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Processes with conditional stationary independent increments

Published online by Cambridge University Press:  14 July 2016

Richard F. Serfozo*
Affiliation:
Syracuse University

Abstract

We study a class of processes which are essentially processes with stationary independent increments whose basic parameters are allowed to vary randomly over time. These processes are equivalent to random time transformations of processes with stationary independent increments where the time process is independent of the original process. Several limiting theorems are presented including weak and strong laws of large numbers and a functional central limit theorem.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1972 

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References

[1] Albert, A. (1970) Optimally timing the sale of a stock when the tax man is breathing down your neck. Ann. Math. Statist. 41, 626641.Google Scholar
[2] Bartlett, M. S. (1963) The spectral analysis of point processes. J. R. Statist. Soc. B 25, 264296.Google Scholar
[3] Billingsley, P. (1968) Convergence of Probability Measures. John Wiley, New York.Google Scholar
[4] Breiman, L. (1968) Probability. Addison-Wesley, Reading, Massachusetts.Google Scholar
[5] Cootner, P. et al. (1964) The Random Character of Stock Market Prices. M. I. T. Press.Google Scholar
[6] Cox, D. R. (1955) Some statistical models connected with series of events. J. R. Statist. Soc. B 17, 129164.Google Scholar
[7] Cox, D. R. and Lewis, P. A. W. (1966) Statistical Analysis of Series of Events. Methuen, London.CrossRefGoogle Scholar
[8] Feller, W. (1966) An Introduction to Probability Theory and Its Applications, Vol. II. John Wiley, New York.Google Scholar
[9] Gaver, D. P. (1963) Random hazard in reliability problems. Technometrics 5, 211225.Google Scholar
[10] Iglehart, D. L. and Kennedy, D. P. (1970) Weak convergence of the average of flag processes. J. Appl. Prob. 7, 747753.CrossRefGoogle Scholar
[11] Kingman, J. F. C. (1964) On double stochastic Poisson processes. Proc. Camb. Phil. Soc. 60, 923930.Google Scholar
[12] Mandelbrot, B. and Taylor, H. (1967) On the distribution of stock price differences. Operat. Res. 15, 10571062.CrossRefGoogle Scholar
[13] Mcfadden, J. A. (1965) The mixed Poisson process. Sankhya A 27, 8392.Google Scholar
[14] Parzen, E. (1962) Stochastic Processes. Holden-Day, San Francisco.Google Scholar
[15] Serfozo, R. (1972) Conditional Poisson processes. J. Appl. Prob. 9, 288302.CrossRefGoogle Scholar
[16] Stam, A. J. (1966) Derived stochastic processes. Compositio Math. 17, 102140.Google Scholar