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In this paper we study optimal investment when the investor can peek some time units into the future, but cannot fully take advantage of this knowledge because of quadratic transaction costs. In the Bachelier setting with exponential…

Mathematical Finance · Quantitative Finance 2022-05-04 Peter Bank , Yan Dolinsky , Miklós Rásonyi

We consider a multi-stock continuous time incomplete market model with random coefficients. We study the investment problem in the class of strategies which do not use direct observations of the appreciation rates of the stocks, but rather…

Mathematical Finance · Quantitative Finance 2015-02-10 Nikolai Dokuchaev

Bayesian decision theory outlines a rigorous framework for making optimal decisions based on maximizing expected utility over a model posterior. However, practitioners often do not have access to the full posterior and resort to approximate…

Machine Learning · Statistics 2019-10-29 Tomasz Kuśmierczyk , Joseph Sakaya , Arto Klami

We introduce a linear space of finitely additive measures to treat the problem of optimal expected utility from consumption under a stochastic clock and an unbounded random endowment process. In this way we establish existence and…

Probability · Mathematics 2008-12-10 Gordan Zitkovic

This working paper presents a comprehensive study on the development and analysis of various electricity market models, focusing on continuous, discrete, and fractional-order approaches. The continuous model captures the ongoing…

Optimization and Control · Mathematics 2024-07-29 Ioannis Dassios

We study arbitrage opportunities, market viability and utility maximization in market models with an insider. Assuming that an economic agent possesses from the beginning an additional information in the form of a random variable G, which…

Risk Management · Quantitative Finance 2016-10-03 Ngoc Huy Chau , Wolfgang Runggaldier , Peter Tankov

We give a general formulation of the utility maximization problem under nondominated model uncertainty in discrete time and show that an optimal portfolio exists for any utility function that is bounded from above. In the unbounded case,…

Portfolio Management · Quantitative Finance 2013-07-16 Marcel Nutz

We study S-shaped utility maximisation with VaR constraint and unobservable drift coefficient. Using the Bayesian filter, the concavification principle, and the change of measure, we give a semi-closed integral representation for the dual…

Mathematical Finance · Quantitative Finance 2025-06-13 Dongmei Zhu , Ashley Davey , Harry Zheng

We present a general two-side market model with divisible commodities and price functions of participants. A general existence result on unbounded sets is obtained from its variational inequality re-formulation. We describe an extension of…

Optimization and Control · Mathematics 2017-06-14 Igor Konnov

In this paper we study a robust utility maximization problem in continuous time under model uncertainty. The model uncertainty is governed by a continuous semimartingale with uncertain local characteristics. Here, the differential…

Mathematical Finance · Quantitative Finance 2023-08-04 David Criens , Lars Niemann

We study a general robust utility maximization problem in a discrete-time frictionless market. The investor is assumed to have a possibly infinite, random, nonconcave, and nondecreasing utility function defined on the whole real line. She…

Mathematical Finance · Quantitative Finance 2025-10-14 Laurence Carassus , Massinissa Ferhoune

An innovative extension of Geometric Brownian Motion model is developed by incorporating a weighting factor and a stochastic function modelled as a mixture of power and trigonometric functions. Simulations based on this Modified Brownian…

Pricing of Securities · Quantitative Finance 2015-07-09 Gurjeet Dhesi , Muhammad Bilal Shakeel , Ling Xiao

This paper studies the problem of maximizing the expected utility of terminal wealth for a financial agent with an unbounded random endowment, and with a utility function which supports both positive and negative wealth. We prove the…

Portfolio Management · Quantitative Finance 2008-12-10 Mark Owen , Gordan Zitkovic

In this paper, we study expected utility maximization under ratchet and drawdown constraints on consumption in a general incomplete semimartingale market using duality methods. The optimization is considered with respect to two parameters:…

Optimization and Control · Mathematics 2022-07-19 Anastasiya Tanana

Gaussian Process based Bayesian Optimization is a well-known sample efficient sequential strategy for globally optimizing black-box, expensive, and multi-extremal functions. The role of the Gaussian Process is to provide a probabilistic…

Machine Learning · Computer Science 2023-05-16 Antonio Candelieri

Stochastic volatility models based on Gaussian processes, like fractional Brownian motion, are able to reproduce important stylized facts of financial markets such as rich autocorrelation structures, persistence and roughness of sample…

Probability · Mathematics 2022-05-10 Eduardo Abi Jaber

A model for decision making that generalizes Expected Utility Maximization is presented. This model, Expected Qualitative Utility Maximization, encompasses the Maximin criterion. It relaxes both the Independence and the Continuity…

Computer Science and Game Theory · Computer Science 2007-05-23 Daniel Lehmann

We consider an infinite dimensional optimization problem motivated by mathematical economics. Within the celebrated "Arbitrage Pricing Model", we use probabilistic and functional analytic techniques to show the existence of optimal…

Mathematical Finance · Quantitative Finance 2017-03-10 Miklos Rasonyi

The aim of this short note is to present a solution to the discrete time exponential utility maximization problem in a case where the underlying asset has a multivariate normal distribution. In addition to the usual setting considered in…

Mathematical Finance · Quantitative Finance 2023-06-27 Yan Dolinsky , Or Zuk

In machine learning, knowing the impact of a given datum on model training is a fundamental task referred to as Data Valuation. Building on previous works from the literature, we have designed a novel canonical decomposition allowing…

Machine Learning · Computer Science 2025-06-05 Clément Bénesse , Patrick Mesana , Athénaïs Gautier , Sébastien Gambs
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