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This paper is concerned with an optimal reinsurance and investment problem for an insurance firm under the criterion of mean-variance. The driving Brownian motion and the rate in return of the risky asset price dynamic equation cannot be…

Optimization and Control · Mathematics 2020-06-04 Shihao Zhu , Jingtao Shi

We study the ergodic control problem for a class of controlled jump diffusions driven by a compound Poisson process. This extends the results of [SIAM J. Control Optim. 57 (2019), no. 2, 1516-1540] to running costs that are not…

Optimization and Control · Mathematics 2021-01-01 Ari Arapostathis , Guodong Pang , Yi Zheng

In this paper we propose and analyze a method based on the Riccati transformation for solving the evolutionary Hamilton-Jacobi-Bellman equation arising from the stochastic dynamic optimal allocation problem. We show how the fully nonlinear…

Portfolio Management · Quantitative Finance 2013-07-25 Sona Kilianova , Daniel Sevcovic

In this paper, we study the following nonlinear backward stochastic integral partial differential equation with jumps \begin{equation*} \left\{ \begin{split} -d V(t,x) =&\displaystyle\inf_{u\in U}\bigg\{H(t,x,u, DV(t,x),D \Phi(t,x), D^2…

Optimization and Control · Mathematics 2020-11-10 Qingxin Meng , Yuchao Dong , Yang Shen , Shanjian Tang

We consider a mean-variance portfolio selection problem in a financial market with contagion risk. The risky assets follow a jump-diffusion model, in which jumps are driven by a multivariate Hawkes process with mutual-excitation effect. The…

Mathematical Finance · Quantitative Finance 2021-10-19 Yang Shen , Bin Zou

We study an optimal control problem on infinite horizon for a controlled stochastic differential equation driven by Brownian motion, with a discounted reward functional. The equation may have memory or delay effects in the coefficients,…

Optimization and Control · Mathematics 2017-10-19 F. Confortola , A. Cosso , M. Fuhrman

This paper is concerned with a long standing optimal dividend payout problem subject to the so-called ratcheting constraint, that is, the dividend payout rate shall be non-decreasing over time and is thus self-path-dependent. The surplus…

Mathematical Finance · Quantitative Finance 2024-07-08 Chonghu Guan , Zuo Quan Xu

We consider a stochastic volatility model with jumps where the underlying asset price is driven by the process sum of a 2-dimensional Brownian motion and a 2-dimensional compensated Poisson process. The market is incomplete, resulting in…

Probability · Mathematics 2011-10-31 Youssef El-Khatib

The purpose of this paper is to study optimal control of conditional McKean-Vlasov (mean-field) stochastic differential equations with jumps (conditional McKean-Vlasov jump diffusions, for short). To this end, we first prove a stochastic…

Probability · Mathematics 2023-01-10 Nacira Agram , Bernt Oksendal

We investigate the optimal strategy over a finite time horizon for a portfolio of stock and bond and a derivative in an multiplicative Markovian market model with transaction costs (friction). The optimization problem is solved by a…

Physics and Society · Physics 2011-06-24 Erik Aurell , Paolo Muratore-Ginanneschi

This paper is concerned with the maximum principle and dynamic programming principle for mean-variance portfolio selection of jump diffusions and their relationship. First, the optimal portfolio and efficient frontier of the problem are…

Portfolio Management · Quantitative Finance 2025-08-05 Qiyue Zhang , Jingtao Shi

We consider a dynamic portfolio optimization problem that incorporates predictable returns, instantaneous transaction costs, price impact, and stochastic volatility, extending the classical results of Garleanu and Pedersen (2013), which…

Computational Finance · Quantitative Finance 2025-07-24 Patrick Chan , Ronnie Sircar , Iosif Zimbidis

In this paper, we consider the portfolio optimization problem in a financial market under a general utility function. Empirical results suggest that if a significant market fluctuation occurs, invested wealth tends to have a notable change…

Portfolio Management · Quantitative Finance 2022-01-26 Minglian Lin , Indranil SenGupta

In this paper we study mean-field type control problems with risk-sensitive performance functionals. We establish a stochastic maximum principle (SMP) for optimal control of stochastic differential equations (SDEs) of mean-field type, in…

Optimization and Control · Mathematics 2014-04-08 Boualem Djehiche , Hamidou Tembine , Raul Tempone

In this paper, we consider the problem of optimal investment by an insurer. The insurer invests in a market consisting of a bank account and $m$ risky assets. The mean returns and volatilities of the risky assets depend nonlinearly on…

Portfolio Management · Quantitative Finance 2019-03-22 Hiroaki Hata , Shuenn-Jyi Sheu , Li-Hsien Sun

In this paper, we consider the stochastic optimal control problem for jump diffusion systems with state constraints. In general, the value function of such problems is a discontinuous viscosity solution of the Hamilton-Jacobi-Bellman (HJB)…

Optimization and Control · Mathematics 2020-06-11 Jun Moon

IIn this paper, we study a partially observed progressive optimal control problem of forward-backward stochastic differential equations with random jumps, where the control domain is not necessarily convex, and the control variable enter…

Optimization and Control · Mathematics 2022-06-27 Yueyang Zheng , Jingtao Shi

In this paper we study jump-diffusion stochastic differential equations (SDEs) with a discontinuous drift coefficient and a possibly degenerate diffusion coefficient. Such SDEs appear in applications such as optimal control problems in…

Numerical Analysis · Mathematics 2021-01-15 Paweł Przybyłowicz , Michaela Szölgyenyi

The solution to a stochastic optimal control problem can be determined by computing the value function from a discretization of the associated Hamilton-Jacobi-Bellman equation. Alternatively, the problem can be reformulated in terms of a…

Optimization and Control · Mathematics 2024-02-29 Sebastian Reich

We study continuous-time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump-diffusion processes. We formulate an entropy-regularized exploratory control problem with stochastic policies to…

Machine Learning · Computer Science 2025-08-26 Xuefeng Gao , Lingfei Li , Xun Yu Zhou