Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach

Benhmad, François

doi:10.1016/j.econmod.2012.01.003

Cited by 196 publications

(100 citation statements)

References 35 publications

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“…Their results reported that a positive shock to oil prices Granger cause US dollar exchange rate to decline in short run in all emerging economies. In case of Malaysia; Hussein et al [53] investigated the causality between oil price and US dollar exchange rate. They found cointegration between the variables and unidirectional causal relationship is found running from oil price to US dollar exchange rate.…”

Section: Literature Reviewmentioning

confidence: 99%

Analyzing time–frequency relationship between oil price and exchange rate in Pakistan through wavelets

Shahbaz

Tiwari

Tahir

2014

Journal of Applied Statistics

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Abstract:This study analyzes the time-frequency relationship between oil price and exchange rate for Pakistan by using measures of continuous wavelet such as wavelet power, cross-wavelet power, and cross-wavelet coherency. The results of cross-wavelet analysis indicate that covariance between oil price and exchange rate are unable to give clear-cut results but both variables have been in phase and out phase (i.e. they are anti-cyclical and cyclical in nature) in some or other durations. However, results of squared wavelet coherence disclose that both variables are out of phase and real exchange rate was leading during the entire period studied, corresponding to the 10~15 months scale. These results are the unique contribution of the present study, which would have not been drawn if one would have utilized any other time series or frequency domain based approach. This finding provides evidence of anti-cyclical relationship between oil price and real effective exchange rate. However; in most of the period studied, real exchange rate was leading and passing anti-cycle effects on oil price shocks which is the major contribution of the study.

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Section: Literature Reviewmentioning

confidence: 99%

Analyzing time–frequency relationship between oil price and exchange rate in Pakistan through wavelets

Shahbaz

Tiwari

Tahir

2014

Journal of Applied Statistics

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“…Orthogonal wavelets such as the Haar, Daublets, Symmlets and coiflets are the most widely used in empirical studies (Daubechies, 1993). The applications of wavelet analysis for specific purposes in economics and finance are relatively recent and were initiated by Ramsey and Lampart (1998), Gencay et al (2003), Kim and In (2007), Crowley and Lee (2005), and Crowley (2010) and Benhmad (2012), among others.…”

Section: Accepted Manuscriptmentioning

confidence: 98%

How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective

Jia

Fang

et al. 2015

Energy Economics

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“…More recently, Naccache [10], Aguiar-Conraria and Soares [28], Benhmad (2012) [25] and Reboredo and Rivera-Castro [11], among others, address the question of the link between oil prices and the macroeconomy using world data and a time scale decomposition based on the theory of wavelets. However, the first study of the relationship between spot and futures prices of crude oil using wavelet analysis was not performed until 2015 by Chang and Lee [12].…”

Section: The Wavelet Methodologymentioning

confidence: 99%

“…The MODWT is used to compute wavelet variances, wavelet correlations (WC) and cross-correlations (WCC) of bivariate time series [13,14]. Several applications of the DWT and MODWT can be found in economic and financial literature (see e.g., [8,13,23,24]) and to a lesser extent in energy studies [25][26][27]. Nevertheless, to date the WCC (via MODWT) has not been widely used to study the correlation and co-movements between spot and long-term futures oil prices (though some exceptions are discussed below).…”

Section: The Wavelet Methodologymentioning

confidence: 99%

Analyzing Crude Oil Spot Price Dynamics versus Long Term Future Prices: A Wavelet Analysis Approach

Polanco-Martínez

Abadie

2016

Energies

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Abstract:The West Texas Intermediate (WTI) spot price shows high volatility and in 2014 and 2015 when quoted prices declined sharply, long-term prices in future markets were less volatile. These prices are different and diverge depending on how they process fundamental and transitory factors. US tight oil production has been a major innovation with significant macroeconomic effects. In this paper we use WTI spot prices and long-term futures prices, the latter calculated as the expected value with a stochastic model calibrated with the futures quotes of each sample day. These long-term prices are the long-term equilibrium value under risk neutral measurement. In order to analyze potential time-scale relationships between spots and future, we perform a wavelet cross-correlation analysis using a novel wavelet graphical tool recently proposed. To check the direction of the causality, we apply non-linear causality tests to raw data and log returns as well as to the wavelet transform of the spot and futures prices. Our results show that in the spot and futures markets for the period 24 February 2006-2 April 2016 there is a bi-directional causality effect for most time scales (from intra-week to biannual). This suggests that spot and futures prices react simultaneously to new information.

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Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach

Cited by 196 publications

References 35 publications

Analyzing time–frequency relationship between oil price and exchange rate in Pakistan through wavelets

Analyzing time–frequency relationship between oil price and exchange rate in Pakistan through wavelets

How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective

Analyzing Crude Oil Spot Price Dynamics versus Long Term Future Prices: A Wavelet Analysis Approach

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