Time-frequency connectedness and cross-quantile dependence between carbon emission trading and commodity markets: Evidence from China

This paper aims to investigate the dynamic connectedness and the cross-quantile dependence structure between carbon emission trading and commodity markets in China. We employ both the Baruník and Křehlík (2018) connectedness method and the Baruník and Kley (2019) cross-quantile dependence method to provide time-frequency-quantile evidence. In addition, we use a daily dataset from September 2, 2013, to September 30, 2022, to gauge the macroeconomic effects of the COVID-19 pandemic. We find that Petrochemical is the biggest contributor and recipient in the carbon-commodities system, and the results show that carbon markets are more influenced by other commodity markets than the reverse. Furthermore, the total connectedness is stronger in the short term but can increase over the long term, especially during the onset of COVID-19. The dynamic pair-wise results show that the carbon market can impact other commodity markets, but the effects are diverse and varied. The quantile-varying dependence between the carbon market and commodities is detected, and the cross-quantile dependence gradually strengthens as the trading days increase. This paper concludes with fruitful policy implications for resource decision-makers. © 2023 Elsevier Ltd

COVID-19, Russia-Ukraine war and interconnectedness between stock and crypto markets: a wavelet-based analysis

This paper aims to investigate the impacts of the COVID-19 pandemic and Russia-Ukraine war on the interconnectedness between the US and China stock markets, major cryptocurrency and commodity markets using the wavelet coherence approach over the period from January 1 2016 to April 18 2022. The aim is to understand how the COVID-19 pandemic and the Russia-Ukraine war have affected the hedging efficiency of volatile crypto-currencies and gold. Wavelet coherency analysis unveils perceptual differences between the short-term and longer-term market reactions. In the short-run, we find strong co-movements during the first and second waves of the pandemic. During the first wave, longer-term investors were driven by the belief of future pandemic demise. They make use of time diversification that results in positive returns. During the Russia-Ukraine war, S&P 500 leads Bitcoin, BNB, and Ripple whereas Ethereum leads S&P 500 and SSE. © 2023 The Operational Research Society.

Risk co-movements and portfolio strategies between energy, gold and BRICS markets

This study applies the parametric and nonparametric approach to examine risk comovement between energy, gold, and BRICS equity markets. Our analysis indicates that the risk comovement between these markets varies across financial crisis events. Crude oil and Russian stocks are substantially connected throughout all sub-sample periods, while gold shows a negative relationship with China and Indian stock markets. Moreover, the short-term risk transmission between the stock markets and commodity markets of China, Brazil, Russia, and India is stronger than the gold and oil markets of South Africa during the financial crises. Chinese stock market returns are higher in connectedness than other emerging markets. Further, crude oil and BRICS indices can be utilized as portfolio diversification assets to offset risks, especially during COVID-19. In addition, China and Russia have greater flexibility regarding hedging efficiency for crude oil in crises. Finally, this study offers policymakers insights into how to improve BRICS business convergence among financial and commodity markets to attract domestic and international investments while avoiding the risk of contagion. © 2023 Elsevier Ltd

Fresh evidence on connectedness between prominent markets during COVID-19 pandemic.

Various empirical studies have examined the nexus between financial markets, but this study focused on the comovement among prominent markets. Our study examines the interrelationship among main financial markets, i.e., stock, oil, and commodity during the recent pandemic. The interconnections among the selected markets are investigated using a battery of wavelet coherence tools and the Granger causality test. From the wavelet coherence analysis, our findings indicate strong co-movements among the VIX, oil volatility, and commodity prices during pandemic and localized in all scales and over the sample period. The dependency strength among the considered economies is noted to increase in pandemic, which implies increased short- and long-term benefits for the investors. Moreover, Our result exhibits a feedback causality between OVIX and crude oil, VIX and S&P 500, and gasoline and VIX. Interestingly, a unidirectional causality exists between VIX and crude oil, S&P 500 and crude oil, Brent and crude oil, gasoline, crude oil, and VIX and OVIX. We advocate that the findings will be helpful for portfolio managers, investors, and officials around the world.

Stochastic ordering of systemic risk in commodity markets

The contribution of commodity risks to the systemic risk is assessed in this paper through a novel approach that relies on the stochastic property of concordance ordering of CoVaR. Considering the period that spans from 2005 to 2022 and the VIX as the proxy for the stability of the financial system, we build the stochastic ordering of systemic risk for 35 commodities belonging to four sectors: Agriculture, Energy, Industrial Metals, and Precious Metals. The estimates of the ΔCoVaR signal that contagion effects from commodity markets to the financial system have been stronger during the years 2017–2019. Backtests validate CoVaR as a more resilient risk measure than the VaR, especially during periods of market turmoils. The stochastic ordering of CoVaR shows that severe losses (downside risk) in commodity markets tend to exacerbate systemic financial distress more than gains (upside risk). Commodity risks arising from WTI and EUA are threatening triggers for systemic risk. In contrast, the financial system is less vulnerable to a broader range of scenarios arising from fluctuations in Gold prices. As top contributors to the systemic risk, among the sectors we find Energy and Precious Metals with respect to upside risk and downside risk. The Covid-19 crisis has deeply amplified the systemic influence arising from the downside risk of WTI, Gasoline, and Natural Gas UK and has confirmed the safe-haven role of Gold. © 2022 Elsevier B.V.

COVID-19 Influence Over Brazilian Agricultural Commodities and Dollar-Real Exchange

This study evaluates the Brazilian agricultural commodities market and the dollar-real exchange price variation using the multifractal detrended fluctuations analysis methodology. We investigated the period from January 1, 2019 to September 25, 2019, outside the COVID-19 pandemic, and from January 1, 2020 to September 25, 2020, during the COVID-19 pandemic. We verified the fluctuations of commodities and dollar-real exchange prices during the pandemic caused by COVID-19 showed a record price. The results of Hurst exponent and multifractal parameters α0, w, and r indicate that during the COVID-19 pandemic, sugar was the most efficient commodity, while pork the less one. Compared to the identical months in 2019, the dollar-real exchange was the most efficient market, while ethanol was the least efficient. © 2022 World Scientific Publishing Company.

On the stylized facts of precious metals’ volatility: A comparative analysis of pre- and during COVID-19 crisis

The main aim of this paper is to investigate the stylized facts associated with the volatility of precious metals before and during the COVID-19 pandemic using GARCH-type models. In particular, we employ an ARMA-GARCH, ARMA-EGARCH and ARMA-FIGARCH framework to account for volatility clustering, asymmetry and long memory in the volatility of gold, silver, platinum and palladium. Based on structural breaks, we divide the whole sample into sub-samples and find that the breakpoints occurred after the declaration of COVID-19 pandemic. Our results show a very distinct behaviour in the memory of the four metals before and during the crisis. While there is a moderate persistence in the full sample and in the pre-COVID-19 sub-period for the four metals, this effect vanishes after the crisis outburst. Positive asymmetric effects are also found in gold and silver volatilities, which intensify during COVID-19 phase. We ascribe this phenomenon to the hedge/safe-haven properties of these metals. By contrast, a diverse pattern is observed in the palladium and platinum volatilities, which display negative asymmetries before the pandemic, in tandem of financial markets. After the crisis, these metals show mixed evidence. Moreover, we argue that COVID-19 significantly affects the volatility of precious metals. © 2022 Elsevier B.V.

Are Pair Trading Strategies Profitable during COVID-19 Period?

Pair trading strategy is a well-known profitable strategy in stock, forex, and commodity markets. As most of the world stock markets declined during COVID-19 period, therefore this study is going to observe whether this strategy is still profitable after COVID-19 pandemic. One of the powerful algorithms of DBSCAN under the umbrella of unsupervised machine learning is applied and three clusters were formed by using market and accounting data. The formation of these three clusters was based on book value per share, earning per share, classification of sector, market capitalisation and with other factors formed from PCA on the returns of daily data of six months of the 80 sample firms for year 2019-2020. An average of -0.32% average excess monthly return with Sharpe ratio of -0.0012 and Treynor ratio of -0.0231 is to be observed in COVID-19 pandemic period. However, the result of risk-adjusted performance under Jensen's alpha is observed to be insignificant. The policy implication of this study, for different portfolios and fund managers is suggested to use machine learning approach to get positive and higher returns for their clients. © 2022 World Scientific Publishing Company.