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Related papers: Fitting Martingales To Given Marginals

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We review recent results on the metastable behavior of continuous-time Markov chains derived through the characterization of Markov chains as unique solutions of martingale problems.

Probability · Mathematics 2018-07-12 C. Landim

We study the convergence of random function iterations for finding an invariant measure of the corresponding Markov operator. We call the problem of finding such an invariant measure the stochastic fixed point problem. This generalizes…

Functional Analysis · Mathematics 2022-03-24 Neal Hermer , D. Russell Luke , Anja Sturm

We study the problem of bounding path-dependent expectations (within any finite time horizon $d$) over the class of discrete-time martingales whose marginal distributions lie within a prescribed tolerance of a given collection of benchmark…

Probability · Mathematics 2021-12-01 Zhengqing Zhou , Jose Blanchet , Peter W. Glynn

We show that any self-conformal measure $\mu$ on $\mathbb{R}$ is uniformly scaling and generates an ergodic fractal distribution. This generalizes existing results by removing the need for any separation condition. We also obtain…

Dynamical Systems · Mathematics 2023-08-23 Balázs Bárány , Antti Käenmäki , Aleksi Pyörälä , Meng Wu

We study branching Markov chains on a countable state space (space of types) $\mathscr{X}$, with the focus on the qualitative aspects of the limit behaviour of the evolving empirical population distributions. No conditions are imposed on…

Probability · Mathematics 2025-07-30 Vadim A. Kaimanovich , Wolfgang Woess

A classical result of Strassen asserts that given probabilities $\mu, \nu$ on the real line which are in convex order, there exists a \emph{martingale coupling} with these marginals, i.e.\ a random vector $(X_1,X_2)$ such that $X_1\sim \mu,…

Probability · Mathematics 2016-09-13 Mathias Beiglboeck , Nicolas Juillet

Given a matrix of distribution functions and a quasi-stochastic matrix, i.e. an irreducible nonnegative matrix with maximal eigenvalue one and associated unique positive left and right eigenvectors, the article studies the properties of an…

Probability · Mathematics 2015-08-28 Gerold Alsmeyer

We give a collection of explicit sufficient conditions for the true martingale property of a wide class of exponentials of semimartingales. We express the conditions in terms of semimartingale characteristics. This turns out to be very…

Mathematical Finance · Quantitative Finance 2016-08-12 David Criens , Kathrin Glau , Zorana Grbac

A set of matrices is said to have the finiteness property if the maximal rate of exponential growth of long products of matrices drawn from that set is realised by a periodic product. The extent to which the finiteness property is prevalent…

Rings and Algebras · Mathematics 2009-09-16 Ian D. Morris

The quantale of distance distributions is of fundamental importance for understanding probabilistic metric spaces as enriched categories. Motivated by the categorical interpretation of partial metric spaces, we are led to investigate the…

General Topology · Mathematics 2020-01-30 Jialiang He , Hongliang Lai , Lili Shen

Markov chain Monte Carlo (MCMC) methods asymptotically sample from complex probability distributions. The pseudo-marginal MCMC framework only requires an unbiased estimator of the unnormalized probability distribution function to construct…

Computation · Statistics 2016-05-25 Iain Murray , Matthew M. Graham

Continuous-time Markov chains describing interacting processes exhibit a state space that grows exponentially in the number of processes. This state-space explosion renders the computation or storage of the time-marginal distribution, which…

Numerical Analysis · Mathematics 2020-06-16 Peter Georg , Lars Grasedyck , Maren Klever , Rudolf Schill , Rainer Spang , Tilo Wettig

We consider optimal transportation of measures on metric and topological spaces in the case where the cost function and marginal distributions depend on a parameter with values in a metric space. The Hausdorff distance between the sets of…

Functional Analysis · Mathematics 2021-11-29 Vladimir Bogachev , Svetlana Popova

Computing the rate-distortion function for continuous sources is commonly regarded as a standard continuous optimization problem. When numerically addressing this problem, a typical approach involves discretizing the source space and…

Information Theory · Computer Science 2024-05-02 Lingyi Chen , Shitong Wu , Wenyi Zhang , Huihui Wu , Hao Wu

Stochastic optimization methods such as mirror descent have wide applications due to low computational cost. Those methods have been well studied under assumption of the independent and identical distribution, and usually achieve sublinear…

Machine Learning · Computer Science 2023-09-27 Yawei Zhao

Many results in stochastic analysis and mathematical finance involve local martingales. However, specific examples of strict local martingales are rare and analytically often rather unhandy. We study local martingales that follow a given…

Probability · Mathematics 2015-10-13 Martin Herdegen , Sebastian Herrmann

We investigate the efficiency of a marginal likelihood estimator where the product of the marginal posterior distributions is used as an importance-sampling function. The approach is generally applicable to multi-block parameter vector…

Computation · Statistics 2014-07-08 K. Perrakis , I. Ntzoufras , E. G. Tsionas

By investigating model-independent bounds for exotic options in financial mathematics, a martingale version of the Monge-Kantorovich mass transport problem was introduced in \cite{BeiglbockHenry…

Computational Finance · Quantitative Finance 2013-04-10 Pierre Henry-Labordere , Nizar Touzi

For local martingales with nonnegative jumps, we prove a sufficient criterion for the corresponding exponential martingale to be a true martingale. The criterion is in terms of exponential moments of a convex combination of the optional and…

Probability · Mathematics 2015-04-15 Alexander Sokol

In regression modelling approach, the main step is to fit the regression line as close as possible to the target variable. In this process most algorithms try to fit all of the data in a single line and hence fitting all parts of target…

Machine Learning · Statistics 2018-05-07 Kumarjit Pathak , Jitin Kapila , Aasheesh Barvey , Nikit Gawande
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