0452317 20240103211418.220151216235959.9 000352328100019 84923807398 10.1016/j.physa.2015.02.057 12 s. P cav_un_epca*02574230378-43714281 (2015)194-205Elsevier Online searches Google Trends Long-term memory Cross-correlations Volatility Traded volume cav_un_auth*0256902 Krištoufek Ladislav Ekonometrie Department of Econometrics E E UTIA-B Department of Econometrics 100 Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2015/E/kristoufek-0452317.pdf GP14-11402P GA ČR CZ cav_un_auth*0303546 We study power-law correlations properties of the Google search queries for Dow Jones Industrial Average (DJIA) component stocks. Examining the daily data of the searched terms with a combination of the rescaled range and rescaled variance tests together with the detrended fluctuation analysis, we show that the searches are in fact power-law correlated with Hurst exponents between 0.8 and 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 detrended cross-correlation and detrending moving-average cross-correlation coefficients. Contrary to the universal power-law correlations structure of the related Google searches, the results suggest that there is no universal relationship between the online search queries and the analyzed financial measures. Even though we confirm positive correlation for a majority of pairs, there are several pairs with insignificant or even negative correlations. In addition, the correlations vary quite strongly across scales. 2016 AH 1 RVO:67985556 http://hdl.handle.net/11104/0253708 S PHYSICS.MULTIDISCIPLINARY 1.738 0.554 8.8 0.02088 0.42 18034 0.677 Q2 1.276 793 Q2 49.081 71.5 Q3 Q3 71.519 2015 84923807398 SCOPUS 000352328100019 WOS cav_un_epca*0257423 Physica. A : Statistical Mechanics and its Applications 0378-4371 1873-2119 Roč. 428 č. 1 2015 194 205 Elsevier