The real-time detection of changes in a noisily observed signal is an important problem in applied science and engineering. The study of parametric optimal detection theory began in …
S Campbell, Y Zhang - arXiv preprint arXiv:2403.18297, 2024 - arxiv.org
We introduce a mean field game for a family of filtering problems related to the classic sequential testing of the drift of a Brownian motion. To the best of our knowledge this work …
H Dyrssen, E Ekström - Sequential Analysis, 2018 - Taylor & Francis
We consider the sequential testing of two simple hypotheses for the drift of a Brownian motion when each observation of the underlying process is associated with a positive cost …
PV Gapeev, AN Shiryaev - Stochastics An International Journal of …, 2011 - Taylor & Francis
We study the Bayesian problem of sequential testing of two simple hypotheses about the drift rate of an observable diffusion process. The optimal stopping time is found as the first …
S Qiu - Applied Mathematical Finance, 2020 - Taylor & Francis
In this paper, we show that the double optimal stopping boundaries for American strangle options with finite horizon can be characterized as the unique pair of solution to a system of …
PA Ernst, G Peskir, Q Zhou - The Annals of Applied Probability, 2020 - JSTOR
Consider the motion of a Brownian particle in three dimensions, whose two spatial coordinates are standard Brownian motions with zero drift, and the remaining (unknown) …
P Johnson, G Peskir - Transactions of the American Mathematical Society, 2018 - ams.org
Consider the motion of a Brownian particle that takes place either in a two-dimensional plane or in three-dimensional space. Given that only the distance of the particle to the origin …
We study a two-dimensional discounted optimal stopping problem related to the pricing of perpetual commodity equities in a model of financial markets in which the behaviour of the …
We study a classical Bayesian statistics problem of sequentially testing the sign of the drift of an arithmetic Brownian motion with the 0-1 loss function and a constant cost of observation …