Optimal hedge ratios for clean energy equities

By Wasim Ahmad, Perry Sadorsky, Amit Sharma. Economic Modelling, 2018

195 citations recorded by the source corpus.

Clean energy equities represent a relatively new class of assets to invest in, and these assets can be very volatile. An understanding of how investors in clean energy stocks can hedge their investment is essential for risk management. In this study, we use daily data covering the period March 03, 2008 to October 31, 2017, to examine how crude oil, US-bonds, gold, VIX, OVX and European carbon prices can be used to hedge an investment in clean energy equities. We apply three variants of multivariate GARCH models (DCC, ADCC and GO-GARCH) to estimate time-varying optimal hedge ratios. The results suggest that VIX is the best asset to hedge clean energy equities followed by crude oil and OVX. This is a new result relative to the existing literature on clean energy stock prices and one that is of interest to current and future investors in clean energy stocks.

Subfields: Economics and Econometrics, Finance, General Energy

View Paper: https://www.semanticscholar.org/paper/12cc82c7c6789d706901a52d959125ec4140c857

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In Economics and Econometrics

1. Anupam Dutta
2. Elie Bouri
3. Tareq Saeed
4. Gazi Salah Uddin
5. B. Elie
6. J. Naji
7. D. Tran
8. David Roubaud

In Finance

1. B. Elie
2. Tareq Saeed
3. Anupam Dutta
4. J. Naji
5. Gazi Salah Uddin
6. D. Tran
7. Elie Bouri
8. Afees A. Salisu

In General Energy

1. Tareq Saeed
2. Anupam Dutta
3. Gazi Salah Uddin
4. D. Tran
5. Elie Bouri

Citations in the corpus

• Crude oil prices and clean energy stock indices: Lagged and asymmetric effects with quantile regression (2021, background): “[22] show that OVX and clean energy equities are negatively correlated, suggesting that the inclusion of OVX in a portfolio of clean energy equities reduces the risk associated with the alternative energy markets.”
• Gold and crude oil as safe-haven assets for clean energy stock indices: Blended copulas approach (2019, methodology): “…models can explain the relationship between Clean Energy Stock Indices and Gold Or Crude Oil Different econometric methods have been used such as DCC and Multivariate GARCH models (Ahmad et al., 2018; Sadorsky, 2012a), Connectedness measures (Ahmad, 2017), and Cointegration (Bondia et al., 2016).”
• Hedging Strategies of Green Assets against Dirty Energy Assets (2020, methodology): “[5] apply multivariate GARCH models to examine how indices from the crude oil, gold, and US bonds markets are related to clean energy stocks.”