M
Mikhail Zhitlukhin
Researcher at Russian Academy of Sciences
Publications - 57
Citations - 302
Mikhail Zhitlukhin is an academic researcher from Russian Academy of Sciences. The author has contributed to research in topics: Optimal stopping & Fractional Brownian motion. The author has an hindex of 8, co-authored 55 publications receiving 222 citations. Previous affiliations of Mikhail Zhitlukhin include National Research University – Higher School of Economics & Steklov Mathematical Institute.
Papers
More filters
Journal ArticleDOI
Bounds for expected maxima of Gaussian processes and their discrete approximations
TL;DR: In this article, the expected maxima of continuous Gaussian processes that are continuous in -norm and/or satisfy the opposite inequality for the -norms of their increments are investigated. And the convergence rate of these two maxima is investigated in the special case of the fractional Brownian motion.
Book
Asymptotic Analysis of Random Walks: Light-Tailed Distributions
TL;DR: The large deviation principle for random walks was first established by the author in 1967, under the restrictive condition that the distribution tails decay faster than exponentially as mentioned in this paper, but only in a rather special case, since then, the principle has always been treated in the literature only under this condition.
Journal ArticleDOI
Bayesian Disorder Problems on Filtered Probability Spaces
TL;DR: In this article, a general Bayesian disorder detection problem for Brownian motion on a finite time segment is formulated, and properties of basic statistics are studied to reduce problems of quickest detection of disorder moments to optimal stopping problems.
Journal ArticleDOI
A Bayesian sequential testing problem of three hypotheses for Brownian motion
TL;DR: In this paper, a sequential testing problem of three hypotheses that the unknown drift of a Brownian motion takes one of three values is considered, and a reduction to an optimal stopping problem for local times of the observable process is shown.
Journal ArticleDOI
When to Sell Apple and the Nasdaq? Trading Bubbles with a Stochastic Disorder Model
TL;DR: In this paper, the authors apply a continuous-time stochastic process model developed by Shiryaev and Zhutlukhin for optimally stopping random price processes that appear to be bubbles, defined as price increases that are largely based on the expectation of higher and higher future prices.