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Article
Publication date: 22 March 2024

Amira Said and Chokri Ouerfelli

This paper aims to examine the dynamic conditional correlation (DCC) and hedging ratios between Dow Jones markets and oil, gold and bitcoin. Using daily data, including the…

154

Abstract

Purpose

This paper aims to examine the dynamic conditional correlation (DCC) and hedging ratios between Dow Jones markets and oil, gold and bitcoin. Using daily data, including the COVID-19 pandemic and the Russia–Ukraine war. We employ the DCC-generalized autoregressive conditional heteroskedasticity (GARCH) and asymmetric DCC (ADCC)-GARCH models.

Design/methodology/approach

DCC-GARCH and ADCC-GARCH models.

Findings

The most of DCCs among market pairs are positive during COVID-19 period, implying the existence of volatility spillovers (Contagion-effects). This implies the lack of additional economic gains of diversification. So, COVID-19 represents a systematic risk that resists diversification. However, during the Russia–Ukraine war the DCCs are negative for most pairs that include Oil and Gold, implying investors may benefit from portfolio-diversification. Our hedging analysis carries significant implications for investors seeking higher returns while hedging their Dow Jones portfolios: keeping their portfolios unhedged is better than hedging them. This is because Islamic stocks have the ability to mitigate risks.

Originality/value

Our paper may make a valuable contribution to the existing literature by examining the hedging of financial assets, including both conventional and Islamic assets, during periods of stability and crisis, such as the COVID-19 pandemic and the Russia–Ukraine war.

Details

The Journal of Risk Finance, vol. 25 no. 3
Type: Research Article
ISSN: 1526-5943

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Article
Publication date: 24 July 2020

Paul Adjei Kwakwa

This study aims to fill the gap in existing studies that have analyzed the drivers of carbon dioxide (CO2) emissions. The author investigate the long-run effects of energy types…

510

Abstract

Purpose

This study aims to fill the gap in existing studies that have analyzed the drivers of carbon dioxide (CO2) emissions. The author investigate the long-run effects of energy types, urbanization, financial development and, the interaction between urbanization and financial development on CO2 emissions.

Design/methodology/approach

Stochastic impacts by regression on population, affluence and technology model served as the framework for empirical modeling. Using annual time-series data for Tunisia, autoregressive distributed lag bounds test was used to examine the cointegration of the variables. Also, the fully modified ordinary least squares was used to estimate the emission effect of the explanatory variables. Further investigations were done using the principal component analysis and variance decomposition analysis.

Findings

Income, urbanization, trade and financial development exert upward pressure on CO2 emissions. However, the interaction between urbanization and financial development reduces the emission of CO2. Furthermore, primary energy use, energy intensity, electricity consumption and fossil fuel consumption have positive effects on carbon emission, while combustible renewables and waste, and electricity production from natural gas have negative effects on carbon emission.

Practical implications

The policy implication/recommendation indicates that the financial sector’s authorities can combat carbon emission by properly regulating the development and activities of the financial sector in urban areas in Tunisia. The promotion of the development and usage of cleaner energy is recommended to help reduce carbon emission. Policymakers need to promote environmentally friendly economic growth and development agenda.

Originality/value

The contribution of this study to the environmental degradation literature is that it offers evidence from Tunisia, which has not received much empirical attention. It also examines the effect of various forms of energy usage on carbon emission. To the best of the author’s knowledge, this is the first study to examine the interaction effect between urbanization and financial development on carbon emission. Also, if not the first, this study is among the earliest to use the principal component analysis as a part of the prediction of the carbon emission effect of energy variables.

Details

International Journal of Energy Sector Management, vol. 14 no. 6
Type: Research Article
ISSN: 1750-6220

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