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This study focuses on how China EPU may impact copper-firms stock returns and also how China EPU mediates between stock returns and copper prices returns.

The sample consists of 44 copper firms from January 2011 to March 2022. The study also considers a subsample of 29 net-exporters countries. Panel data methodology is used, allowing to control for unobservable heterogeneity and endogeneity problems. The equations are estimated through a dynamic panel using the generalized methods of moments (GMM).

China EPU has a negative and statistically significant relationship with stock returns. Copper price returns are positively associated with stock returns. This research also considers two scenarios: high and low levels of China EPU. For high levels of China EPU states it is reported a negative relationship between stock returns and China EPU and copper price returns show a positive relationship with stock returns.

There is need to explore other metals for what China exhibits a high demand and observe if China EPU and Global EPU have similar impacts on stock returns. It will be useful to identify main firm's consumers of copper and these other metals to explore the relationship between EPU and stock returns.

To the best of the authors’ knowledge, this is the first paper that analyzes China EPU index and its impact on both copper-firms stocks returns and on changes in copper prices. This is done using all public copper firms worldwide.

Este estudio se enfoca en como la incertidumbre en política económica de China (llamado China EPU) puede impactar en los retornos de las acciones de empresas del sector del cobre y como China EPU media entre los retornos de las acciones y los retornos de los precios del cobre.

La muestral consiste en 44 firmas de cobre desde enero 2011 a marzo 2022. El estudio también considera una sub muestra de 29 países que son exportadores netos de cobre. Se utiliza la metodología de datos de panel, permitiendo controlar por lo inobservable y por problemas de endogeneidad. Las ecuaciones son estimadas a través de panel dinámico usando el método generalizado de los momentos (G.M.M.).

EPU de China tiene una relación negativa y estadísticamente significativa con los retornos accionarios. Los retornos de los precios del cobre están positivamente asociados con los retornos accionarios. La investigación también considera dos posibles escenarios: altos y bajos niveles de EPU. Para el estado de altos niveles se reporta una relación negativa entre los retornos accionarios y el EPU de China, además los retornos de los precios del cobre muestran una relación positiva con los retornos accionarios.

Se requiere explorar otros metales para los cuales China sea un importante demandante a nivel internacional y observar si el EPU de China y el EPU Global tienen similares impactos en los retornos accionarios. A su vez sería útil identificar las principales firmas consumidoras de cobres y estos otros metales de tal forma de chequear la relación entre EPU y retornos accionarios.

En nuestro mejor conocimiento, este es el primer artículo que analiza el índice EPU de China y como este impacta tanto los retornos accionarios de las empresas de cobre como los cambios de precios del cobre. Esto es hecho usando una muestral que incluye todas las empresas de cobre que se transan en bolsa a nivel internacional.

This article unveils first the lead–lag structure between the confirmed cases of COVID-19 and financial markets, including the stock (DJI), cryptocurrency (Bitcoin) and commodities (crude oil, gold, copper and brent oil) compared to the financial stress index. Second, this paper assesses the role of Bitcoin as a hedge or diversifier by determining the efficient frontier with and without including Bitcoin before and during the COVID-19 pandemic.

The authors examine the lead–lag relationship between COVID-19 and financial market returns compared to the financial stress index and between all markets returns using the thermal optimal path model. Moreover, the authors estimate the efficient frontier of the portfolio with and without Bitcoin using the Bayesian approach.

Employing thermal optimal path model, the authors find that COVID-19 confirmed cases are leading returns prices of DJI, Bitcoin and crude oil, gold, copper and brent oil. Moreover, the authors find a strong lead–lag relationship between all financial market returns. By relying on the Bayesian approach, findings show when Bitcoin was included in the portfolio optimization before or during COVID-19 period; the Bayesian efficient frontier shifts to the left giving the investor a better risk return trade-off. Consequently, Bitcoin serves as a safe haven asset for the two sub-periods: pre-COVID-19 period and COVID-19 period.

Based on the above research conclusions, investors can use the number of COVID-19 confirmed cases to predict financial market dynamics. Similarly, the work is helpful for decision-makers who search for portfolio diversification opportunities, especially during health crisis. In addition, the results support the fact that Bitcoin is a safe haven asset that should be combined with commodities and stocks for better performance in portfolio optimization and hedging before and during COVID-19 periods.

This research thus adds value to the existing literature along four directions. First, the novelty of this study lies in the analysis of several financial markets (stock, cryptocurrencies and commodities)’ response to different pandemics and epidemics events, financial crises and natural disasters (Correia et al., 2020; Ma et al., 2020). Second, to the best of the authors' knowledge, this is the first study that examine the lead–lag relationship between COVID-19 and financial markets compared to financial stress index by employing the Thermal Optimal Path method. Third, it is a first endeavor to analyze the lead–lag interplay between the financial markets within a thermal optimal path method that can provide useful insights for the spillover effect studies in all countries and regions around the world. To check the robustness of our findings, the authors have employed financial stress index compared to COVID-19 confirmed cases. Fourth, this study tests whether Bitcoin is a hedge or diversifier given this current pandemic situation using the Bayesian approach.

This paper aims to model the relationship between oil price and stock returns for selected sectors in Nigeria using monthly data from January 2007 to December 2016.

The authors use both the linear (symmetric) autoregressive distributed lag (ARDL) by Pesaran et al. (2001) and non-linear (asymmetric) ARDL by Shin et al. (2014), and they also account for structural breaks using the Bai and Perron (2003) test that allows for multiple structural changes in regression models.

The results indicate that the strength of this relationship varies across sectors, albeit asymmetric and breaks. The authors identify two structural breaks that occur in 2008 and 2010/2011, which coincidentally correspond to the global financial crisis and the Arab spring (Libyan shutdowns), respectively. Moreover, the authors observe strong support for asymmetry and structural breaks for some sectors in the reaction of sector returns to movement in oil prices. These findings are robust and insensitive when considering different oil proxies. While further extensions can be pursued, the consideration of asymmetric effects as well as structural breaks should not be jettisoned when modelling this nexus.

This study is one of the very few studies that have investigated the sectoral behaviour of stocks to oil price shocks, particularly in Nigeria. This paper contributes to the oil stock literature using the recent technique of asymmetry and also considering the role structural breaks play in the relationship between oil price and stock returns.