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Related papers: Risk-minimization and hedging claims on a jump-dif…

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Estimating the likelihood, timing, and nature of events is a major goal of modeling stochastic dynamical systems. When the event is rare in comparison with the timescales of simulation and/or measurement needed to resolve the elemental…

Computational Physics · Physics 2023-06-14 John Strahan , Justin Finkel , Aaron R. Dinner , Jonathan Weare

We consider an optimal control problem for piecewise deterministic Markov processes (PDMPs) on a bounded state space. The control problem under study is very general: a pair of controls acts continuously on the deterministic flow and on the…

Optimization and Control · Mathematics 2018-02-14 Elena Bandini

We introduce a mean-reverting SDE whose solution is naturally defined on the space of correlation matrices. This SDE can be seen as an extension of the well-known Wright-Fisher diffusion. We provide conditions that ensure weak and strong…

Probability · Mathematics 2012-02-14 Abdelkoddousse Ahdida , Aurélien Alfonsi

In this paper, we study an optimal mean-variance investment-reinsurance problem for an insurer (she) under a Cram\'er-Lundberg model with random coefficients. At any time, the insurer can purchase reinsurance or acquire new business and…

Portfolio Management · Quantitative Finance 2024-06-18 Xiaomin Shi , Zuo Quan Xu

In a Markovian framework, we consider the problem of finding the minimal initial value of a controlled process allowing to reach a stochastic target with a given level of expected loss. This question arises typically in approximate hedging…

Optimization and Control · Mathematics 2017-04-06 Géraldine Bouveret , Jean-François Chassagneux

The challenge to fruitfully merge state-of-the-art techniques from mathematical finance and numerical analysis has inspired researchers to develop fast deterministic option pricing methods. As a result, highly efficient algorithms to…

Computational Finance · Quantitative Finance 2015-11-06 Kathrin Glau

We model a nonlinear price curve quoted in a market as the utility indifference curve of a representative liquidity supplier. As the utility function we adopt a g-expectation. In contrast to the standard framework of financial engineering,…

Mathematical Finance · Quantitative Finance 2017-02-07 Masaaki Fukasawa , Mitja Stadje

This thesis develops equilibrium asset pricing models in incomplete markets with a large number of heterogeneous agents using mean field game theory. The market equilibrium is characterized by a novel form of mean field backward stochastic…

Mathematical Finance · Quantitative Finance 2026-03-24 Masashi Sekine

The classical Feynman-Kac formula states the connection between linear parabolic partial differential equations (PDEs), like the heat equation, and expectation of stochastic processes driven by Brownian motion. It gives then a method for…

Probability · Mathematics 2014-09-03 Huyen Pham

In this article, a compact finite difference method is proposed for pricing European and American options under jump-diffusion models. Partial integro-differential equation and linear complementary problem governing European and American…

Computational Finance · Quantitative Finance 2018-04-25 Kuldip Singh Patel , Mani Mehra

This paper studies an asset pricing model in a partially observable market with a large number of heterogeneous agents using the mean field game theory. In this model, we assume that investors can only observe stock prices and must infer…

Pricing of Securities · Quantitative Finance 2025-04-02 Masashi Sekine

This article investigates a regime-switching investment strategy aimed at mitigating downside risk by reducing market exposure during anticipated unfavorable market regimes. We highlight the statistical jump model (JM) for market regime…

Portfolio Management · Quantitative Finance 2024-09-18 Yizhan Shu , Chenyu Yu , John M. Mulvey

In this paper, we study the pricing of contingent claims under G-expectation. In order to accomodate volatility uncertainty, the price of the risky security is supposed to governed by a general linear stochastic differential equation (SDE)…

Probability · Mathematics 2013-03-19 Mingshang Hu , Shaolin Ji

This paper presents a novel approach to numerically solve stochastic differential games for nonlinear systems. The proposed approach relies on the nonlinear Feynman-Kac theorem that establishes a connection between parabolic deterministic…

Optimization and Control · Mathematics 2019-06-13 Ziyi Wang , Keuntaek Lee , Marcus A. Pereira , Ioannis Exarchos , Evangelos A. Theodorou

Measuring model risk is required by regulators on financial and insurance markets. We separate model risk into parameter estimation risk and model specification risk, and we propose expected shortfall type model risk measures applied to…

Econometrics · Economics 2020-10-29 Emese Lazar , Shuyuan Qi , Radu Tunaru

In this paper, we consider a risk-based optimal investment problem of an insurer in a regime-switching jump diffusion model with noisy memory. Using the model uncertainty modeling, we formulate the investment problem as a zero-sum,…

Portfolio Management · Quantitative Finance 2019-03-25 Rodwell Kufakunesu , Calisto Guambe , Lesedi Mabitsela

We consider a time-consistent mean-variance portfolio selection problem of an insurer and allow for the incorporation of basis (mortality) risk. The optimal solution is identified with a Nash subgame perfect equilibrium. We characterize an…

Portfolio Management · Quantitative Finance 2019-08-16 Frank Bosserhoff , Mitja Stadje

We model the stock price dynamics through a semi-Markov process obtained using a Poisson random measure. We establish the existence and uniqueness of the classical solution of a non-homogeneous terminal value problem and we show that the…

Mathematical Finance · Quantitative Finance 2022-09-13 Garima Agrawal , Anindya Goswami

This study contributes to understanding Valuation Adjustments (xVA) by focussing on the dynamic hedging of Credit Valuation Adjustment (CVA), corresponding Profit & Loss (P&L) and the P&L explain. This is done in a Monte Carlo simulation…

Computational Finance · Quantitative Finance 2022-04-07 T. van der Zwaard , L. A. Grzelak , C. W. Oosterlee

The cryptocurrency market is volatile, non-stationary and non-continuous. Together with liquid derivatives markets, this poses a unique opportunity to study risk management, especially the hedging of options, in a turbulent market. We study…

Pricing of Securities · Quantitative Finance 2022-12-05 Jovanka Lili Matic , Natalie Packham , Wolfgang Karl Härdle