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An Introduction To Regret Minimization In Algorithmic Trading: A Survey of Universal Portfolio Techniques

2021/05/26 by Thomas G. Orton, Orton, Thomas
Computer Science · Decision Sciences · Economics, Econometrics and Finance · Engineering · #Advanced Bandit Algorithms Research #Computational Engineering #FOS: Computer and information sciences #FOS: Economics and business #Finance #Financial Markets and Investment Strategies #Portfolio Management (q-fin.PM) #Reinforcement Learning in Robotics #Reservoir Engineering and Simulation Methods #Stochastic processes and financial applications #and Science (cs.CE)

paper · pdf · doi:10.48550/arxiv.2105.13126

openalex publication_date 2021/05/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In financial investing, universal portfolios are a means of constructing portfolios which guarantee a certain level of performance relative to a baseline, while making no statistical assumptions about the future market data. They fall under the broad category of regret minimization algorithms. This document covers an introduction and survey to universal portfolio techniques, covering some of the basic concepts and proofs in the area. Topics include: Constant Rebalanced Portfolios, Cover's Algorithm, Incorporating Transaction Costs, Efficient Computation of Portfolios, Including Side Information, and Follow The Leader Algorithm.

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