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Real-world clinical problems are often characterized by multimodal data, usually associated with incomplete views and limited sample sizes in their cohorts, posing significant limitations for machine learning algorithms. In this work, we…

A novel model of intermittency is presented in which the dynamics of the rates of energy transfer between successive steps in the energy cascade is described by a hierarchy of stochastic differential equations. The probability distribution…

Fluid Dynamics · Physics 2010-10-27 Domingos S. P. Salazar , Giovani L. Vasconcelos

A backward stochastic differential equation (BSDE) is an SDE of the form $-dY_t = f(t,Y_t,Z_t)dt - Z_t^*dW_t;\ Y_T = \xi$. The subject of BSDEs has seen extensive attention since their introduction in the linear case by Bismut (1973) and in…

Probability · Mathematics 2023-12-13 Weiye Yang

We are interested in modelling Darwinian evolution, resulting from the interplay of phenotypic variation and natural selection through ecological interactions. Our models are rooted in the microscopic, stochastic description of a population…

Probability · Mathematics 2016-08-16 Nicolas Champagnat , Régis Ferrière , Sylvie Méléard

In this paper we deal with the utility maximization problem with a general utility function. We derive a new approach in which we reduce the utility maximization problem with general utility to the study of a fully-coupled Forward-Backward…

Probability · Mathematics 2011-10-13 Ulrich Horst , Ying Hu , Peter Imkeller , Anthony Réveillac , Jianing Zhang

In this work, we apply the Stochastic Grid Bundling Method (SGBM) to numerically solve backward stochastic differential equations (BSDEs). The SGBM algorithm is based on conditional expectations approximation by means of bundling of Monte…

Numerical Analysis · Mathematics 2019-08-26 Ki Wai Chau , Cornelis W. Oosterlee

We consider the problem of numerical approximation for forward-backward stochastic differential equations with drivers of quadratic growth (qgFBSDE). To illustrate the significance of qgFBSDE, we discuss a problem of cross hedging of an…

Computational Finance · Quantitative Finance 2010-04-14 Peter Imkeller , Gonçalo dos Reis , Jianing Zhang

Inference for functional linear models in the presence of heteroscedastic errors has received insufficient attention given its practical importance; in fact, even a central limit theorem has not been studied in this case. At issue,…

Statistics Theory · Mathematics 2024-05-27 Hyemin Yeon , Xiongtao Dai , Daniel John Nordman

The problem of robust utility maximization in an incomplete market with volatility uncertainty is considered, in the sense that the volatility of the market is only assumed to lie between two given bounds. The set of all possible models…

Probability · Mathematics 2015-04-07 Anis Matoussi , Dylan Possamaï , Chao Zhou

This paper deals with partially-observed optimal control problems for the state governed by stochastic differential equation with delay. We develop a stochastic maximum principle for this kind of optimal control problems using a variational…

Optimization and Control · Mathematics 2020-10-15 Shuaiqi Zhang , Xun Li , Jie Xiong

In this paper, we study optimal switching problems under ambiguity. To characterize the optimal switching under ambiguity in the finite horizon, we use multidimensional reflected backward stochastic differential equations (multidimensional…

Mathematical Finance · Quantitative Finance 2016-08-23 Yuki Shigeta

In this paper, we present own point of view how the unexpected fluctuations of the long-term real interest rate can be explained. We describe a macroeconomic environment by the modification of the fundamental macroeconomic equilibrium model…

General Finance · Quantitative Finance 2019-03-21 Barbora Volná

In this paper, we study the solvability of a class of multi-dimensional forward backward stochastic differential equations (FBSDEs) with oblique reflection and unbounded stopping time. Under some mild assumptions on the coefficients in such…

Probability · Mathematics 2012-07-03 Soufiane Aazizi , Imade Fakhouri

We present a minimal agent-based model of interacting agents characterized by their wealth to study taxation and inequality in a non-conservative economy. Wealth evolves through an extremal stochastic replacement process in which the…

Physics and Society · Physics 2026-05-05 Lautaro Giordano , Sebastian Gonçalves , José Roberto Iglesias , María Fabiana Laguna

Dynamical systems that are subject to continuous uncertain fluctuations can be modelled using Stochastic Differential Equations (SDEs). Controlling such system results in solving path constrained SDEs. Broadly, these problems fall under the…

Optimization and Control · Mathematics 2023-06-16 Sumit Suthar , Soumyendu Raha

We study partial information Nash equilibrium between a broker and an informed trader. In this setting, the informed trader, who possesses knowledge of a trading signal, trades multiple assets with the broker in a dealer market.…

Mathematical Finance · Quantitative Finance 2025-04-03 Xuchen Wu , Sebastian Jaimungal

In this paper, we consider the mixed optimal control of a linear stochastic system with a quadratic cost functional, with two controllers-one can choose only deterministic time functions, called the deterministic controller, while the other…

Optimization and Control · Mathematics 2017-08-23 Ying Hu , Shanjian Tang

This paper solves a consumption-investment choice problem with Epstein-Zin recursive utility under partial information--unobservable market price of risk. The main novelty is the introduction of a terminal liability constraint, a feature…

Optimization and Control · Mathematics 2025-12-04 Wilfried Kuissi-Kamdem

We study an optimal control problem on infinite time horizon with semimartingale strategies, random coefficients and regime switching. The value function and the optimal strategy can be characterized in terms of three systems of backward…

Optimization and Control · Mathematics 2026-02-27 Xinman Cheng , Guanxing Fu , Xiaonyu Xia

Stochastic differential equation mixed-effects models (SDEMEMs) are flexible hierarchical models that are able to account for random variability inherent in the underlying time-dynamics, as well as the variability between experimental units…

Computation · Statistics 2021-01-22 Samuel Wiqvist , Andrew Golightly , Ashleigh T. McLean , Umberto Picchini
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