@inproceedings{ad48bd5047e74672a810b09dea1aa077,
title = "Exchange rate modelling using news articles and economic data",
abstract = "This paper provides a framework of using news articles and economic data to model the exchange rate changes between Euro and US dollars. Many studies have conducted on the approach of regressing exchange rate movement using numerical data such as macroeconomic indicators. However, this approach is effective in studying the long term trend of the movement but not so accurate in short to middle term behaviour. Recent research suggests that the market daily movement is the result of the market reaction to the daily news. In this paper, it is proposed to use text mining methods to incorporate the daily economic news as well as economic and political events into the prediction model. While this type of news is not included in most of existing models due to its non-quantitative nature, it has important influence in short to middle terms of market behaviour. It is expected that this approach will lead to, an exchange rate model with improved accuracy.",
author = "Debbie Zhang and Simoff, {Simeon J.} and John Debenham",
year = "2005",
doi = "10.1007/11589990_49",
language = "English",
isbn = "3540304622",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "467--476",
booktitle = "AI 2005",
note = "18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence ; Conference date: 05-12-2005 Through 09-12-2005",
}