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In this paper we study a continuous-time stochastic linear quadratic control problem arising from mathematical finance. We model the asset dynamics with random market coefficients and portfolio strategies with convex constraints. Following…

Portfolio Management · Quantitative Finance 2017-05-24 Yusong Li , Harry Zheng

In this paper, we consider the chance constrained based uncertain portfolio optimization problem in which the uncertain parameters are stochastic in nature. The primary goal of the work is to formulate the uncertain problem into a…

Optimization and Control · Mathematics 2023-11-09 Pulak Swain , Akshay Kumar Ojha

Decision-changing imitation is a prevalent phenomenon in financial markets, where investors imitate others' decision-changing rates when making their own investment decisions. In this work, we study the optimal investment problem under the…

Systems and Control · Electrical Eng. & Systems 2024-10-07 Huisheng Wang , H. Vicky Zhao

We survey research that studies the connection between the computational complexity of optimization problems on the one hand, and the duality gap between the primal and dual optimization problems on the other. To our knowledge, this is the…

Optimization and Control · Mathematics 2011-11-16 Prabhu Manyem

We consider the problem of choosing an optimal portfolio, assuming the asset returns have a Gaussian mixture (GM) distribution, with the objective of maximizing expected exponential utility. In this paper we show that this problem is…

Optimization and Control · Mathematics 2022-08-12 Eric Luxenberg , Stephen Boyd

The paper solves the problem of optimal portfolio choice when the parameters of the asset returns distribution, like the mean vector and the covariance matrix are unknown and have to be estimated by using historical data of the asset…

Statistical Finance · Quantitative Finance 2023-04-19 David Bauder , Taras Bodnar , Nestor Parolya , Wolfgang Schmid

We study the problem of super-resolution, where we recover the locations and weights of non-negative point sources from a few samples of their convolution with a Gaussian kernel. It has been recently shown that exact recovery is possible by…

Optimization and Control · Mathematics 2019-05-09 Stephane Chretien , Andrew Thompson , Bogdan Toader

We consider a Markov chain approximation scheme for utility maximization problems in continuous time, which uses, in turn, a piecewise constant policy approximation, Euler-Maruyama time stepping, and a Gauss-Hermite approximation of the…

Optimization and Control · Mathematics 2020-01-07 Athena Picarelli , Christoph Reisinger

Convex duality for two two different super--replication problems in a continuous time financial market with proportional transaction cost is proved. In this market, static hedging in a finite number of options, in addition to usual dynamic…

Mathematical Finance · Quantitative Finance 2015-10-20 Yan Dolinsky , H. Mete Soner

In this paper, the optimal mean-reverting portfolio (MRP) design problem is considered, which plays an important role for the statistical arbitrage (a.k.a. pairs trading) strategy in financial markets. The target of the optimal MRP design…

Portfolio Management · Quantitative Finance 2018-03-09 Ziping Zhao , Rui Zhou , Zhongju Wang , Daniel P. Palomar

We consider a discrete time financial market with proportional transaction cost under model uncertainty, and study a super-replication problem. We recover the duality results that are well known in the classical dominated context. Our key…

Probability · Mathematics 2017-07-31 Bruno Bouchard , Shuoqing Deng , Xiaolu Tan

We show that, in a resource allocation problem, the ex ante aggregate utility of players with cumulative-prospect-theoretic preferences can be increased over deterministic allocations by implementing lotteries. We formulate an optimization…

Theoretical Economics · Economics 2020-12-07 Soham R. Phade , Venkat Anantharam

Attention to data-driven optimization approaches, including the well-known stochastic gradient descent method, has grown significantly over recent decades, but data-driven constraints have rarely been studied, because of the computational…

Machine Learning · Computer Science 2023-10-11 Shuoguang Yang , Xudong Li , Guanghui Lan

This thesis investigates Merton's portfolio problem under two different rough Heston models, which have a non-Markovian structure. The motivation behind this choice of problem is due to the recent discovery and success of rough volatility…

Mathematical Finance · Quantitative Finance 2019-09-09 Benjamin James Duthie

This paper is concerned with the study of constrained statistical learning problems, the unconstrained version of which are at the core of virtually all of modern information processing. Accounting for constraints, however, is paramount to…

Machine Learning · Computer Science 2020-02-14 Luiz F. O. Chamon , Santiago Paternain , Miguel Calvo-Fullana , Alejandro Ribeiro

We consider a generic convex optimization problem associated with regularized empirical risk minimization of linear predictors. The problem structure allows us to reformulate it as a convex-concave saddle point problem. We propose a…

Optimization and Control · Mathematics 2015-09-10 Yuchen Zhang , Lin Xiao

We consider a financial market with one riskless and one risky asset. The super-replication theorem states that there is no duality gap in the problem of super-replicating a contingent claim under transaction costs and the associated dual…

Probability · Mathematics 2014-05-07 Walter Schachermayer

This paper studies a continuous-time optimal portfolio selection problem in the complete market for a behavioral investor whose preference is of the prospect type with probability distortion. The investor concerns about the terminal…

Portfolio Management · Quantitative Finance 2022-11-11 Jing Peng , Pengyu Wei , Zuo Quan Xu

We consider mixed model of traffic flow distribution in large networks (BMW model, 1954 & Stable Dynamic model, 1999). We build dual problem and consider primal-dual mirror descent method for the dual problem. There are two ways to recover…

Optimization and Control · Mathematics 2018-08-16 Alexander Gasnikov , Evgenia Gasnikova , Yurii Nesterov

Performative prediction is a recently proposed framework where predictions guide decision-making and hence influence future data distributions. Such performative phenomena are ubiquitous in various areas, such as transportation, finance,…

Machine Learning · Computer Science 2023-09-25 Wenjing Yan , Xuanyu Cao
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