The quantitative evaluations of relationships between word appearances on blogs and stock prices

Abstract

To clarify connections between social media data and ?nancial market data, we studied the quantitative evaluations of relations between time series of word appearances on Japanese blogs and those of stock prices. In particular, we proposed the method of comparison of some correlation indices such as the Spearman's rank correlation coe?cient, based on the man-made related stock information. We found that the Spearman's rank correlation coe?cients over time series of 562 keywords can hardly pick the correct combinations of related stocks out the pool of more than 3,000 stocks on the Tokyo Stock Exchange. However, we show that the composite correlation indicators, which re?ect multiple features of the time series, can pick the correct stocks up to a certain level of statically signi?cant.