Algorithmic Trading

descriptionPublicationkeyboard_double_arrow_right Article 01 Nov 2011Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:Computer, volume 44, pages 61-69 (issn: 0018-9162,

Copyright policy )

Authors: Giuseppe Nuti; Mahnoosh Mirghaemi; Philip C. Treleaven; Chaiyakorn Yingsaeree;

doi: 10.1109/mc.2011.31

Algorithmic Trading

- Summary
- Metrics

Abstract

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 generation (buy and sell recommendations), and trade execution. Trade execution is further divided into agency/broker execution (when a system optimizes the execution of a trade on behalf of a client) and principal/proprietary trading (where an institution trades on its own account). Each stage of this trading process can be conducted by humans, by humans and algorithms, or fully by algorithms.

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	72
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 1%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%