Abstract
Financial markets are highly volatile and decision making in these markets is highly risky. With the introduction of automated trading, a number of techniques are developed to facilitate the automation of financial markets. We consider a set of preemptive as well as non-preemptive online algorithms and evaluate them on real world as well as synthetically produced data. We present extensive computational results based on the observed performance of algorithms in terms of experimentally achieved competitive ratio, number of transactions performed and consistency of the results. We also investigate the gap between the worst case competitive ratio and experimentally achieved competitive ratio and conclude that algorithms perform better than their performance guarantee suggest. We conclude by highlighting a number of open questions.
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Ahmad, I., Schmidt, G. (2012). An Experimental Analysis of Online Unidirectional Conversion Problem. In: Huemer, C., Lops, P. (eds) E-Commerce and Web Technologies. EC-Web 2012. Lecture Notes in Business Information Processing, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32273-0_15
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DOI: https://doi.org/10.1007/978-3-642-32273-0_15
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