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The question addressed in this paper is the performance of the optimal strategy, and the impact of partial information. The setting we consider is that of a stochastic asset price model where the trend follows an unobservable…

Portfolio Management · Quantitative Finance 2015-10-14 Ahmed Bel Hadj Ayed , Grégoire Loeper , Sofiene El Aoud , Frédéric Abergel

We consider a piecewise deterministic Markov decision process, where the expected exponential utility of total (nonnegative) cost is to be minimized. The cost rate, transition rate and post-jump distributions are under control. The state…

Optimization and Control · Mathematics 2017-11-22 Xin Guo , Yi Zhang

In this paper, we introduce and develop the theory of semimartingale optimal transport in a path dependent setting. Instead of the classical constraints on marginal distributions, we consider a general framework of path dependent…

Probability · Mathematics 2020-09-15 Ivan Guo , Gregoire Loeper

We consider robust pricing and hedging for options written on multiple assets given market option prices for the individual assets. The resulting problem is called the multi-marginal martingale optimal transport problem. We propose two…

Probability · Mathematics 2020-10-08 Stephan Eckstein , Gaoyue Guo , Tongseok Lim , Jan Obloj

In this paper we study the pricing and hedging of nonreplicable contingent claims, such as long-term insurance contracts like variable annuities. Our approach is based on the benchmark-neutral pricing framework of Platen (2024), which…

Mathematical Finance · Quantitative Finance 2025-06-25 Michael Schmutz , Eckhard Platen , Thorsten Schmidt

We consider the problem of finding consistent upper price bounds and super replication strategies for exotic options, given the observation of call prices in the market. This field of research is called model-independent finance and has…

Optimization and Control · Mathematics 2020-01-31 Nicole Bäuerle , Daniel Schmithals

In this paper, we examine the use of self-stabilizing algorithms, operating in a hierarchical manner, to determine intellectual property risks at a macro level. We are both interested in finding a solution that will support all defined…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-22 Ken Kennedy , Iman Evazzade

Working under a model of privacy in which data remains private even from the statistician, we study the tradeoff between privacy guarantees and the risk of the resulting statistical estimators. We develop private versions of classical…

Statistics Theory · Mathematics 2017-11-16 John Duchi , Martin Wainwright , Michael Jordan

This paper studies a portfolio optimization problem in a discrete-time Markovian model of a financial market, in which asset price dynamics depend on an external process of economic factors. There are transaction costs with a structure that…

Portfolio Management · Quantitative Finance 2008-12-02 Jan Palczewski , Lukasz Stettner

We study conditional risk minimization (CRM), i.e. the problem of learning a hypothesis of minimal risk for prediction at the next step of sequentially arriving dependent data. Despite it being a fundamental problem, successful learning in…

Machine Learning · Statistics 2018-11-06 Alexander Zimin , Christoph Lampert

A drawdown constraint forces the current wealth to remain above a given function of its maximum to date. We consider the portfolio optimisation problem of maximising the long-term growth rate of the expected utility of wealth subject to a…

Portfolio Management · Quantitative Finance 2013-04-23 Vladimir Cherny , Jan Obloj

We solve the problem of pricing and optimal exercise of American call-type options in markets which do not necessarily admit an equivalent local martingale measure. This resolves an open question proposed by Fernholz and Karatzas…

Pricing of Securities · Quantitative Finance 2009-12-21 Erhan Bayraktar , Constantinos Kardaras , Hao Xing

We study the minimization of a spectral risk measure of the total discounted cost generated by a Markov Decision Process (MDP) over a finite or infinite planning horizon. The MDP is assumed to have Borel state and action spaces and the cost…

Optimization and Control · Mathematics 2025-10-16 Nicole Bäuerle , Alexander Glauner

Rough stochastic volatility models have attracted a lot of attentions recently, in particular for the linear option pricing problem. In this paper, starting with power utilities, we propose to use a martingale distortion representation of…

Mathematical Finance · Quantitative Finance 2017-12-12 Jean-Pierre Fouque , Ruimeng Hu

With model uncertainty characterized by a convex, possibly non-dominated set of probability measures, the agent minimizes the cost of hedging a path dependent contingent claim with given expected success ratio, in a discrete-time,…

Mathematical Finance · Quantitative Finance 2017-09-29 Erhan Bayraktar , Gu Wang

In this research, we present an analysis of the optimal investment, consumption, and life insurance acquisition problem for a wage earner with partial information. Our study considers the non-linear filter case where risky asset prices are…

Optimization and Control · Mathematics 2023-04-25 Woundjiagué Apollinaire , Rodwell Kufakunesu , Julius Esunge

We use the martingale method to discuss the relationship between mean-variance (MV) and monotone mean-variance (MMV) portfolio selections. We propose a unified framework to discuss the relationship in general financial markets without any…

Optimization and Control · Mathematics 2024-03-12 Yuchen Li , Zongxia Liang , Shunzhi Pang

We consider the problem of maximising expected utility from terminal wealth in a semimartingale setting, where the semimartingale is written as a sum of a time-changed Brownian motion and a finite variation process. To solve this problem,…

Probability · Mathematics 2024-07-04 Giulia Di Nunno , Hannes Haferkorn , Asma Khedher , Michèle Vanmaele

Conditional risk minimization arises in high-stakes decisions where risk must be assessed in light of side information, such as stressed economic conditions, specific customer profiles, or other contextual covariates. Constructing reliable…

Machine Learning · Statistics 2025-09-30 Xinqiao Xie , Jonathan Yu-Meng Li

Many scenarios where agents with restrictions compete for resources can be cast as maximum matching problems on bipartite graphs. Our focus is on resource allocation problems where agents may have restrictions that make them incompatible…

Artificial Intelligence · Computer Science 2022-09-13 Yohai Trabelsi , Abhijin Adiga , Sarit Kraus , S. S. Ravi
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