License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license (CC BY-NC-ND 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.SCOR.2012.43
URN: urn:nbn:de:0030-drops-35455
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2012/3545/
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Iqbal, Javeria ; Ahmad, Iftikhar ; Schmidt, Günter

Can online trading algorithms beat the market? An experimental evaluation

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Abstract

From experimental evaluation, we reasonably infer that online trading algorithms can beat the market. We consider the scenario of trading in financial market and present an extensive experimental study to answer the question "Can online trading algorithms beat the market?". We evaluate the selected set of online trading algorithms on DAX30 and measure the performance against buy-and-hold strategy. In order to compute the experimentally achieved competitive ratio, we also compare the set of algorithms against an optimum offline algorithm. To add further dimensionality into experimental setup, we use trading periods of various lengths and apply a number of evaluation criteria (such as annualized geometric returns, average period returns and experimentally achieved competitive ratio) to measure the performance of algorithms in short vs. Long term investment decisions. We highlight the best and worst performing algorithms and discuss the possible reasons for the performance behavior of algorithms.

BibTeX - Entry

@InProceedings{iqbal_et_al:OASIcs:2012:3545,
  author =	{Javeria Iqbal and Iftikhar Ahmad and G{\"u}nter Schmidt},
  title =	{{Can online trading algorithms beat the marketl An experimental evaluation}},
  booktitle =	{3rd Student Conference on Operational Research},
  pages =	{43--52},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-39-2},
  ISSN =	{2190-6807},
  year =	{2012},
  volume =	{22},
  editor =	{Stefan Ravizza and Penny Holborn},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2012/3545},
  URN =		{urn:nbn:de:0030-drops-35455},
  doi =		{10.4230/OASIcs.SCOR.2012.43},
  annote =	{Keywords: Online Algorithms, Experimental Evaluation, Competitive Analysis}
}

Keywords: Online Algorithms, Experimental Evaluation, Competitive Analysis
Collection: 3rd Student Conference on Operational Research
Issue Date: 2012
Date of publication: 26.06.2012

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