Abstract
In Chapter 12 we discussed reinforcement learning, in which we optimise a function that is state-dependent. In this chapter we look at a portfolio of assets which is modified at each time step. If transactions costs are applied to all asset changes (as is the case in all real situations), then we have a state-dependent system and the principles of Chapter 12 apply. We will, however, extend those methods to allow us to jointly optimise two processes in a manner that allows maximum profit to be made from a trading system.
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© 2002 Springer-Verlag London
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Towers, N. (2002). Joint Optimisation in Statistical Arbitrage Trading. In: Shadbolt, J., Taylor, J.G. (eds) Neural Networks and the Financial Markets. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0151-2_22
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DOI: https://doi.org/10.1007/978-1-4471-0151-2_22
Publisher Name: Springer, London
Print ISBN: 978-1-85233-531-1
Online ISBN: 978-1-4471-0151-2
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