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Recently, \cite{BeJu16, BeNuTo16} established that optimizers to the martingale optimal transport problem (MOT) are concentrated on $c$-monotone sets. In this article we characterize monotonicity preserving transformations revealing certain…

Probability · Mathematics 2017-07-27 Martin Huesmann , Florian Stebegg

In this paper, we study the $m$-states optimal switching problem in finite horizon, when the switching cost functions are arbitrary and can be positive or negative. This has an economic incentive in terms of central evaluation in cases…

Optimization and Control · Mathematics 2016-05-06 Brahim El Asri , Imade Fakhouri

We consider the problem of robustly maximizing the growth rate of investor wealth in the presence of model uncertainty. Possible models are all those under which the assets' region $E$ and instantaneous covariation $c$ are known, and where…

Portfolio Management · Quantitative Finance 2018-01-22 Constantinos Kardaras , Scott Robertson

This paper shows the usefulness of the Perov contraction theorem, which is a generalization of the classical Banach contraction theorem, for solving Markov dynamic programming problems. When the reward function is unbounded, combining an…

Optimization and Control · Mathematics 2024-05-06 Alexis Akira Toda

The aim of this article is to show that the Monge-Kantorovich problem is the limit of a sequence of entropy minimization problems when a fluctuation parameter tends down to zero. We prove the convergence of the entropic values to the…

Optimization and Control · Mathematics 2013-08-02 Christian Léonard

We derive closed-form solutions to the optimal stopping problems related to the pricing of perpetual American standard and lookback put and call options in the extensions of the Black-Merton-Scholes model with progressively enlarged…

Mathematical Finance · Quantitative Finance 2025-07-08 Pavel V. Gapeev , Libo Li

For a strictly stationary sequence of $\mathbb{R}_{+}^{d}$--valued random vectors we derive functional convergence of partial maxima stochastic processes under joint regular variation and weak dependence conditions. The limit process is an…

Probability · Mathematics 2016-07-14 Danijel Krizmanić

Motivated by practical applications, recent works have considered maximization of sums of a submodular function $g$ and a linear function $\ell$. Almost all such works, to date, studied only the special case of this problem in which $g$ is…

Data Structures and Algorithms · Computer Science 2022-04-08 Kobi Bodek , Moran Feldman

We develop an explicit non-randomized solution to the Skorokhod embedding problem in an abstract setup of signed functionals of Markovian excursions. Our setting allows to solve the Skorokhod embedding problem, in particular, for diffusions…

Probability · Mathematics 2007-05-23 Jan Obloj

We show an intimate connection between solutions of the Skorokhod Embedding Problem which are given as the first hitting time of a barrier and the concept of shadows in martingale optimal transport. More precisely, we show that a solution…

Probability · Mathematics 2021-03-08 Martin Brückerhoff , Martin Huesmann

The well known maximum-entropy principle due to Jaynes, which states that given mean parameters, the maximum entropy distribution matching them is in an exponential family, has been very popular in machine learning due to its "Occam's…

Machine Learning · Computer Science 2016-07-13 Yuanzhi Li , Andrej Risteski

Consider the discounted optimal stopping problem for a real valued Markov process with only positive jumps. We provide a theorem to verify that the optimal stopping region has the form {x >= x^*} for some critical threshold x^*, and a…

Probability · Mathematics 2024-11-14 Fabian Crocce , Ernesto Mordecki

In Bayesian inference, the maximum a posteriori (MAP) problem combines the most probable explanation (MPE) and marginalization (MAR) problems. The counterpart in propositional logic is the exist-random stochastic satisfiability (ER-SSAT)…

Logic in Computer Science · Computer Science 2022-05-23 Vu H. N. Phan , Moshe Y. Vardi

We present a simple combinatorial $\frac{1 -e^{-2}}{2}$-approximation algorithm for maximizing a monotone submodular function subject to a knapsack and a matroid constraint. This classic problem is known to be hard to approximate within…

Data Structures and Algorithms · Computer Science 2018-01-16 Kanthi K. Sarpatwar , Baruch Schieber , Hadas Shachnai

In this paper, we study stochastic submodular maximization problems with general matroid constraints, that naturally arise in online learning, team formation, facility location, influence maximization, active learning and sensing objective…

Machine Learning · Computer Science 2023-03-20 Gözde Özcan , Stratis Ioannidis

In this paper we introduce a completely continuous and time-variate model of the evolution of market limit orders based on the existence, uniqueness, and regularity of the solutions to a type of stochastic partial differential equations…

Trading and Market Microstructure · Quantitative Finance 2012-10-29 Zhi Zheng , Richard B. Sowers

The analysis of structure-preserving numerical methods for the Poisson--Nernst--Planck (PNP) system has attracted growing interests in recent years. In this work, we provide an optimal rate convergence analysis and error estimate for finite…

Numerical Analysis · Mathematics 2022-02-23 Jie Ding , Cheng Wang , Shenggao Zhou

In this paper we develop necessary conditions for optimality, in the form of the Pontryagin maximum principle, for the optimal control problem of a class of infinite dimensional evolution equations with delay in the state. In the cost…

Probability · Mathematics 2017-06-12 Giuseppina Guatteri , Federica Masiero , Carlo Orrieri

We analyze the performance of the greedy algorithm, and also a discrete semi-gradient based algorithm, for maximizing the sum of a suBmodular and suPermodular (BP) function (both of which are non-negative monotone non-decreasing) under two…

Discrete Mathematics · Computer Science 2018-01-24 Wenruo Bai , Jeffrey A. Bilmes

We study perpetual American option pricing problems in an extension of the Black-Merton-Scholes model in which the dividend and volatility rates of the underlying risky asset depend on the running values of its maximum and maximum drawdown.…

Probability · Mathematics 2016-04-12 Pavel V. Gapeev , Neofytos Rodosthenous
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