algosel - Algorithm Selection: A Quantitative Approach JIAN...

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Algorithm Selection: A Quantitative Approach J IAN Y ANG AND B RETT J IU April 25, 2006 Abstract The widespread use of algorithmic trading has led to the question of whether the most suitable algorithm is always being used. We propose a practical framework to help traders qualitatively characterize algorithms as well as quantitatively evaluate comparative performance among vari- ous algorithms. We demonstrate the applicability of the quantitative model using historical data from orders executed through ITG Algorithms. B RETT J IU is a senior research analyst at ITG Solutions Network, Inc., 44 Farnsworth Street, Boston MA 02210, Tel: (617)-692-6741; E-mail: bjiu @itginc.com J IAN Y ANG is a senior vice president at ITG Solutions Network, Inc., 44 Farnsworth Street, Boston MA 02210, Tel: (617)-692-6860; E-mail: jyang@itginc.com The authors wish to thank Milan Borkovec, Gabe Butler, Vitaly Serbin, Xiangyang Wang, James Wong, Henry Yegerman and Ian Domowitz all of ITG Inc., as well as Yingchuan Wang for their support and comments. The information contained herein is for informational purposes only. Nothing herein is investment advice as de- fined by the Investment Advisers Act of 1940. ITG Inc. does not guarantee its accuracy or completeness and ITG Inc. does not make any warranties regarding results from usage. Any opinions expressed herein reflect the judgment of the authors at the time of publication and are subject to change without notice and may not reflect the opinion of ITG Inc. This communication is neither an offer to sell nor a solicitation of an offer to buy any security or financial instrument in any jurisdiction where such offer or solicitation would be illegal. All trademarks not owned by ITG are owned by their respective owners. © 2006, ITG Inc. Member NASD, SIPC. All rights reserved. Compliance #22206-64331
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he relentless pursuit of lower transaction costs has led to increasing demand for sophis- ticated trading tools and algorithms, which in turn has led to an explosion in the num- ber of algorithmic products offered in the marketplace today. Yang and Borkovec [2005] predict that this trend will continue as more investment management firms em- brace best execution as a top priority. T Having more algorithms at their disposal offers traders both opportunities and challenges. On the up side, a trader now has the opportunity to pick the suitable algorithm that will most likely achieve the trading objective for each order. On the down side, the number of algorithm choices can be so large as to make it difficult to make a quick and correct choice. 1 Adding to the algorithm selection challenge is the fact that algorithms offered by sell-side vendors usually come in the form of a “black box,” with inner workings hidden to the end users. Because of this lack of transparency, users may find it difficult to clearly understand the per-
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algosel - Algorithm Selection: A Quantitative Approach JIAN...

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