The General Theory of Stochastic Processes, Semimartingales and Stochastic Integrals

Author(s):  
Jean Jacod ◽  
Albert N. Shiryaev
2021 ◽  
pp. 724-756
Author(s):  
James Davidson

The main object of this chapter is to prove the convergence of the covariances of stochastic processes with their increments to stochastic integrals with respect to Brownian motion. Some preliminary theory is given relating to random functionals on C, stochastic integrals, and the important Itô isometry. The main result is first proved for the tractable special cases of martingale difference increments and linear processes. The final section is devoted to proving the more difficult general case, of NED functions of mixing processes.


2011 ◽  
Vol 11 (02n03) ◽  
pp. 389-413
Author(s):  
DARIO GASBARRA ◽  
JOSÉ IGOR MORLANES ◽  
ESKO VALKEILA

Enlargement of filtrations is a classical topic in the general theory of stochastic processes. This theory has been applied to stochastic finance in order to analyze models with insider information. In this paper we study initial enlargement in a Markov chain market model, introduced by Norberg. In the enlarged filtration, several things can happen: some of the jumps times can be accessible or predictable, but in the original filtration all the jumps times are totally inaccessible. But even if the jumps times change to accessible or predictable, the insider does not necessarily have arbitrage possibilities.


1983 ◽  
Vol 15 (1) ◽  
pp. 81-98 ◽  
Author(s):  
B. L. S. Prakasa Rao

Let be a continuous homogeneous stochastic process with independent increments. A review of the recent work on the characterization of Wiener and stable processes and connected results through stochastic integrals is presented. No proofs are given but appropriate references are mentioned.


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