2021
DOI: 10.3390/en14134024
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The Connections between COVID-19 and the Energy Commodities Prices: Evidence through the Dynamic Time Warping Method

Abstract: The main objective of the study is to assess the similarity between the time series of energy commodity prices and the time series of daily COVID-19 cases. The COVID-19 pandemic affects all aspects of the global economy. Although this impact is multifaceted, we assess the connections between the number of COVID-19 cases and the energy commodities sector. We analyse these connections by using the Dynamic Time Warping (DTW) method. On this basis, we calculate the similarity measure—the DTW distance between the t… Show more

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Cited by 33 publications
(26 citation statements)
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“…By spring 2021, commodity prices were above the prepandemic levels. Dmytrów et al [87] compared the time series of energy commodity prices with the time series of daily COVID-19 cases from 5 January 2020 to 12 March 2021. They find that the commodities such as ULSD, fuel oil, crude oil, and gasoline are weakly associated with the COVID-19 cases.…”
Section: Discussionmentioning
confidence: 99%
“…By spring 2021, commodity prices were above the prepandemic levels. Dmytrów et al [87] compared the time series of energy commodity prices with the time series of daily COVID-19 cases from 5 January 2020 to 12 March 2021. They find that the commodities such as ULSD, fuel oil, crude oil, and gasoline are weakly associated with the COVID-19 cases.…”
Section: Discussionmentioning
confidence: 99%
“…DTW was originally applied for the context speech recognition (Giorgino, 2009). Since then, it was used in many other disciplines such, as finance (Stübinger, 2019), comparison of the COVID-19 dynamics (Landmesser, 2021a;2021b), dynamics of share prices of energy commodities (Dmytrów et al, 2021), or labour market (Dmytrów & Bieszk-Stolorz, 2019) It is used for estimation of the optimal alignment of timeseries by means of the dynamic programming methods. The alignment between the two-time series is measured by the cost matrix obtained by means of the taxicab geometry (Manhattan distance metric).…”
Section: Methodsmentioning
confidence: 99%
“…The first wave of the pandemic proved to be a great surprise and problem for the entire economy. However, the introduced protective tools for companies and the acquired experience meant that the impact of the second wave on the economy was not as severe (Dmytrów et al, 2021). It seems that during the second wave of the pandemic, those sectors of companies that were most severely affected by the first wave suffered more.…”
Section: Methodsmentioning
confidence: 99%