Exploring the dynamics of the equity–commodity nexus: A study of base metal futures

Abstract

This empirical exercise explores different aspects of the time-varying linkage between the commodity and equity markets in India, focusing on base metal futures. The Dynamic Conditional Correlation model ( 2002) and Diebold-Yilmaz spillover index (2012) are employed to ascertain the presence, pattern, direction, and magnitude of the connectedness between the returns of base metal futures and related equity indices over the period of 2006-2019. The study builds on a less-studied "input" channel of linkage between the two, reckoning with the economic fundamentals of demand-supply interaction. Our results show that 36% of the return forecast error variance originates from spillovers, to which the contribution of equity indices is minimal. It indicates segmentation between the two markets which offer the scope for potential diversification. Further, base metal futures are the net transmitters and equity indices are the net recipients of spillovers. Positive correlations outweigh the negative correlations, in both frequency and magnitude.

The effectiveness of crude oil futures hedging during infectious disease outbreaks in the 21st century

“…We closely follow the methodology adopted in prior studies by Park and Switzer (1995), Park and Jei (2010), Chang et al (2011), and Saishree and Padhi (2022). Specifically, we use a vector autoregressive specification to define the conditional mean returns: $$${r}_{i,t}=C+{{\omega }_{i}{r}_{i,t-1}+\varepsilon }_{i,t},$$$ $$${\varepsilon }_{i,t}={H}_{i,t}^{1/2}{z}_{i,t},$$$where $${r}_{i,t}={({r}_{s,t},{r}_{F,t})}^{^{\prime} }$$ with $${r}_{s,t}$$ and $${r}_{F,t}$$ refer to the daily log returns on the spot ( S ) and futures ( F ) markets at time t , respectively, $${\varepsilon }_{i,t}={({\varepsilon }_{s,t},{\varepsilon }_{F,t})}^{^{\prime} }$$ is the vector of regression residuals, H t refers to a time‐varying 2 × 2 positive‐definite conditional covariance matrix, and $${z}_{i,t}={({z}_{s,t},{z}_{F,t})}^{^{\prime} }$$ is a vector of random errors assumed to be independently and identically distributed.…”

“…We closely follow the methodology adopted in prior studies by Park and Switzer (1995), Park and Jei (2010), Chang et al (2011), and Saishree and Padhi (2022). Specifically, we use a vector autoregressive specification to define the conditional mean returns:…”

“…We retrieve the daily closing spot and futures prices from the Bloomberg database for WTI, Brent, and Oman crude oil markets. As noted by Switzer and El-Khoury (2007) and Saishree and Padhi (2022), the closing futures prices of commodities such as crude oil sourced from Bloomberg are actually the prices of continuous contracts constructed by rolling over the front (near)-month futures contract, which is widely regarded as the most liquid and actively traded. 6 Because we are interested in evaluating the hedging effectiveness of the crude oil markets during notable disease outbreaks in the 21st century, our analysis focuses primarily on three subperiods: November 18, 2002-May 19, 2004(the SARS outbreak), April 16, 2009-August 11, 2010(the H1N1 pandemic), and March 10, 2020-December 31, 2020 (the COVID-19 pandemic).…”

Dynamic Risk Spillovers in Non-Ferrous Metal Future Markets During COVID-19: A Frequency Domain Analysis

“…Zhong, et al [14] used the model and rolling sample estimation method to investigate the tail risk spillover effect between China's stock market and macroeconomic system. Saishree and Padhi [15] explored the linkage between the commodity and equity markets in India based on DY spillover index. Shahzad, et al [16] used the method to analyze the impact of COVID-19 outbreak on US equity sectors.…”