TAILIEUCHUNG - On discrete approximation of occupation time of diffusion processes with irregular sampling

Thus, in this paper, we will construct an estimation scheme for Γ(A) based on an irregular sample {Xti, i = 0, 1, . . .} of X and study its asymptotic behavior. In particular, we first introduce an unbiased estimator for when X is a standard Brownian motion and provide a functional central limit theorem (Theorem ) for the error process. | JOURNAL OF SCIENCE OF HNUE Interdisciplinary Science 2014 Vol. 59 No. 5 pp. 3-16 This paper is available online at http ON DISCRETE APPROXIMATION OF OCCUPATION TIME OF DIFFUSION PROCESSES WITH IRREGULAR SAMPLING Nguyen Thi Lan Huong Ngo Hoang Long and Tran Quang Vinh Faculty of Mathematics and Informatics Hanoi National University of Education Abstract. Let X be a diffusion processes and A be some Borel subsetR of R. In this t paper we introduce an estimator for the occupation time Γ A t 0 I Xs A ds based on an irregular sample of X and study its asymptotic behavior. Keywords Occupation time diffusion processes irregular sample. 1. Introduction Let X be a solution to the following stochastic differential equation dXt b Xt dt σ Xt dWt X0 x0 R where b and σ are measurable functions and Wt is a standard Brownian motion defined on a filtered probability space Ω F Ft t gt 0 P . For each set A B R the occupation time of X in A is defined by Z t Γ A t I Xs A ds. 0 The quantity Γ A is the amount of time the diffusion X spends on set A. The problem of evaluating Γ A is very important in many applied domains such as mathematical finance queueing theory and biology. For example in mathematical finance these quantities are of great interest for the pricing of many derivatives such as Parisian corridor and Eddoko options see 1 2 9 . In practice one cannot observe the whole trajectory of X during a fixed interval. In other words we can only collect the values of X at some discrete times say 0 t1 lt t2 lt . . . Recently Ngo and Ogawa 10 and Kohatsu-Higa et al. 7 have introduced an estimate for Γ A by using a Riemann sum and they studied the rate of convergence of this i approximation when X is observed at regular points . ti i 6 nt for all i gt 0 n Received December 25 2013. Accepted June 26 2014. Contact Nguyen Thi Lan Huong e-mail address nguyenhuong0011@ 3 Nguyen Thi Lan Huong Ngo Hoang Long and Tran Quang Vinh and any n gt 0. However in .

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