Online Algorithms in Trading Systems

A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Randomized, Online, and Approximation Algorithms".

Deadline for manuscript submissions: closed (30 June 2020) | Viewed by 3117

Special Issue Editors


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Guest Editor
Department of Informatics, University of Leicester, University Road, Leicester, LE1 7RH, UK
Interests: online algorithms; scheduling algorithms

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Co-Guest Editor
Department of Operations Research and Business Informatics, Saarland University, 66123 Saarbrücken, Germany
Interests: combinatorial optimization; scheduling; conversion and trading
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Special Issue Information

Dear Colleagues,

Online algorithms handle situations where the future input is unknown. Since competitive analysis was first introduced in the mid-1980s, online algorithms have been studied for a wide range of problems, and naturally this includes those involving financial markets and trading. As algorithmic and high-frequency trading become increasingly prevalent, many new algorithmic questions and challenges arise.

For this Special Issue, we invite submissions of articles that describe recent advances in the design and analysis of online algorithms for trading systems (broadly defined). Both original research papers and surveys are welcome. Topics of interest include, but are not limited to:

  • Time series search
  • Trading strategies
  • Portfolio optimization
  • Hedging and risk management
  • Pricing and market clearing
  • Auction systems
  • Mechanism design and other game-theoretic issues
  • Empirical evaluation of algorithm performance

Dr. Stanley P. Y. Fung
Prof. Dr. Günter Schmidt
Guest Editor

Manuscript Submission Information

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Published Papers (1 paper)

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Research

12 pages, 239 KiB  
Article
Lower and Upper Bounds for the Discrete Bi-Directional Preemptive Conversion Problem with a Constant Price Interval
by Michael Schwarz
Algorithms 2020, 13(2), 42; https://doi.org/10.3390/a13020042 - 18 Feb 2020
Cited by 1 | Viewed by 2747
Abstract
In the conversion problem, wealth has to be distributed between two assets with the objective to maximize the wealth at the end of the investment horizon. The bi-directional preemptive conversion problem with a constant price interval is the only problem, of the four [...] Read more.
In the conversion problem, wealth has to be distributed between two assets with the objective to maximize the wealth at the end of the investment horizon. The bi-directional preemptive conversion problem with a constant price interval is the only problem, of the four main variants of the conversion problem, that has not yet been optimally solved by competitive analysis. Assuming a given number of monotonous price trends called runs, lower and upper bounds for the competitive ratio are given. In this work, the assumption of a given number of runs is rejected and lower and upper bounds for the bi-directional preemptive conversion problem with a constant price interval are given. Furthermore, an algorithm based on error balancing is given which at minimum achieves the given upper bound. It can also be shown that this algorithm is optimal for the single-period model. Full article
(This article belongs to the Special Issue Online Algorithms in Trading Systems)
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