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This paper sets up a methodology for approximately solving optimal investment problems using duality methods combined with Monte Carlo simulations. In particular, we show how to tackle high dimensional problems in incomplete markets, where…

Computational Finance · Quantitative Finance 2013-05-16 L C G Rogers , Pawel Zaczkowski

Motivated by the need to better understand the properties of sparse cutting-planes used in mixed integer programming solvers, the paper [2] studied the idealized problem of how well a polytope is approximated by the use of sparse valid…

Optimization and Control · Mathematics 2014-12-12 Santanu S. Dey , Andres Iroume , Marco Molinaro

As the development of distributed systems progresses, more and more challenges arise and the need for developing optimized systems and for optimizing existing systems from multiple perspectives becomes more stringent. In this paper I…

Data Structures and Algorithms · Computer Science 2009-03-21 Mugurel Ionut Andreica

This paper studies the optimal dividend problem with capital injection under the constraint that the cumulative dividend strategy is absolutely continuous. We consider an open problem of the general spectrally negative case and derive the…

Mathematical Finance · Quantitative Finance 2018-06-12 José-Luis Pérez , Kazutoshi Yamazaki , Xiang Yu

This paper addresses the critical problem of co-optimizing the optimal locations for orbital depots and the sequence of in-space servicing for a satellite constellation. While most traditional studies used network optimization for this…

Optimization and Control · Mathematics 2025-08-27 Euihyeon Choi , Koki Ho

In large-scale systems there are fundamental challenges when centralised techniques are used for task allocation. The number of interactions is limited by resource constraints such as on computation, storage, and network communication. We…

Artificial Intelligence · Computer Science 2022-05-12 Niall Creech , Natalia Criado Pacheco , Simon Miles

Hydro storage system optimization is becoming one of the most challenging tasks in Energy Finance. While currently the state-of-the-art of the commercial software in the industry implements mainly linear models, we would like to introduce…

Risk Management · Quantitative Finance 2017-08-28 Simone Farinelli , Luisa Tibiletti

In this paper, we investigate a distributed interval optimization problem which is modeled with optimizing a sum of convex interval-valued objective functions subject to global convex constraints, corresponding to agents over a time-varying…

Optimization and Control · Mathematics 2019-05-01 Yinghui Wang , Xianlin Zeng , Wenxiao Zhao , Yiguang Hong

In this report, we survey Bayesian Optimization methods focussed on the Multi-Armed Bandit Problem. We take the help of the paper "Portfolio Allocation for Bayesian Optimization". We report a small literature survey on the acquisition…

Machine Learning · Computer Science 2020-12-16 Abhilash Nandy , Chandan Kumar , Deepak Mewada , Soumya Sharma

In this paper, we search for optimal portfolio strategies in the presence of various risk measure that are common in financial applications. Particularly, we deal with the static optimization problem with respect to Value at Risk, Expected…

Portfolio Management · Quantitative Finance 2019-12-23 Alev Meral

We study an optimal execution problem in the infinite horizon setup. Our financial market is given by the Black-Scholes model with a linear price impact. The main novelty of the current note is that we study the constrained case where the…

Mathematical Finance · Quantitative Finance 2024-11-20 Yan Dolinsky

We study the allocation strategies for redundant components in the load-sharing series/parallel systems. We show that under the specified assumptions, the allocation of a redundant component to the stochastically weakest (strongest)…

Applications · Statistics 2016-02-18 Maxim Finkelstein , Nil Kamal Hazra

Many allocation problems in multiagent systems rely on agents specifying cardinal preferences. However, allocation mechanisms can be sensitive to small perturbations in cardinal preferences, thus causing agents who make ``small" or…

Computer Science and Game Theory · Computer Science 2021-07-13 Vijay Menon , Kate Larson

This paper firstly addresses the problem of risk assessment under false data injection attacks on uncertain control systems. We consider an adversary with complete system knowledge, injecting stealthy false data into an uncertain control…

Systems and Control · Electrical Eng. & Systems 2022-12-12 Sribalaji C. Anand , André M. H. Teixeira , Anders Ahlén

Optimal trading strategies for pairs trading have been studied by models that try to find either optimal shares of stocks by assuming no transaction costs or optimal timing of trading fixed numbers of shares of stocks with transaction…

Trading and Market Microstructure · Quantitative Finance 2019-11-26 Haipeng Xing

Placement Optimization is an important problem in systems and chip design, which consists of mapping the nodes of a graph onto a limited set of resources to optimize for an objective, subject to constraints. In this paper, we start by…

Artificial Intelligence · Computer Science 2020-03-20 Anna Goldie , Azalia Mirhoseini

The pooling problem has applications, e.g., in petrochemical refining, water networks, and supply chains and is widely studied in global optimization. To date, it has largely been treated deterministically, neglecting the influence of…

Optimization and Control · Mathematics 2019-06-19 Johannes Wiebe , Inês Cecílio , Ruth Misener

We examine the problem of the existence of optimal deterministic stationary strategiesintwo-players antagonistic (zero-sum) perfect information stochastic games with finitely many states and actions.We show that the existenceof such…

Computer Science and Game Theory · Computer Science 2016-11-28 Hugo Gimbert , Wieslaw Zielonka

We consider the problem of finding optimally stable polynomial approximations to the exponential for application to one-step integration of initial value ordinary and partial differential equations. The objective is to find the largest…

Numerical Analysis · Mathematics 2013-01-10 David I. Ketcheson , Aron J. Ahmadia

We propose a novel pooling strategy that learns how to adaptively rank deep convolutional features for selecting more informative representations. To this end, we exploit discriminative analysis to project the features onto a space spanned…

Machine Learning · Computer Science 2017-10-23 Arash Shahriari , Fatih Porikli
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