Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis

By Lukáš Vácha, Jozef Baruník. 2012

490 citations recorded by the source corpus.

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 separately. 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 correlation approach of Engle (2002) on the main components of the energy sector. Namely, we use crude oil, gasoline, heating oil, and natural gas on a nearest-future basis over a period of approximately 16 and 1/2years beginning on November 1, 1993 and ending on July 21, 2010. Using wavelet coherence, we uncover interesting dynamics of correlations between energy commodities in the time-frequency space.

Subfields: Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/a6fc8bf4ddfd5e9bc4f9904d92348bd951049f6d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Renewable Energy, Sustainability and the Environment

Citations in the corpus

Co-movements of GCC emerging stock markets: New evidence from wavelet coherence analysis (2014, methodology): “In this vein, major previous works were devoted to developed stock markets (Madaleno and Pinho, 2010; Rua and Nunes, 2009; Sharkasi et al., 2005; Vacha and Barunik, 2012; Garham and Kiviaho, 2012, 2011).”
Gold, Oil, and Stocks: Dynamic Correlations (2016, unknown): “…stocks (Fernandez, 2006, 2008; In & Kim, 2006; Rua &Nunes, 2009), commodities (Graham, Kiviaho, & Nikkinen, 2013; Reboredo & Rivera-Castro, 2014a; Vacha & Barunik, 2012), exchange rates (Karuppiah & Los, 2005; Nekhili, Altay-Salih, & Gençay, 2002; Nikkinen, Pynnönen, Ranta, & Vähämaa, 2011), and…”
Correlations between biofuels and related commodities before and during the food crisis: A taxonomy perspective (2012, methodology): “, 2011) to various cointegration estimations (Peri and Baldi, 2010) to volatility spillovers (Serra, 2011) and wavelet coherence analysis (Vacha and Barunik, 2012) and others.”
Time-Frequency Dynamics of Biofuels-Fuels-Food System (2012, methodology): “o localize where exactly this change occurs. When bivariate relation is studied, the same problem with time localization applies, see Gen˘cay et al. (2002); Percival and Walden (2000); Ramsay (2002); Vacha and Barunik (2012) for details. The utilized wavelet analysis overcomes these issues. Since th”
Testing the Conventional and Islamic Financial Market Contagion: Evidence from Wavelet Analysis (2016, background): “More recently, continuous wavelet transform (CWT) has appeared in the literature review and several authors provide some examples of useful economic applications (Aguiar-Conraria and Soares 2011; Madaleno and Pinho 2012; Vacha and Barunik 2012).”