Abstract
Actionable trading strategies for trading agents determine the potential of the simulated models in real-life markets. The development of actionable strategies is a non-trivial task, which needs to consider real-life constraints and organizational factors in the market. In this paper, we first analyze such constraints on developing actionable trading strategies. Further we propose an actionable trading strategy development framework. These points are deployed into developing a series of actionable trading strategies through optimizing, enhancing, discovering and integrating actionable trading strategies. We demonstrate working case studies in market data. These approaches and their performance are evaluated from both technical and business perspectives. Actionable trading strategies have potential to supporting smart trading decision for brokerage firms and financial companies.
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Cao, L. (2009). Developing Actionable Trading Strategies. In: Jain, L.C., Nguyen, N.T. (eds) Knowledge Processing and Decision Making in Agent-Based Systems. Studies in Computational Intelligence, vol 170. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88049-3_9
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DOI: https://doi.org/10.1007/978-3-540-88049-3_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88048-6
Online ISBN: 978-3-540-88049-3
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