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We study the problem of finding the worst-case joint distribution of a set of risk factors given prescribed multivariate marginals and a nonlinear loss function. We show that when the risk measure is CVaR, and the distributions are…

Risk Management · Quantitative Finance 2016-10-31 Amir Memartoluie , David Saunders , Tony Wirjanto

We consider the problem of optimizing a portfolio of financial assets, where the number of assets can be much larger than the number of observations. The optimal portfolio weights require estimating the inverse covariance matrix of excess…

Portfolio Management · Quantitative Finance 2021-09-29 Anik Burman , Sayantan Banerjee

Risk control and optimal diversification constitute a major focus in the finance and insurance industries as well as, more or less consciously, in our everyday life. We present a discussion of the characterization of risks and of the…

Statistical Mechanics · Physics 2015-06-25 Didier Sornette

Portfolio optimization has long been dominated by covariance-based strategies, such as the Markowitz Mean-Variance framework. However, these approaches often fail to ensure a balanced risk structure across assets, leading to concentration…

Portfolio Management · Quantitative Finance 2025-08-07 Biswarup Chakraborty

This paper is concerned with the uniqueness issue of open-loop equilibrium investment strategies of dynamic mean-variance portfolio selection problems with random coefficients. A unified method is developed to treat both the problems with…

Optimization and Control · Mathematics 2018-02-06 Tianxiao Wang

A refinement of Bennett's inequality is introduced which is strictly tighter than the classical bound. The new bound establishes the convergence of the average of independent random variables to its expected value. It also carefully…

Statistics Theory · Mathematics 2018-04-17 Tony Jebara

We consider a distributionally robust formulation of stochastic optimization problems arising in statistical learning, where robustness is with respect to uncertainty in the underlying data distribution. Our formulation builds on…

Optimization and Control · Mathematics 2021-06-09 Mert Gürbüzbalaban , Andrzej Ruszczyński , Landi Zhu

Modern portfolio theory has provided for decades the main framework for optimizing portfolios. Because of its sensitivity to small changes in input parameters, especially expected returns, the mean-variance framework proposed by Markowitz…

Portfolio Management · Quantitative Finance 2023-09-06 Adil Rengim Cetingoz , Jean-David Fermanian , Olivier Guéant

Kelly's Criterion is well known among gamblers and investors as a method for maximizing the returns one would expect to observe over long periods of betting or investing. These ideas are conspicuously absent from portfolio optimization…

Portfolio Management · Quantitative Finance 2018-02-20 Zachariah Peterson

Optimal capital allocation between different assets is an important financial problem, which is generally framed as the portfolio optimization problem. General models include the single-period and multi-period cases. The traditional…

Portfolio Management · Quantitative Finance 2019-03-18 Masoud Fekri , Babak Barazandeh

We consider the problem of mean-variance portfolio optimization for a generic covariance matrix subject to the budget constraint and the constraint for the expected return, with the application of the replica method borrowed from the…

Portfolio Management · Quantitative Finance 2017-01-04 Istvan Varga-Haszonits , Fabio Caccioli , Imre Kondor

Given a set of assets and an investment capital, the classical portfolio selection problem consists in determining the amount of capital to be invested in each asset in order to build the most profitable portfolio. The portfolio…

Portfolio Management · Quantitative Finance 2019-07-17 Justo Puerto , Moises Rodríguez-Madrena , Andrea Scozzari

One of the most interesting problems discerned when applying the Black--Scholes model to financial derivatives, is reconciling the deviation between expected and observed values. In our recent work, we derived a new model based on the…

Analysis of PDEs · Mathematics 2014-09-16 Shin-ichi Doi , Yasushi Ota

When an inverse problem is solved by a gradient-based optimization algorithm, the corresponding forward and adjoint problems, which are introduced to compute the gradient, can be also solved iteratively. The idea of iterating at the same…

Numerical Analysis · Mathematics 2025-01-23 Marcella Bonazzoli , Houssem Haddar , Tuan Anh Vu

This paper considers a newly delayed reinsurance and investment optimization problem incorporating random risk aversion, in which an insurer pursues maximization of the expected certainty equivalent of her/his terminal wealth and the…

Optimization and Control · Mathematics 2026-01-23 Jian-hao Kang , Zhun Gou , Nan-jing Huang

The paper addresses general constrained and non-linear optimization problems. For some of these notoriously hard problems, there exists a reformulation as an unconstrained, global optimization problem. We illustrate the transformation, and…

Optimization and Control · Mathematics 2023-06-13 Vladimir Norkin , Alois Pichler

Entropy based ideas find wide-ranging applications in finance for calibrating models of portfolio risk as well as options pricing. The abstracted problem, extensively studied in the literature, corresponds to finding a probability measure…

Statistical Finance · Quantitative Finance 2014-11-04 Santanu Dey , Sandeep Juneja , Karthyek R. A. Murthy

In this paper we present an evolutionary optimization approach to solve the risk parity portfolio selection problem. While there exist convex optimization approaches to solve this problem when long-only portfolios are considered, the…

Portfolio Management · Quantitative Finance 2015-04-14 Ronald Hochreiter

In this paper we consider a generalization of the Markowitz's Mean-Variance model under linear transaction costs and cardinality constraints. The cardinality constraints are used to limit the number of assets in the optimal portfolio. The…

Computational Engineering, Finance, and Science · Computer Science 2014-04-15 Mahdi Moeini

In black-box optimization, a central question is which algorithm to use to solve a given, previously unseen, problem. Selecting a single algorithm, however, entails inherent risks: inaccuracies in the selector may lead to poor choices, and…

Neural and Evolutionary Computing · Computer Science 2026-04-21 Catalin-Viorel Dinu , Diederick Vermetten , Carola Doerr
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