Perpustakaan Digital ITB

Exchange rate markets are quite sensitive to unexpected news and events. Over the last few years, investor’s sentiments toward exchange rate have been used to provide early indicators and predict future movements. This research use data mining of investor’s sentiments through social media, news articles, websites, blogs, forums, and group discussion to model and forecast exchange rate. Daily data on the nominal exchange rate of major global currencies— USD, EUR, and JPY against the IDR (Indonesian Rupiah) are collected from the entire year of 2015. The methodologies used in this paper are big data analysis using LWIC (Linguistic Inquiry and Word Count) and event analysis.The expected outcome of this research is that the market sentiment can significantly predict the future price of the currency and find out which channel that can strongly predict the future prices. The exchange rate model or trend can also be useful information for institutional investors, individual traders, corporations, or even governments