Leading edge forecasting techniques for exchange rate prediction

Research output: Contribution to journalArticle

View graph of relations Save citation

Authors

Research units

Abstract

This paper describes how modern machine learning techniques can be used in conjunction with statistical methods to forecast short term movements in exchange rates, producing models suitable for use in trading. It compares the results achieved by two different techniques, and shows how they can be used in a complementary fashion. The paper draws on experience of both inter- and intra-day forecasting taken from earlier studies conducted by Logica and Chemical Bank Quantitative Research and Trading (QRT) group's experience in developing trading models.

Request a copy

Request a copy

Details

Original languageEnglish
Pages (from-to)311-323
Number of pages13
JournalEuropean Journal of Finance
Volume1
Issue4
DOIs
StatePublished - 4 Dec 1995

    Keywords

  • machine learning technique, leading-edge forecasting, rule induction, neural networks

DOI

Employable Graduates; Exploitable Research

Copy the text from this field...