Evidence on Price Formation In Financial Markets: A Multitemporal Analysis

Abstract

Background: Although clean energy stocks have become a popular new asset class for market players, relatively little research has been done on risk management strategies for investors in clean energy stock markets. Gold and Silver are examples of precious metals typically considered suitable investments to hedge against uncertainty. Therefore, their demand tends to rise when stock markets decline. Purpose: The study aims to analyse the influence of precious metals (Gold, Silver and Platinum) and green stock indices (Clean Energy Fuels, Nasdaq Clean Edge Green Energy, S&P Global Clean Energy, WilderHill Clean Energy) on price formation during different economic periods between 1 January 2018 and 23 November 2023. Methods: The periods analysed were Tranquil, 2020 pandemic, pre-conflict and Conflict (Russian invasion of Ukraine). To this end, a VAR Granger Causality/Block Exogeneity Wald model was estimated to identify different influence patterns during each period. Results: During the Tranquil period, 15 movements affecting prices were observed, with Silver significantly influencing all its peers, while Gold impacted Platinum, S&P Global, Nasdaq and WilderHill. Platinum was the asset that received the most shocks from its peers. During the 2020 pandemic, there was an increase to 26 movements, with the S&P Global and Nasdaq Clean indices influencing most of their peers. Gold and Platinum continued to be the assets most influenced by their peers. In the pre-conflict period, 11 movements were identified, with the highlight being the mutual influence between Gold, the Nasdaq and WilderHill indices, and Platinum. During this period, Silver and S&P Global only affected the price formation of Platinum and Clean Energy Fuels, respectively. During the Conflict period, 18 movements were observed, highlighting the influence of Platinum and S&P Global on the price formation of various assets. Gold was the asset that received the most shocks from its peers during this period. Conclusion: the results indicate changes in the interactions between assets throughout the different economic contexts, highlighting the importance of understanding these dynamics to make more informed decisions.