• Title/Summary/Keyword: Brownian processes

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THE EXISTENCE OF PRODUCT BROWNIAN PROCESSES

  • Kwon, Joong-Sung
    • Journal of the Korean Mathematical Society
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    • v.33 no.2
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    • pp.319-332
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    • 1996
  • Many authors have studied multiple stochastic integrals in pursuit of the existence of product processes in terms of multiple integrals. But there has not been much research into the structure of the product processes themselves. In this direction, a study which gives emphasis on sample path continuity and boundedness properties was initiated in Pyke[9]. For details of problem set-ups and necessary notations, see [9]. Recently the weak limits of U-processes are shown to be chaos processes, which is product of the same Brownian measures, see [2] and [7].

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ON ESTIMATES OF POISSON KERNELS FOR SYMMETRIC LÉVY PROCESSES

  • Kang, Jaehoon;Kim, Panki
    • Journal of the Korean Mathematical Society
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    • v.50 no.5
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    • pp.1009-1031
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    • 2013
  • In this paper, using elementary calculus only, we give a simple proof that Green function estimates imply the sharp two-sided pointwise estimates for Poisson kernels for subordinate Brownian motions. In particular, by combining the recent result of Kim and Mimica [5], our result provides the sharp two-sided estimates for Poisson kernels for a large class of subordinate Brownian motions including geometric stable processes.

A NOTE ON FUNCTIONAL LIMIT THEOREM FOR THE INCREMENTS OF FBM IN SUP-NORM

  • Hwang, Kyo-Shin
    • East Asian mathematical journal
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    • v.24 no.3
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    • pp.275-287
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    • 2008
  • In this paper, using large deviation results for Gaussian processes, we establish some functional limit theorems for increments of a fractional Brownian motion in the usual sup-norm via estimating large deviation probabilities for increments of a fractional Brownian motion.

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Experimental Study on Brownian Coagulation in the Transition Regime (전이영역에서의 Brown 응집에 관한 실험적 연구)

  • Kim Dae-Seong;Lee Gyu-Won
    • Proceedings of the Korea Air Pollution Research Association Conference
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    • 2003.05b
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    • pp.355-356
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    • 2003
  • Coagulation is a process whereby particles collide with one another due to their relative motion, and adhere to form large particles. Coagulation caused by the random Brownian motion of particles is called Brownian coagulation. Many properties, such as light scattering, electrostatic charges, toxicity, as well as physical processes, including diffusion, condensation and thermophoresis depend strongly on their size distribution. Therefore, Brownian coagulation is substantially important in atmospheric science, combustion technology, inhalation toxicology and nuclear safety analysis. (omitted)

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RESIDUAL EMPIRICAL PROCESS FOR DIFFUSION PROCESSES

  • Lee, Sang-Yeol;Wee, In-Suk
    • Journal of the Korean Mathematical Society
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    • v.45 no.3
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    • pp.683-693
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    • 2008
  • In this paper, we study the asymptotic behavior of the residual empirical process from diffusion processes. For this task, adopting the discrete sampling scheme as in Florens-Zmirou [9], we calculate the residuals and construct the residual empirical process. It is shown that the residual empirical process converges weakly to a Brownian bridge.

ON THE GOODNESS OF FIT TEST FOR DISCRETELY OBSERVED SAMPLE FROM DIFFUSION PROCESSES: DIVERGENCE MEASURE APPROACH

  • Lee, Sang-Yeol
    • Journal of the Korean Mathematical Society
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    • v.47 no.6
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    • pp.1137-1146
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    • 2010
  • In this paper, we study the divergence based goodness of fit test for partially observed sample from diffusion processes. In order to derive the limiting distribution of the test, we study the asymptotic behavior of the residual empirical process based on the observed sample. It is shown that the residual empirical process converges weakly to a Brownian bridge and the associated phi-divergence test has a chi-square limiting null distribution.

WEAK CONVERGENCE OF VARIOUS MODELS TO FRACTIONAL BROWNIAN MOTION

  • Kim, Joo-Mok
    • Korean Journal of Mathematics
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    • v.15 no.1
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    • pp.71-78
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    • 2007
  • We consider arrival process and ON/OFF source model which allows for long packet trains and long inter-train distances. We prove the weak convergence of theses processes to Fractional Brownian motion. Finally, we figure out the coefficients of $B_H(t)$ and time $t$ when ON/OFF periods have the Pareto distribution.

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Limiting Processes of Stopping Time in Estimating a Population Size

  • Choi, Ki-Heon
    • Journal of the Korean Data and Information Science Society
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    • v.11 no.2
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    • pp.327-334
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    • 2000
  • Suppose that there is a population of hidden objects of which the total number N is unknown. From such data, we derive some properties of the limiting processes of stopping time in estimating a population size.

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Option Pricing with Bounded Expected Loss under Variance-Gamma Processes

  • Song, Seong-Joo;Song, Jong-Woo
    • Communications for Statistical Applications and Methods
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    • v.17 no.4
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    • pp.575-589
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    • 2010
  • Exponential L$\acute{e}$evy models have become popular in modeling price processes recently in mathematical finance. Although it is a relatively simple extension of the geometric Brownian motion, it makes the market incomplete so that the option price is not uniquely determined. As a trial to find an appropriate price for an option, we suppose a situation where a hedger wants to initially invest as little as possible, but wants to have the expected squared loss at the end not exceeding a certain constant. For this, we assume that the underlying price process follows a variance-gamma model and it converges to a geometric Brownian motion as its quadratic variation converges to a constant. In the limit, we use the mean-variance approach to find the asymptotic minimum investment with the expected squared loss bounded. Some numerical results are also provided.

Application of GTH-like algorithm to Markov modulated Brownian motion with jumps

  • Hong, Sung-Chul;Ahn, Soohan
    • Communications for Statistical Applications and Methods
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    • v.28 no.5
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    • pp.477-491
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    • 2021
  • The Markov modulated Brownian motion is a substantial generalization of the classical Brownian Motion. On the other hand, the Markovian arrival process (MAP) is a point process whose family is dense for any stochastic point process and is used to approximate complex stochastic counting processes. In this paper, we consider a superposition of the Markov modulated Brownian motion (MMBM) and the Markovian arrival process of jumps which are distributed as the bilateral ph-type distribution, the class of which is also dense in the space of distribution functions defined on the whole real line. In the model, we assume that the inter-arrival times of the MAP depend on the underlying Markov process of the MMBM. One of the subjects of this paper is introducing how to obtain the first passage probabilities of the superposed process using a stochastic doubling algorithm designed for getting the minimal solution of a nonsymmetric algebraic Riccatti equation. The other is to provide eigenvalue and eigenvector results on the superposed process to make it possible to apply the GTH-like algorithm, which improves the accuracy of the doubling algorithm.