Abstract
Commodity price volatility within the stainless-steel supply chain impacts the profitability of the companies involved. The stainless-steel sector faces an increasingly unstable business environment and a rising complexity while the stainless-steel supply chain is characterised by price fluctuations both at upstream (e.g., miners) and downstream levels (e.g., stainless steel producers). The competitiveness of the industry is influenced by the high level of fixed costs and commodity price fluctuations while the raw material accounts for up to 70% of the final product price. Hence, companies within the stainless-steel sector need to assess constantly their financial performance and prosperity. These can be measured by share prices, which are also characterised by volatility.
This research studies the relationships (co-volatility) between each commodity (Nickel and Iron Ore) stock prices and the share prices of key companies in the stainless-steel supply chains. Twenty-eight multivariate GARCH (MGARCH) models have been studied, which represent the same number of different two-node supply chain structures comprising an upstream (miner) and a downstream node (stainless-steel producer. Four miners and seven manufacturing companies are included in our study. MGARCH approach helps to understand the dynamics of the supply chains by investigating the direction of volatility and if the shocks in the stainless-steel market will affect commodity price volatility or vice versa. All twenty-eight MGARCH models are estimated based on time series data spanning from January 2011 to May 2022. Post-model diagnostics indicate the satisfying fitting performance of the twenty-eight estimated models. Finally, this research aims to help companies to appraise the disruption phenomena within supply chains, explore new opportunities, understand the risks associated with political and financial instability and (re)evaluate the new rules of competition.
This research studies the relationships (co-volatility) between each commodity (Nickel and Iron Ore) stock prices and the share prices of key companies in the stainless-steel supply chains. Twenty-eight multivariate GARCH (MGARCH) models have been studied, which represent the same number of different two-node supply chain structures comprising an upstream (miner) and a downstream node (stainless-steel producer. Four miners and seven manufacturing companies are included in our study. MGARCH approach helps to understand the dynamics of the supply chains by investigating the direction of volatility and if the shocks in the stainless-steel market will affect commodity price volatility or vice versa. All twenty-eight MGARCH models are estimated based on time series data spanning from January 2011 to May 2022. Post-model diagnostics indicate the satisfying fitting performance of the twenty-eight estimated models. Finally, this research aims to help companies to appraise the disruption phenomena within supply chains, explore new opportunities, understand the risks associated with political and financial instability and (re)evaluate the new rules of competition.
Original language | English |
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Publication status | Published - Sept 2022 |
Event | Logistics Research Network Conference: Supply Chain Innovation: People, Process, Technology - Aston University, Birmingham , United Kingdom Duration: 7 Sept 2022 → 9 Sept 2022 https://ciltuk.org.uk/Events/CILT-National-Events/LRN-2022 |
Conference
Conference | Logistics Research Network Conference |
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Abbreviated title | LRN 2022 |
Country/Territory | United Kingdom |
City | Birmingham |
Period | 7/09/22 → 9/09/22 |
Internet address |