0367037 20240103195823.820120124235959.9 000300753300025 84856055942 10.1016/j.eneco.2011.10.007 7 s. cav_un_epca*02504260140-9883341 (2012)241-247Elsevier Correlation Co-movement Wavelet analysis Wavelet coherence cav_un_auth*0101217 Vácha Lukáš Ekonometrie Department of Econometrics E E UTIA-B Department of Econometrics Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0242028 Baruník Jozef Ekonometrie Department of Econometrics E E UTIA-B Department of Econometrics Ústav teorie informace a automatizace AV ČR, v. v. i. GA402/09/0965 GA ČR cav_un_auth*0253176 GD402/09/H045 GA ČR cav_un_auth*0253998 GAP402/10/1610 GA ČR cav_un_auth*0263483 CEZ:AV0Z10750506 In this paper, we contribute to the literature on energy market co-movement by studying its dynamics in the time-frequency domain. The novelty of our approach lies in the application of wavelet tools to commodity market data. A major part of economic time series analysis is done in the time or frequency domain separate- ly. Wavelet analysis combines these two fundamental approaches allowing study of the time series in the time-frequency domain. Using this framework, we propose a new, model-free way of estimating time- varying correlations. In the empirical analysis, we connect our approach to the dynamic conditional correla- tion approach of Engle (2002) on the main components of the energy sector. Namely, we use crude oil, gas- oline, heating oil, and natural gas on a nearest-future basis over a period of approximately 16 and 1/2 years beginning on November 1, 1993 and ending on July 21, 2010. 2012 AH 2 4 A 4a 20231122134745.9 http://hdl.handle.net/11104/0201831 ECONOMICS 1.12 2.083 Q1 69.466 92.943 Q2 Q1 2012 Soubory v repozitáři: vacha-0367037.pdf 84856055942 SCOPUS 000300753300025 WOS cav_un_epca*0250426 Energy Economics 0140-9883 1873-6181 Roč. 34 č. 1 2012 241 247 Elsevier