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DOI:10.1145/2500117 - Corpus ID: 14938340
@article{Treleaven2013AlgorithmicTR, title={Algorithmic trading review}, author={Philip C. Treleaven and Michal Galas and Vidhi Lalchand}, journal={Commun. ACM}, year={2013}, volume={56}, pages={76-85}, url={https://api.semanticscholar.org/CorpusID:14938340}}
- P. Treleaven, M. Galas, V. Lalchand
- Published in CACM 1 November 2013
- Computer Science
- Commun. ACM
The competitive nature of AT, the scarcity of expertise, and the vast profits potential, makes for a secretive community where implementation details are difficult to find.
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22 References
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In electronic financial markets, algorithmic trading refers to the use of computer programs to automate one or more stages of the trading process: pretrade analysis (data analysis), trading signal…
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This book discusses the business case for Quantitative Trading, how to identify a Strategy that suits you, and the importance of minimizing Transaction Costs.
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This book discusses the development of a Trading Strategy Design Process, the Three Principle Components of a Strategy, and the importance of accuracy in the management of risk.
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The algorithms used for automated trading and a library of algorithms developed which the author believes is unique in academia are described, which are used to study the behavior and risk of trading algorithms.
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This paper documents that strategies that buy stocks that have performed well in the past and sell stocks that hav e performed poorly in the past generate significant positive returns o ver three- to…
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This book presents a practical guide to Quantitative Trading for Investors in Quantitative Strategies and discusses the importance of data mining, analysis, and decision-making in this fast-paced environment.
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