Foundations of statistical natural language processing
Foundations of statistical natural language processing
Currency exchange rate forecasting from news headlines
ADC '02 Proceedings of the 13th Australasian database conference - Volume 5
Survey of Text Mining
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
An e-market framework for informed trading
Proceedings of the 15th international conference on World Wide Web
Building an electronic market system
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Making informed automated trading a reality
EC-Web'06 Proceedings of the 7th international conference on E-Commerce and Web Technologies
Agents for information-rich environments
CIA'06 Proceedings of the 10th international conference on Cooperative Information Agents
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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.