Abstract
The COVID-19 pandemic has shocked commodities markets in general and base metals markets in particular. The market turmoil made it very difficult to act in the physical market, given the impossibility of establishing or maintaining physical and/or financial positions in a context of high uncertainty. This has happened both in different moments of the development of the pandemic and in geographically different frames. That is why this contribution tries to explain the evolution of warehouses and copper price structure and its utility for hedging in the context of an extreme event. To that end, Granger causality has been used to test whether, during the COVID-19 first wave, the pandemic evolution is cointegrated on one hand with copper futures price structure and, on the other, with the incremental levels of copper stocks. Using 102 official copper prices on London Metal Exchange (LME) trading days, between 13 January 2020 and 5 June 2020 (once the most severe effects of the first wave had been overcome), it was demonstrated that, during the first COVID-19 wave in Europe, the weekly death index variation was cointegrated with the copper future price structure. It has been proven that, in this timelapse, contango in futures price structure has increased its value, and the incremental levels of stock in copper LME warehouses are linked with a stable contango structure. In short, we find that fundamental market effects predominate, in a context in which commodities used to be more financialized. This leads market players, such as traders, miners, and transformers, to move exposures in their hedging structures, under such extreme event situations, in favor of or against either contango or backwardation, so as to derive value from them.
Highlights
The COVID-19 pandemic started as an epidemic, with China being the first country reporting the disease
Relationship between London Metal Exchange (LME) Copper Warehouses’ Level and the Structure of Copper Futures Prices. Both series STOCKt and strut have been shown to be non-stationary, even after Box– Cox [83] transformations, and we found non-stationarity at the following levels of both series. We confirmed this via augmented Dickey–Fuller (ADF), PP, and KPSS tests to check the non-stationary of the two series, STOCKt and strut, as can be seen in Table 3, finding that both series are non-stationary to the same degree
The COVID-19 pandemic has thrown the world economy into turmoil, and commodity markets have lived through a tsunami since its beginning; its implications have led to a situation of strong normal backwardation
Summary
The COVID-19 pandemic started as an epidemic, with China being the first country reporting the disease. It was only 100 days until the declaration of the pandemic. The recovery after the emergence of the pandemic evolved differently depending on the country and the sanitary situation, causing a global disruption in the commerce interchange and affecting the full value-added chain. Other commodities traded in futures exchanges, such as soft commodities and metals, reacted sharply to this global crisis, with a vast shift in prices [2], and the historical refuges of these stock markets being affected [3]. In particular, underwent a price decrease of almost 25%, from EUR 6200 at the beginning of 2020 to EUR 4627 per metric ton only 3 months after, with a lack of interest in 6200 at the beginning of 2020 to EUR 4627 per metric ton only 3 months after, with a of interest in the buying market and with most of the players trying to liquidate their l held positions in official warehouses
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