White Rose University Consortium logo
University of Leeds logo University of Sheffield logo York University logo

Distribution Forecasting of High Frequency Time Series

Pasley, A. and Austin, J. (2004) Distribution Forecasting of High Frequency Time Series. Decision Support Systems, 37 (4). pp. 501-513. ISSN 0167-9236

Full text not available from this repository.


The availability of high frequency data sets in finance has allowed the use of very data intensive techniques using large data sets in forecasting. An algorithm requiring fast k-NN type search has been implemented using AURA, a binary neural network based upon Correlation Matrix Memories. This work has also constructed probability distribution forecasts, the volume of data allowing this to be done in a nonparametric manner. In assistance to standard statistical error measures the implementation of simulations has allowed actual measures of profit to be calculated.

Item Type: Article
Copyright, Publisher and Additional Information: Copyright © 2004 Elsevier.
Keywords: financial forecasting, neural networks, associative memories, probability distribution forecasting, high frequency time series
Institution: The University of York
Academic Units: The University of York > Computer Science (York)
Depositing User: Sherpa Assistant
Date Deposited: 01 Sep 2006
Last Modified: 05 Aug 2007 18:17
Published Version: http://dx.doi.org/10.1016/S0167-9236(03)00083-6
Status: Published
Publisher: Elsevier
Refereed: Yes
Identification Number: 10.1016/S0167-9236(03)00083-6
URI: http://eprints.whiterose.ac.uk/id/eprint/1527

Actions (repository staff only: login required)