Skip navigation

Financial Time Series Forecasting using Agent Based Models in Equity and FX Markets

Financial Time Series Forecasting using Agent Based Models in Equity and FX Markets

Chinthalapati, V L Raju (2014) Financial Time Series Forecasting using Agent Based Models in Equity and FX Markets. In: Proceedings of the 6th Computer Science and Electronic Engineering Conference (CEEC), 2014. IEEE Xplore. ISBN 978-­1-­4799-­6691-­2 (doi:https://doi.org/10.1109/CEEC.2014.6958562)

[img]
Preview
PDF (Author Accepted Manuscript)
13355_CHINTHALAPATI_Financial_times_series_(2014).pdf - Accepted Version
Available under License Creative Commons Attribution.

Download (293kB)

Abstract

We investigate the application of machine learning Agent Based Modelling (ABM) techniques to model and forecast various financial markets including Foreign Exchange and Equities, especially models that could reproduce the time-series properties of the financial variables. We model the economy by considering non-equilibrium economics. We adopt the features that are required for modelling non-equilibrium economics using ABMs and replicate the non-equilibrium nature of the financial markets by considering a set of bounded rational heterogeneous agents, with different strategies that are ranked according to their performance in the market. We consider markets where there are different agents interacting among themselves and forming some sort of patterns. For example, the patterns are equity prices or exchange rates. While the agents have been interacting in the artificial market, the generated patterns (price dynamics) they co-produce would match with the real financial time-series. In order to get the best fit to the real market, we need to search for the best set of artificial heterogeneous agents that represents the underlying market. Evolutionary computing techniques are used in order to search for a suitable set of agent configuration in the market. We verify the forecasting performance of the artificial markets by comparing that with the real financial market by conducting out-of-sample tests.

Item Type: Conference Proceedings
Title of Proceedings: Proceedings of the 6th Computer Science and Electronic Engineering Conference (CEEC), 2014
Additional Information: © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Conference dates: 25-26 Sept. 2014 (Colchester)
Uncontrolled Keywords: Agent Based Models, FX markets, Evolutionary computing, Non-equilibrium Economics
Faculty / Department / Research Group: Faculty of Business > Department of Accounting & Finance
Last Modified: 14 Oct 2016 09:32
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/13355

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics