Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components

摘要

We study power-law correlations properties of the Google search queries forDow Jones Industrial Average (DJIA) component stocks. Examining the daily dataof the searched terms with a combination of the rescaled range and rescaledvariance tests together with the detrended fluctuation analysis, we show thatthe searches are in fact power-law correlated with Hurst exponents between 0.8and 1.1. The general interest in the DJIA stocks is thus strongly persistent.We further reinvestigate the cross-correlation structure between the searches,traded volume and volatility of the component stocks using the detrendedcross-correlation and detrending moving-average cross-correlation coefficients.Contrary to the universal power-law correlations structure of the relatedGoogle searches, the results suggest that there is no universal relationshipbetween the online search queries and the analyzed financial measures. Eventhough we confirm positive correlation for a majority of pairs, there areseveral pairs with insignificant or even negative correlations. In addition,the correlations vary quite strongly across scales.