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We explore martingale and convex duality techniques to study optimal investment strategies that maximize expected risk-averse utility from consumption and terminal wealth. We consider a market model with jumps driven by (multivariate)…

Portfolio Management · Quantitative Finance 2015-09-22 Mauricio Junca , Rafael Serrano

In this paper, we consider the classical problem of utility maximization in a financial market allowing jumps. Assuming that the constraint set is a compact set, rather than a convex one, we use a dynamic method from which we derive a…

Probability · Mathematics 2008-12-10 Marie-Amelie Morlais

We study martingale inequalities from an analytic point of view and show that a general martingale inequality can be reduced to a pair of deterministic inequalities in a small number of variables. More precisely, the optimal bound in the…

Probability · Mathematics 2014-10-21 Mathias Beiglböck , Marcel Nutz

Optimal stopping is the problem of determining when to stop a stochastic system in order to maximize reward, which is of practical importance in domains such as finance, operations management and healthcare. Existing methods for…

Optimization and Control · Mathematics 2022-03-28 Xinyi Guan , Velibor V. Mišić

We study the most famous example of a large financial market: the Arbitrage Pricing Model, where investors can trade in a one-period setting with countably many assets admitting a factor structure. We consider the problem of maximising…

Portfolio Management · Quantitative Finance 2020-10-06 Laurence Carassus , Miklos Rasonyi

In this paper, we study a stochastic optimal control problem with stochastic volatility. We prove the sufficient and necessary maximum principle for the proposed problem. Then we apply the results to solve an investment, consumption and…

Portfolio Management · Quantitative Finance 2018-08-15 Rodwell Kufakunesu , Calisto Guambe

The present paper studies a kind of robust optimization problems with constraint. The problem is formulated through Backward Stochastic Differential Equations (BSDEs) with quadratic generators. A necessary condition is established for the…

Optimization and Control · Mathematics 2024-02-14 Peng Luo , Alexander Schied , Xiaole Xue

The main result of this paper is a probabilistic proof of the penalty method for approximating the price of an American put in the Black-Scholes market. The method gives a parametrized family of partial differential equations, and by…

Mathematical Finance · Quantitative Finance 2014-10-07 K. Gad , J. L. Pedersen

We address the Merton problem of maximizing the expected utility of terminal wealth using techniques from variational analysis. Under a general continuous semimartingale market model with stochastic parameters, we obtain a characterization…

Portfolio Management · Quantitative Finance 2020-03-20 Ali Al-Aradi , Sebastian Jaimungal

In this paper we make a survey on the so called randomization method, a recent methodology to study stochastic optimization problems. It allows to represent the value function of an optimal control problem by a suitable backward stochastic…

Optimization and Control · Mathematics 2025-06-12 Marco Fuhrman

In this article we consider a game theoretic approach to the Risk-Sensitive Benchmarked Asset Management problem (RSBAM) of Davis and Lleo \cite{DL}. In particular, we consider a stochastic differential game between two players, namely, the…

Optimization and Control · Mathematics 2015-03-09 Amogh Deshpande , Saul D. Jacka

We study the expected utility portfolio optimization problem in an incomplete financial market where the risky asset dynamics depend on stochastic factors and the portfolio allocation is constrained to lie within a given convex set. We…

Portfolio Management · Quantitative Finance 2023-03-20 Marcos Escobar-Anel , Michel Kschonnek , Rudi Zagst

In this paper the utility optimization problem for a general insurance model is studied. The reserve process of the insurance company is described by a stochastic differential equation driven by a Brownian motion and a Poisson random…

Probability · Mathematics 2009-09-01 Yuping Liu , Jin Ma

We consider the problem of utility maximization with exponential preferences in a market where the traded stock/risky asset price is modelled as a L\'evy-driven pure jump process (i.e. the driving L\'evy process has no Brownian component).…

Probability · Mathematics 2016-02-02 Carla Mereu , Robert Stelzer

We study the portfolio problem of maximizing the outperformance probability over a random benchmark through dynamic trading with a fixed initial capital. Under a general incomplete market framework, this stochastic control problem can be…

Portfolio Management · Quantitative Finance 2015-03-19 Tim Leung , Qingshuo Song , Jie Yang

We study a generic principal-agent problem in continuous time on a finite time horizon. We introduce a framework in which the agent is allowed to employ measure-valued controls and characterise the continuation utility as a solution to a…

Probability · Mathematics 2025-12-01 Daniel Kršek , Dylan Possamaï

We study non-linear Backward Stochastic Differential Equations (BSDEs) driven by a Brownian motion and p default martingales. The driver of the BSDE with multiple default jumps can take a generalized form involving an optional finite…

Mathematical Finance · Quantitative Finance 2026-01-06 Miryana Grigorova , James Wheeldon

In this paper, we extend the optimal securitisation model of Pag\`es [50] and Possama\"i and Pag\`es [51] between an investor and a bank to a setting allowing both moral hazard and adverse selection. Following the recent approach to these…

Economics · Quantitative Finance 2019-01-17 Nicolás Hernández Santibáñez , Dylan Possamaï , Chao Zhou

We present a new approach for studying the problem of optimal hedging of a European option in a finite and complete discrete-time market model. We consider partial hedging strategies that maximize the success probability or minimize the…

Pricing of Securities · Quantitative Finance 2009-10-28 Peter G. Lindberg

Most methods for decision-theoretic online learning are based on the Hedge algorithm, which takes a parameter called the learning rate. In most previous analyses the learning rate was carefully tuned to obtain optimal worst-case…

Machine Learning · Statistics 2015-03-04 Tim van Erven , Peter Grünwald , Wouter M. Koolen , Steven de Rooij
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