Dynamic co-movement between oil and stock markets in oil-importing and oil-exporting countries: Two types of wavelet analysis

Jiang, Zhuhua; Yoon, Seong‐Min

doi:10.1016/j.eneco.2020.104835

Cited by 114 publications

(54 citation statements)

References 79 publications

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“…First, an essential characteristic of the wavelet method is to capture latent processes with time varying cycle trends, lead-lag interactions, and patterns in the underlying time series ( Fakhfekh et al, 2021 ; Sherif, 2020 ). Second, a major advantage of wavelet coherence approach relates with its flexibility in dealing with non-stationary signals which are prevalent in the prices of soft commodities ( Aguiar-Conraria and Soares, 2011 ; Demir et al, 2020 ; Jiang and Yoon, 2020 ; León and Soto, 1997 ; Oglend and Asche, 2016 ; Shehzad et al, 2021 ). In addition, the wavelet coherence framework is also useful to study the co-movements between time series variables with frequent structural changes ( Fruehwirt et al, 2021 ; Kristoufek et al, 2016 ), and the variables that face sudden fluctuations in their structure.…”

Section: Data and Research Methodologymentioning

confidence: 99%

Safe-haven properties of soft commodities during times of Covid-19

Rubbaniy

Khalid

Syriopoulos

et al. 2022

Journal of Commodity Markets

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We use wavelet coherence analysis on global COVID-19 fear index and, soft commodities’ spot and futures prices to investigate safe-haven properties of soft commodities over the period from January 28, 2020 to April 29, 2021. Our findings show that each of the sampled soft commodities shows safe-haven behavior in one of the spot or futures markets and for one of the short-term or long-term investors during the times of COVID-19. Our results also show that safe-haven properties of soft commodities are contingent upon the nature of the commodity. The findings of our mean-variance portfolio analysis indicate that the portfolios with commodity futures are less risky and efficient compared to the portfolio containing stocks only, thus robustly supporting the safe-haven properties of soft commodities during COVID-19. Our results not only have important implications for individual investors and asset managers in suggesting particular soft commodities to strengthen safe-haven and diversification features of their portfolios but also can assist the policy makers to understand and disentangle health fear dimension of several interlocking dynamics affecting the spot and futures prices of soft commodities during COVID-19.

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Section: Data and Research Methodologymentioning

confidence: 99%

Safe-haven properties of soft commodities during times of Covid-19

Rubbaniy

Khalid

Syriopoulos

et al. 2022

Journal of Commodity Markets

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“…Wavelet analysis is one of the most commonly used frequency analysis in non-stationary time series data analysis. The advantage of the wavelet analysis relates to its flexibility in the use of various non-stationary signals ( Aguiar-Conraria and Joana Soares, 2011 ; Bilgili, 2015 ; Bravo et al, 2020 ; Jiang and Yoon, 2020 ; Kuşkaya and Bilgili, 2020 ; Tiwari et al, 2020 ; Bilgili et al, 2020a , 2020b ). As wavelets are structured over finite intervals of time and are not perforce homogeneous over time, they are localised in time scale ( Ramsey, 2014 ).…”

Section: Methodology and Datamentioning

confidence: 99%

Is gold favourable than bitcoin during the COVID-19 outbreak? Comparative analysis through wavelet approach

et al. 2021

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The novel coronavirus (COVID-19) has tremendously oscillated the global financial markets. Consequently, investors feel pressured to find safe-haven investments during the pandemic crisis. Numerous studies have evaluated bitcoin's safe-haven properties during the COVID-19; however, the present study considered gold as a potential safe-haven for investors of renowned stock markets of Asia, Europe, and the US. The present investigation computed the ratio of gold to bitcoin (Gold_Bitcoin) and compared the safe-haven properties of gold in contrast to bitcoin. The present study analysed the Morlet Wavelet approach and found that most of the time during the COVID-19, gold investments proved to be more beneficial than bitcoin. Remarkably, the findings highlighted that the Gold_Bitcoin ratio increased in higher and lower frequencies combined with CAC40. In the long run, the return on investments in gold increased in contrast to bitcoin returns pooled with DAX30. Also, the Gold_Bitcoin ratio of the US stock market increased during the one-week and one-month cycles of January and August. Likewise, the Hang Seng Index caused the Gold_Bitcoin ratio to rise at a much higher frequency (i.e., the second half of January, the first half of February and April, and the first half of June and August), whereas IBEX35 surged Gold_Bitcoin at a lower frequency (i.e., during January, February, and August). In higher frequency bands, LSE increased the Gold_Bitcoin ratio (i.e., in February and March); nevertheless, Gold_Bitcoin showed a positive connection with FTSEMIB in the one-to-two month's frequency band (i.e., throughout January, February, and August). Interestingly, the returns on the Gold_Bitcoin ratio increased in the SSEC stock market in the high-frequency band (i.e., during March, May, and July 2020).

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“…On the wavelet coherence plots, the black contour shows the 5% significance level, and regions with strong co-movements are represented by warmer colors (red), whereas colder colors (blue) represent regions with weak co-movements. The arrows provide the direction of interdependence and causality relationships ( Torrence and Webster, 1999 ; Tiwari, 2013 ; Yang et al., 2017 ; Pal and Mitra, 2019 ; Jiang and Yoon, 2020 ). Arrows pointing to the right( → ) indicate that EPU and the sector volatility are positively correlated.…”

Section: Empirical Analysismentioning

confidence: 99%

Industry volatility and economic uncertainty due to the COVID-19 pandemic: Evidence from wavelet coherence analysis

Choi

2020

Finance Research Letters

124

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Highlights We investigate the impact of economic uncertainty due to the coronavirus (COVID-19) pandemic on the industrial economy in the US. We apply wavelet coherence analysis to economic policy uncertainty (EPU) data and monthly sector volatility of the S&P 500 index. Our analysis indicates that COVID-19 has had a substantial impact on all sectors of the US stock market. The influence of the pandemic on the industrial economy is larger than that of the global financial crisis (GFC) for all sectors.

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Dynamic co-movement between oil and stock markets in oil-importing and oil-exporting countries: Two types of wavelet analysis

Cited by 114 publications

References 79 publications

Safe-haven properties of soft commodities during times of Covid-19

Safe-haven properties of soft commodities during times of Covid-19

Is gold favourable than bitcoin during the COVID-19 outbreak? Comparative analysis through wavelet approach

Industry volatility and economic uncertainty due to the COVID-19 pandemic: Evidence from wavelet coherence analysis

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