Carbon credit futures as an emerging asset: Hedging, diversification and downside risks

Demiralay, Sercan; Gencer, Hatice Gaye; Bayracı, Selçuk

doi:10.1016/j.eneco.2022.106196

Cited by 25 publications

(2 citation statements)

References 100 publications

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“…The Chow test presented in Table 10 provides the evidence of a structural break in the optimal hedge ratios for all cases, except for oats, soybean oil, and cotton. The result indicates the outbreak of COVID‐19 appears to have changed the hedging ratios of commodity futures (Demiralay et al, 2022).…”

Section: Financial Implicationsmentioning

confidence: 99%

Global climate change and commodity markets: A hedging perspective

Jia

Chen

Han

et al. 2023

Journal of Futures Markets

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This paper aims to measure the tail‐risk dependence between climate change and commodity futures markets. We utilize Morgan Stanley Capital International Climate Change Index (CCI) to serve as a proxy indicator of the stock market climate change for examining the tail‐risk spillover effect among 16 major commodity futures. Using GARCH–Copula–CoVaR framework, we show that extreme climate change has a significant tail‐risk spillover effect on commodity futures markets, in which agricultural and energy futures are affected by climate change most. We then adopt the copula‐based generalized autoregressive conditional heteroskedasticity (GARCH) model to compute the optimal hedge ratio among each pair of CCI with commodity futures, which performs well economic advantages for all 16 commodities. Compared with hedging against commodity index, CCI has a more significant hedging effect on metal and energy subindex futures. Therefore, we finally suggest an effective hedging portfolio composed of CCI and subindex futures in a significant economic sense.

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Section: Financial Implicationsmentioning

confidence: 99%

Global climate change and commodity markets: A hedging perspective

Jia

Chen

Han

et al. 2023

Journal of Futures Markets

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“…Ahmad et al (2018) proved that the EU carbon price can be used as a hedging asset for clean energy, although the effect is poor compared with VIX and crude oil. Research by Demiralay et al (2022) also shows that adding a small portion of carbon futures to a stock portfolio can provide hedging returns and reduce the overall risk at a given expected return level. However, the above researches are all carried out from the average condition, ignoring the spread of tail risk concerned by investors (Su, 2020).…”

Section: Introductionmentioning

confidence: 99%

Extreme risk spillovers across energy and carbon markets: Evidence from the quantile extended joint connectedness approach

Cao

Xie

2023

Int. J Fin Econ

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Extreme events have further complicated the already closely related carbon‐energy system, but little research has focused on the extreme spillovers between energy and carbon markets. This paper combines quantile vector autoregression with the extended joint connectedness approach to introduce a new quantile extended joint connectedness approach to study the extreme spillover between the carbon market, fossil energy and clean energy markets, using daily data spanning from October 15, 2010 to February 25, 2022. The results show that markets are more closely linked at extreme risk, and the spillover is time‐varying and cyclical. The impact of extreme events will strengthen the links between markets. Further research shows different clean energy have heterogeneous spillovers on the carbon market, especially when impacted by extreme events. Finally, the hedging and portfolio effectiveness of clean energy to carbon market also show the existence of heterogeneity, and clean energy can diversify the portfolio of carbon market.

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Risk spillover measurement of carbon trading market considering susceptible factors: A network perspective

Dong,

Lian,

Jiang

2024

Int. J Fin Econ

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An objective and robust network‐based data‐driven strategy is proposed to analyze risk spillovers in carbon markets. First, we characterize the causality network between the carbon market and potential associated markets using a data‐driven fuzzy cognitive map approach. Second, network‐based community detection is conducted to explore community structures that include carbon trading markets, and five market factors belonging to the same community as EU Allowances (EUA) are identified. Next, we conduct downside and upside‐tail measurements of EUA risk spillover levels within the community based on estimates and fits of marginal and joint distributions for different market pairs. Finally, we point out that the market factor having the most significant upper‐tail spillover effects on EUA is OILFUTURE, besides, EURUSD asset is found to be the best hedge for EUA futures among the detected market factors.

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Carbon credit futures as an emerging asset: Hedging, diversification and downside risks

Cited by 25 publications

References 100 publications

Global climate change and commodity markets: A hedging perspective

Global climate change and commodity markets: A hedging perspective

Extreme risk spillovers across energy and carbon markets: Evidence from the quantile extended joint connectedness approach

Risk spillover measurement of carbon trading market considering susceptible factors: A network perspective

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