High frequency exchange rate prediction with an artificial neural network
High frequency exchange rate prediction with an artificial neural network
This paper examines how market microstructure variables can be used to forecast foreign exchange rates at frequencies of one to several minutes. We use a unique foreign exchange (FX) dataset of global inter-dealer electronic transactions and applied the Artificial Neural Network (ANN) as the predicting model. The immediately preceding bid and ask prices are significant factors in these predictions, which is in keeping with market microstructure theory. These microstructure factors have not been tested in ANN model before. High frequency trading strategies based on ANN model are shown to be profitable even when transaction costs are included.
170-178
Choudhry, Taufiq
6fc3ceb8-8103-4017-b3b5-2d38efa57728
McGroarty, Frank
693a5396-8e01-4d68-8973-d74184c03072
Peng, Ke
4ba591b1-6929-468c-a9a7-c948297e3aa0
Wang, Shiyun
819027ab-c7c6-45a8-b3ba-d4331bbc4189
1 July 2012
Choudhry, Taufiq
6fc3ceb8-8103-4017-b3b5-2d38efa57728
McGroarty, Frank
693a5396-8e01-4d68-8973-d74184c03072
Peng, Ke
4ba591b1-6929-468c-a9a7-c948297e3aa0
Wang, Shiyun
819027ab-c7c6-45a8-b3ba-d4331bbc4189
Choudhry, Taufiq, McGroarty, Frank, Peng, Ke and Wang, Shiyun
(2012)
High frequency exchange rate prediction with an artificial neural network.
Intelligent Systems in Accounting, Finance and Management, 19 (3), .
Abstract
This paper examines how market microstructure variables can be used to forecast foreign exchange rates at frequencies of one to several minutes. We use a unique foreign exchange (FX) dataset of global inter-dealer electronic transactions and applied the Artificial Neural Network (ANN) as the predicting model. The immediately preceding bid and ask prices are significant factors in these predictions, which is in keeping with market microstructure theory. These microstructure factors have not been tested in ANN model before. High frequency trading strategies based on ANN model are shown to be profitable even when transaction costs are included.
This record has no associated files available for download.
More information
Published date: 1 July 2012
Organisations:
Centre for Digital, Interactive & Data Driven Marketing
Identifiers
Local EPrints ID: 340754
URI: http://eprints.soton.ac.uk/id/eprint/340754
ISSN: 1055-615X
PURE UUID: 46fe43cf-9f59-4007-9ab3-99474d27314b
Catalogue record
Date deposited: 02 Jul 2012 13:28
Last modified: 11 Dec 2021 03:53
Export record
Contributors
Author:
Frank McGroarty
Author:
Ke Peng
Author:
Shiyun Wang
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics