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In this paper we propose a computationally efficient algorithm for on-line variable selection in multivariate regression problems involving high dimensional data streams. The algorithm recursively extracts all the latent factors of a…

Machine Learning · Statistics 2009-02-10 Brian McWilliams , Giovanni Montana

This paper studies the optimal clearing problem for prosumers in peer-to-peer (P2P) energy markets. It is proved that if no trade weights are enforced and the communication structure between successfully traded peers is connected, then the…

Systems and Control · Electrical Eng. & Systems 2020-09-02 Dinh Hoa Nguyen

In the seminal paper on optimal execution of portfolio transactions, Almgren and Chriss (2001) define the optimal trading strategy to liquidate a fixed volume of a single security under price uncertainty. Yet there exist situations, such as…

Trading and Market Microstructure · Quantitative Finance 2022-12-06 Julien Vaes , Raphael Hauser

In this paper, we consider distributed optimization design for resource allocation problems over weight-balanced graphs. With the help of singular perturbation analysis, we propose a simple sub-optimal continuous-time optimization…

Optimization and Control · Mathematics 2022-06-14 Shu Liang , Xianlin Zeng , Yiguang Hong

This work initiates research into the problem of determining an optimal investment strategy for investors with different attitudes towards the trade-offs of risk and profit. The probability distribution of the return values of the stocks…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Ming-Yang Kao , Andreas Nolte , Stephen R. Tate

Compute-and-forward (CF) is a relaying strategy which allows the relay to decode a linear combination of the transmitted messages. This work studies the optimal power allocation problem for the CF scheme in fast fading channels for…

Information Theory · Computer Science 2024-11-18 Lanwei Zhang , Jamie Evans , Jingge Zhu

In this paper we show how to implement in a simple way some complex real-life constraints on the portfolio optimization problem, so that it becomes amenable to quantum optimization algorithms. Specifically, first we explain how to obtain…

Portfolio Management · Quantitative Finance 2021-08-23 Samuel Palmer , Serkan Sahin , Rodrigo Hernandez , Samuel Mugel , Roman Orus

We introduce a financial portfolio optimization framework that allows us to automatically select the relevant assets and estimate their weights by relying on a sorted $\ell_1$-Norm penalization, henceforth SLOPE. Our approach is able to…

Portfolio Management · Quantitative Finance 2021-07-30 Philipp J. Kremer , Sangkyun Lee , Malgorzata Bogdan , Sandra Paterlini

With the tremendous increase of the Internet traffic, achieving the best performance with limited resources is becoming an extremely urgent problem. In order to address this concern, in this paper, we build an optimization problem which…

Physics and Society · Physics 2017-02-23 Li Rui , Xia Yongxiang , Tse K Chi

Blockchain technology, while revolutionary in enabling decentralized transactions, faces scalability challenges as the ledger must be replicated across all nodes of the chain, limiting throughput and efficiency. Sharding, which divides the…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-09 Björn Assmann , Samuel J. Burri

We consider a two-way trading problem, where investors buy and sell a stock whose price moves within a certain range. Naturally they want to maximize their profit. Investors can perform up to $k$ trades, where each trade must involve the…

Data Structures and Algorithms · Computer Science 2017-06-19 Stanley P. Y. Fung

In this work, we propose a hybrid variant of the level-based learning swarm optimizer (LLSO) for solving large-scale portfolio optimization problems. Our goal is to maximize a modified formulation of the Sharpe ratio subject to cardinality,…

Optimization and Control · Mathematics 2022-06-30 Massimiliano Kaucic , Filippo Piccotto , Gabriele Sbaiz , Giorgio Valentinuz

In this paper we consider multiple constrained resource allocation problems, where the constraints can be specified by formulating activity dependency restrictions or by using game-theoretic models. All the problems are focused on generic…

Data Structures and Algorithms · Computer Science 2009-06-19 Mugurel Ionut Andreica , Madalina Ecaterina Andreica , Costel Visan

Load balancing, operator instance collocations and horizontal scaling are critical issues in Parallel Stream Processing Engines to achieve low data processing latency, optimized cluster utilization and minimized communication cost…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-02-12 Kasper Grud Skat Madsen , Yongluan Zhou , Jianneng Cao

This paper studies online optimization under inventory (budget) constraints. While online optimization is a well-studied topic, versions with inventory constraints have proven difficult. We consider a formulation of inventory-constrained…

Performance · Computer Science 2024-12-20 Qiulin Lin , Hanling Yi , John Pang , Minghua Chen , Adam Wierman , Michael Honig , Yuanzhang Xiao

Optimizing portfolio performance is a fundamental challenge in financial modeling, requiring the integration of advanced clustering techniques and data-driven optimization strategies. This paper introduces a comparative backtesting approach…

Machine Learning · Computer Science 2025-01-23 Keon Vin Park

We consider robust pricing and hedging for options written on multiple assets given market option prices for the individual assets. The resulting problem is called the multi-marginal martingale optimal transport problem. We propose two…

Probability · Mathematics 2020-10-08 Stephan Eckstein , Gaoyue Guo , Tongseok Lim , Jan Obloj

We study a game-theoretic variant of the maximum circulation problem. In a flow allocation game, we are given a directed flow network. Each node is a rational agent and can strategically allocate any incoming flow to the outgoing edges.…

Computer Science and Game Theory · Computer Science 2023-12-22 Nils Bertschinger , Martin Hoefer , Daniel Schmand

We consider the problem of the statistical uncertainty of the correlation matrix in the optimization of a financial portfolio. We show that the use of clustering algorithms can improve the reliability of the portfolio in terms of the ratio…

Physics and Society · Physics 2008-12-02 Vincenzo Tola , Fabrizio Lillo , Mauro Gallegati , Rosario N. Mantegna

This paper presents how the most recent improvements made on covariance matrix estimation and model order selection can be applied to the portfolio optimisation problem. The particular case of the Maximum Variety Portfolio is treated but…

Applications · Statistics 2018-04-03 Emmanuelle Jay , Eugénie Terreaux , Jean-Philippe Ovarlez , Frédéric Pascal