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DOI: 10.14569/IJACSA.2019.0100675
PDF

Competitive Algorithms for Online Conversion Problem with Interrelated Prices

Author 1: Javeria Iqbal
Author 2: Iftikhar Ahmad
Author 3: Asadullah Shah

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 6, 2019.

  • Abstract and Keywords
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Abstract: The classical uni-directional conversion algorithms are based on the assumption that prices are arbitrarily chosen from the fixed price interval [m,M] where m and M represent the estimated lower and upper bounds of possible prices 0 < m <= M. The estimated interval is erroneous and no attempts are made by the algorithms to update the erroneous estimates. We consider a real world setting where prices are interrelated, i.e., each price depends on its preceding price. Under this assumption, we derive a lower bound on the competitive ratio of randomized non-preemptive algorithms. Motivated by the fixed and erroneous price bounds, we present an update model that progressively improves the bounds. Based on the update model, we propose a non-preemptive reservation price algorithm RP* and analyze it under competitive analysis. Finally, we report the findings of an experimental study that is conducted over the real world stock index data. We observe that RP* consistently outperforms the classical algorithm.

Keywords: Time series search; one-way trading; online algo-rithms; update model

Javeria Iqbal, Iftikhar Ahmad and Asadullah Shah, “Competitive Algorithms for Online Conversion Problem with Interrelated Prices” International Journal of Advanced Computer Science and Applications(IJACSA), 10(6), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100675

@article{Iqbal2019,
title = {Competitive Algorithms for Online Conversion Problem with Interrelated Prices},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100675},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100675},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {6},
author = {Javeria Iqbal and Iftikhar Ahmad and Asadullah Shah}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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