Revealing the nexus between oil and exchange rate in the major emerging markets—The timescale analysis

Živkov, Dejan; Njegić, Jovan; Balaban, Suzana

doi:10.1002/ijfe.1686

Cited by 17 publications

(6 citation statements)

References 37 publications

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“…The findings indicate that the underlying relationship between oil prices and stock returns get stronger in a period of high volatility. More recently, Živkov, Njegić, and Balaban (2019) examine the transmission mechanism of oil price shocks towards exchange rates, using oil prices and exchange rate data from 10 emerging market economies of Asia, Africa, East Europe and South America. They find strong ‘coherence’ between Brent oil prices and exchange rates during the financial crisis period in both oil‐exporting countries and in many of the major oil‐importing countries.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysing spillover between returns and volatility series of oil across major stock markets

Tiwari¹,

Nasreen

Ullah

et al. 2020

Int. J Fin Econ

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Applying recently developed Diebold and Yilmaz (2012) spillover index, this paper investigates the oil–stocks returns and volatility connectedness with weekly data between January 14, 2000 and March 31, 2017. For the purpose of robustness, we have both used WTI and Brent oil prices. Sensitivity of overall spilover index is also examined using different lag‐structures and different forecast horizons. The empirical results are qualitatively similar either when WTI or Brent oil prices are used to examine the spillover amongst series under consideration. Specifically, the spillover index value for WTI and Brent, respectively, is 71.60 and 72.32%. We show that total spillover connectedness, as measured by a rolling‐window approach, has dynamic and volatile characteristics in returns and volatility series across major markets. Last but not least, we find from the net spillover analysis that NYK, SPTSX, IBOV, MICEX, SENSEX, Shanghai, TOP40 and WTI stock markets are net receiver of return spillover, whereas SPX, DAX, UKX, FTSEMIB and CAC40 are the net contributors.

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Section: Literature Reviewmentioning

confidence: 99%

Analysing spillover between returns and volatility series of oil across major stock markets

Tiwari¹,

Nasreen

Ullah

et al. 2020

Int. J Fin Econ

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“…Following the existing studies (e.g., Yang et al, 2016; Gallegati, 2012; Živkov et al, 2019a, 2019b), we use discrete wavelet transform to analyse interdependence and financial contagion among exchange rates. For wavelet transformation, non-decimated orthogonal Maximum Overlap Discrete Wavelet Transform (MODWT) decomposing the data to 8 levels is used.…”

Section: Methodsmentioning

confidence: 99%

Exchange Rate Interdependence in ASEAN Markets: A Wavelet Analysis

Qureshi

Aftab

2020

Global Business Review

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Severe swings among the financial markets’ linkages in the recent past motivate the research to examine the exchange rate co-movements. Therefore, this study examines the interdependence and contagion among the exchange rates of five important Asian emerging markets, namely Indonesia, Malaysia, Philippines, Singapore and Thailand exploring the multifarious nature of interdependence and lead lag association using discrete and continuous wavelet decomposition. The findings show the co-movement among many exchange rate pairs showing a substantial increase during the global financial crisis. There are moderate rises in co-movements, indicating regional market convergence in the long run. Singapore seems to hold driving position and Indonesia falls behind in all exchange rate pairs of the ASEAN-5. The findings provide policy implications for caring the interdependence in foreign exchange markets.

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“…They concluded that lower‐upper and upper‐lower tail dependence of the US dollar and oil are significantly negative. Živkov, Njegić, and Balaban (2019) used wavelet coherence and phase difference methodologies to study the correlation between oil and exchange rate in 10 major countries.…”

Section: Literature Reviewmentioning

confidence: 99%

Time‐dependent intrinsic correlation analysis of crude oil and the US dollar based on CEEMDAN

2020

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In this article, we analyze the dynamic linkage between crude oil price and the US dollar at multi‐scale frequencies using time‐dependent intrinsic correlation analysis based on the complete ensemble empirical mode decomposition with adaptive noise. After applying a refined method to extract the trend, we reveal that the overall correlation and the long‐term trend correlation exhibit very similar patterns. The correlation coefficients between crude oil and the US dollar are negative at most of the time; however, the coefficients become positive in certain periods, such as 2013–2014 and 2017–2018. Furthermore, the negative correlations in high frequency intrinsic mode functions (IMFs), with a shorter time horizon, are weaker and display time‐varying characteristics, whereas the correlation in low frequency IMFs, with a longer time horizon, are stronger and more static. The findings of this article may have important implications for investors to construct optimal portfolio diversification.

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Revealing the nexus between oil and exchange rate in the major emerging markets—The timescale analysis

Cited by 17 publications

References 37 publications

Analysing spillover between returns and volatility series of oil across major stock markets

Analysing spillover between returns and volatility series of oil across major stock markets

Exchange Rate Interdependence in ASEAN Markets: A Wavelet Analysis

Time‐dependent intrinsic correlation analysis of crude oil and the US dollar based on CEEMDAN

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