
8. Black, F., Scholes, M., 1973. The pricing of options and corporate liabilities. Journal of Political Economy 81, 637-654.
9. Bose, A., 1988. Edgeworth correction by bootstrap in autoregressions. Annals of Statistics 14, 1709-1722.
10. Bühlmann, P., 1994. Blockwise bootstrapped empirical process for stationary sequences. Annals of Statistics 22, 995-1012.
11. Bühlmann, P., Künsch, H.R., 1994. Block length selection in the bootstrap for time series. Tech. Report Nr. 72, Seminar für Statistik, ETH Zürich.
12. Campbell, J.Y., Lo, A.W., MacKinlay, A.C., 1995. The econometrics of financial markets. Manuscript.
13. Carlstein, E., 1986. The use of subseries methods for estimating the variance of a general statistic from a stationary time series. Annals of Statistics 14, 1171-1179.
14. Davydov, Y.A., 1970. The invariance principle for stationary processes. Theory of Probability Application 14, 487-498.
15. Doukhan, P., 1994. Mixing: properties and examples. Lecture Notes in Statistics, Vol. 85, Springer, New York.
16. Efron, B., 1979. Bootstrap methods: another look at the jacknife. Annals of Statistics 7, 1-26.
17. Efron, B., Tibshirani, R.J., 1993. An Introduction to the Bootstrap. Chapman & Hall, New York.
18. Fitzenberger, B., 1995. The moving blocks bootstrap and robust inference for linear least squares and quantile regressions. Unpublished discussion paper, Universität Konstanz.
19. Frank, J., Härdie, W., 1992. On bootstrapping kernel spectral estimates. The Annals of Statistics, 20, 121-145.
20. Freedman, D.A., 1981. Bootstrapping regression models. Annals of Statistics 9, 1218-1228.
21. Freedman, D.A., 1984. On bootstrapping two-stage least-squares estimates in stationary linear models. Annals of Statistics 12, 827-842.
22. Hall, P., 1988. On symmetric bootstrap confidence intervals. Journal Royal Statistical Society B 50 (1) 35-45.
23. Hall, P., 1992. The Bootstrap and Edgeworth Expansion, Springer, New York.
24. Hall, P., Heyde, C.C., 1980. Martingale Limit Theory and its Application. Academic Press, New York.
25. Hall, P., Horowitz J.L., Jing, B., 1995. On blocking rules for the bootstrap with dependent data. Biometrika, to appear.
26. Ibragimov, I.A., 1962. Some limit theorems for stationary processes, Theory of Probabilistic Applications 4, 349-382.
27. Künsch, H.R., 1989. The jackknife and the bootstrap for general stationary observations. Annals of Statistics 17, 1217-1241.
28. Lahiri, S.N., 1992. Edgeworth correction by 'Moving block' bootstrap for stationary and nonstationary data. In Exploring the Limits of Bootstrap, pp. 183-214. John Wiley, New York.
29. Liu, R.Y., 1988. Bootstrap procedures under some non-iid models. Annals of Statistics 16, 1696-1708.
30. Liu, R.Y., Singh, K., 1992. Moving blocks jackknife and bootstrap capture weak dependence. In: LePage and Billard (Eds.), Exploring the limits of bootstrap Wiley, New York.
31. Lo, A.W., MacKinley, A.C., 1988. Stock market prices do not follow random walks: Evidence from a simple specificaton test. Review of Financial Studies 1, 41-66.
32. Loh, W.-Y., 1987. Calibrating confidence coefficients. Journal of American Statistical Association 82, 155-162.
33. Malliaropulos, D., 1996. Are long-horizon stock returns predictable? A bootstrap analysis. Journal of Business Finance and Accounting 23(1) 93-106.
34. Oodaira, H., Yoshihara, K., 1972. Functional central limit theorems for strictly stationary processes satisfying the strong mixing condition. Kodai Math. Seminar Report 24, 259-269.
35. Politis, D., Romano, J., 1992. A general resampling scheme for triangular arrays of α-mixing random variables with application to the problem of spectral density estimation. Annals of Statistics 20, 1985-2007.
36. Politis, D., Romano, J., 1994a. The stationary bootstrap. Journal of American Statistics Ass. 89, 1303-1313.
37. Politis, D., Romano, J., 1994b. Large sample confidence regions based on subsamples under minimal assumptions. Annals of Statistics 22, 2031-2050.
38. Politis, D., Romano, J., Wolf, M., 1995. Subsampling for nonstationary time series. Technical Report No. 483, Department of Statistics, Stanford University.
39. Rosenblatt, M., 1956. A central limit theorem and a strong mixing condition. Proceedings of National Academy of Science 42, 43-47.
40. Serfling, R.J., 1968. Contributions to central limit theory for dependent variables. Annals of Mathematics and Statistics 39, 1158-1175.
41. Singh, K., 1981. On the asymptotic accuracy of Efron's bootstrap. Annals of Statistics 9, 1187-1195.
42. Uteev, S., 1984. Inequalities and estimates of the convergence rate for the weakly dependent case. Advances in Probabilistics Theory 1985, Novosibirsk.
43. White, H., 1984. Asymptotic Theory for Econometricians. Academic Press, Orlando.
44. White, H., Domowitz I., 1984. Nonlinear regression with dependent observations. Econometrica 52, 143-161.
45. Wolkonoski, V.A., Rozanov, Y.A., 1959. Some limit theorems for random functions, Part I. Theory of Probabilistic Applications 4, 178-197.
46. Wu, C.F., 1986. Jacknife, bootstrap and other resampling methods in regression analysis. Annals of Statistics 14, 1261-1343.