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Managing insurance and financial risk when data is limited is a key task in the insurance industry. In this paper, we focus on cases where the risk distribution is modeled as a mixture with some components estimable to high precision or…

Optimization and Control · Mathematics 2026-03-03 N. D. Shyamalkumar , Tianrun Wang

We develop new adaptive algorithms for variational inequalities with monotone operators, which capture many problems of interest, notably convex optimization and convex-concave saddle point problems. Our algorithms automatically adapt to…

Machine Learning · Computer Science 2021-08-30 Alina Ene , Huy L. Nguyen

Variational analysis provides the theoretical foundations and practical tools for constructing optimization algorithms without being restricted to smooth or convex problems. We survey the central concepts in the context of a concrete but…

Optimization and Control · Mathematics 2025-04-08 Johannes O. Royset

Rough stochastic volatility models have attracted a lot of attentions recently, in particular for the linear option pricing problem. In this paper, starting with power utilities, we propose to use a martingale distortion representation of…

Mathematical Finance · Quantitative Finance 2017-12-12 Jean-Pierre Fouque , Ruimeng Hu

A variational time discretization of anisotropic Willmore flow combined with a spatial discretization via piecewise affine finite elements is presented. Here, both the energy and the metric underlying the gradient flow are anisotropic,…

Numerical Analysis · Mathematics 2015-03-25 Ricardo Perl , Paola Pozzi , Martin Rumpf

We introduce new fractional operators of variable order on isolated time scales with Mittag-Leffler kernels. This allows a general formulation of a class of fractional variational problems involving variable-order difference operators. Main…

Classical Analysis and ODEs · Mathematics 2019-02-19 Thabet Abdeljawad , Raziye Mert , Delfim F. M. Torres

Variational inference with {\alpha}-divergences has been widely used in modern probabilistic machine learning. Compared to Kullback-Leibler (KL) divergence, a major advantage of using {\alpha}-divergences (with positive {\alpha} values) is…

Machine Learning · Computer Science 2019-09-10 Dilin Wang , Hao Liu , Qiang Liu

We investigate Wiener-transformable markets, where the driving process is given by an adapted transformation of a Wiener process. This includes processes with long memory, like fractional Brownian motion and related processes, and, in…

Probability · Mathematics 2018-08-30 Elena Boguslavskaya , Yuliya Mishura , Georgiy Shevchenko

We propose a constructive framework for the super-hedging problem of a European contingent claim under proportional transaction costs in discrete time. Our main contribution is an explicit recursive scheme that computes both the…

Mathematical Finance · Quantitative Finance 2025-11-06 Emmanuel Lepinette , Amal Omrani

We give a proper fractional extension of the classical calculus of variations. Necessary optimality conditions of Euler-Lagrange type for variational problems containing both classical and fractional derivatives are proved. The fundamental…

Optimization and Control · Mathematics 2012-02-28 Tatiana Odzijewicz , Delfim F. M. Torres

We introduce a novel technique for constructing higher-order variational integrators for Hamiltonian systems of ODEs. In particular, we are concerned with generating globally smooth approximations to solutions of a Hamiltonian system. Our…

Numerical Analysis · Mathematics 2015-03-17 Melvin Leok , Tatiana Shingel

In this work, we study the problem of mean-variance hedging with a random horizon T ^ tau, where T is a deterministic constant and is a jump time of the underlying asset price process. We rst formulate this problem as a stochastic control…

Optimization and Control · Mathematics 2013-07-25 Idris Kharroubi , Thomas Lim , Armand Ngoupeyou

We prove a necessary optimality condition of Euler-Lagrange type for quantum variational problems involving Hahn's derivatives of higher-order.

Optimization and Control · Mathematics 2011-11-11 Artur M. C. Brito da Cruz , Natalia Martins , Delfim F. M. Torres

Black box variational inference allows researchers to easily prototype and evaluate an array of models. Recent advances allow such algorithms to scale to high dimensions. However, a central question remains: How to specify an expressive…

Machine Learning · Statistics 2016-06-01 Rajesh Ranganath , Dustin Tran , David M. Blei

In this paper, we propose an overlapping additive Schwarz method for total variation minimization based on a dual formulation. The $O(1/n)$-energy convergence of the proposed method is proven, where $n$ is the number of iterations. In…

Numerical Analysis · Mathematics 2021-02-05 Jongho Park

We develop a variational technique for some wide classes of nonlinear evolutions. The novelty here is that we derive the main information directly from the corresponding Euler-Lagrange equations. In particular, we prove that not only the…

Analysis of PDEs · Mathematics 2013-08-09 Arkady Poliakovsky

We examine the problem of optimal portfolio allocation within the framework of utility theory. We apply exponential utility to derive the optimal diversification strategy and logarithmic utility to determine the optimal leverage. We enhance…

Portfolio Management · Quantitative Finance 2025-10-01 Vladimir Markov

We propose a deep learning approach to study the minimal variance pricing and hedging problem in an incomplete jump diffusion market. It is based upon a rigorous stochastic calculus derivation of the optimal hedging portfolio, optimal…

Trading and Market Microstructure · Quantitative Finance 2024-07-19 Nacira Agram , Bernt Øksendal , Jan Rems

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

We have applied a collocation approach to obtain the numerical solution to the stationary Schr\"odinger equation for systems of coupled oscillators. The dependence of the discretized Hamiltonian on scale and angle parameters is exploited to…

Quantum Physics · Physics 2015-05-13 Paolo Amore , Francisco M. Fernandez
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