Competitive portfolio selection using stochastic predictions

Batu, Tugkan ORCID: 0000-0003-3914-4645 and Taptagaporn, Pongphat (2016) Competitive portfolio selection using stochastic predictions. In: Lecture Notes in Artificial Intelligence. Lecture Notes in Computer Science. Springer Berlin / Heidelberg, Cham, Switzerland, pp. 288-302. ISBN 9783319463797

Preview

Text - Accepted Version Download (402kB) | Preview

• Author

Abstract

We study a portfolio selection problem where a player attempts to maximise a utility function that represents the growth rate of wealth. We show that, given some stochastic predictions of the asset prices in the next time step, a sublinear expected regret is attainable against an optimal greedy algorithm, subject to tradeoff against the \accuracy" of such predictions that learn (or improve) over time. We also study the effects of introducing transaction costs into the model.

Item Type:	Book Section
Official URL:	http://www.springer.com/gb/
Additional Information:	© 2016 Springer
Divisions:	Mathematics
Subjects:	Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Date Deposited:	03 Aug 2016 12:56
Last Modified:	11 Dec 2024 17:50
URI:	http://eprints.lse.ac.uk/id/eprint/67338

Actions (login required)

View Item