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We present a framework for fine-tuning flow-matching generative models to enforce physical constraints and solve inverse problems in scientific systems. Starting from a model trained on low-fidelity or observational data, we apply a…

Machine Learning · Computer Science 2026-01-28 Jan Tauberschmidt , Sophie Fellenz , Sebastian J. Vollmer , Andrew B. Duncan

In an incomplete continuous-time securities market with uncertainty generated by Brownian motions, we derive closed-form solutions for the equilibrium interest rate and market price of risk processes. The economy has a finite number of…

General Finance · Quantitative Finance 2012-01-06 Peter Ove Christensen , Kasper Larsen

This paper addresses the portfolio selection problem for nonlinear law-dependent preferences in continuous time, which inherently exhibit time inconsistency. Employing the method of stochastic maximum principle, we establish verification…

Mathematical Finance · Quantitative Finance 2023-11-15 Zongxia Liang , Jianming Xia , Fengyi Yuan

In this paper, we study the well-posedness of the Forward-Backward Stochastic Differential Equations (FBSDE) in a general non-Markovian framework. The main purpose is to find a unified scheme which combines all existing methodology in the…

Probability · Mathematics 2015-06-30 Jin Ma , Zhen Wu , Detao Zhang , Jianfeng Zhang

We develop a stochastic equilibrium model for an electricity market with asymmetric renewable energy forecasts. In our setting, market participants optimize their profits using public information about a conditional expectation of energy…

Optimization and Control · Mathematics 2020-05-26 Vladimir Dvorkin , Jalal Kazempour , Pierre Pinson

Many imaging techniques for biological systems -- like fixation of cells coupled with fluorescence microscopy -- provide sharp spatial resolution in reporting locations of individuals at a single moment in time but also destroy the dynamics…

Subcellular Processes · Quantitative Biology 2024-05-15 Christopher E. Miles , Scott A. McKinley , Fangyuan Ding , Richard B. Lehoucq

This paper develops a new model of business cycles. The model is economical in that it is solved with an aggregate demand-aggregate supply diagram, and the effects of shocks and policies are obtained by comparative statics. The model builds…

Theoretical Economics · Economics 2022-03-22 Pascal Michaillat , Emmanuel Saez

This paper presents a novel and direct approach to price boundary and final-value problems, corresponding to barrier options, using forward deep learning to solve forward-backward stochastic differential equations (FBSDEs). Barrier…

Computational Finance · Quantitative Finance 2024-09-13 Narayan Ganesan , Yajie Yu , Bernhard Hientzsch

This paper provides a detailed analysis of the local determinacy of monetary and non-monetary steady states in Tirole (1985)'s classical two-period overlapping generations model with capital and production. We show that the sufficient…

Theoretical Economics · Economics 2024-05-14 Tomohiro Hirano , Alexis Akira Toda

A widely-used model for determining the long-term health impacts of public health interventions, often called a "multistate lifetable", requires estimates of incidence, case fatality, and sometimes also remission rates, for multiple…

Applications · Statistics 2023-03-23 Christopher Jackson , Belen Zapata-Diomedi , James Woodcock

We propose and study a scheme combining the finite element method and machine learning techniques for the numerical approximations of coupled nonlinear forward-backward stochastic partial differential equations (FBSPDEs) with homogeneous…

Numerical Analysis · Mathematics 2020-12-16 Hasib Uddin Molla , Jinniao Qiu

This paper is concerned with an optimal control problem for a forward-backward stochastic differential equation (FBSDE, for short) with a recursive cost functional determined by a backward stochastic Volterra integral equation (BSVIE, for…

Optimization and Control · Mathematics 2022-09-20 Hanxiao Wang , Jiongmin Yong , Chao Zhou

In this paper,we mainly focus on the numerical solution of high-dimensional stochastic optimal control problem driven by fully-coupled forward-backward stochastic differential equations (FBSDEs in short) through deep learning. We first…

Optimization and Control · Mathematics 2024-08-21 Shaolin Ji , Shige Peng , Ying Peng , Xichuan Zhang

Survey data are widely used to study how income inequality, poverty, and welfare evolve over time. A common practice is to estimate the income distribution separately for each year, treating annual observations as independent…

Econometrics · Economics 2026-04-24 David Gunawan

This article introduces a framework for measuring the uncertain behaviour of a changing system in terms of the solution of a class of fractional stochastic differential equations (fsDEs). This is accomplished via operational matrices based…

General Mathematics · Mathematics 2025-06-03 O. T. Birgani , J. F. Peters , S. Kouhkani

We propose a statistical-stochastic surrogate modeling approach to predict the response of the mean and variance statistics under various initial conditions and external forcing perturbations. The proposed modeling framework extends the…

Data Analysis, Statistics and Probability · Physics 2023-04-07 Di Qi , John Harlim

Stochastic multiplicative dynamics characterize many complex natural phenomena such as selection and mutation in evolving populations, and the generation and distribution of wealth within social systems. Population heterogeneity in…

Physics and Society · Physics 2022-09-21 Jordan T. Kemp , Luís M. A. Bettencourt

The optimal (`equilibrium') macroscopic properties of an economy with $N$ industries endowed with different technologies, $P$ commodities and one consumer are derived in the limit $N\to\infty$ with $n=N/P$ fixed using the replica method.…

Disordered Systems and Neural Networks · Physics 2008-12-02 A. De Martino , M. Marsili , I. Perez Castillo

We investigate the optimal reinsurance problem under the criterion of maximizing the expected utility of terminal wealth when the insurance company has restricted information on the loss process. We propose a risk model with claim arrival…

Mathematical Finance · Quantitative Finance 2020-05-15 Matteo Brachetta , Claudia Ceci

Financial studies require volatility based models which provides useful insights on risks related to investments. Stochastic volatility models are one of the most popular approaches to model volatility in such studies. The asset returns…

Methodology · Statistics 2021-10-26 Soham Mukherjee
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