Stochastic volatility of the futures prices of emission allowances: A Bayesian approach

Kim, Jungmu; Park, Yuen Jung; Ryu, Doojin

doi:10.1016/j.physa.2016.08.036

Cited by 23 publications

(6 citation statements)

References 21 publications

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“…We assume a generalized error distribution and calculate the conditional variances of carbon spot and futures and show the results in Figure 4 and Figure 5. Intuitively, carbon spot and futures returns were volatile in the first half of 2013, the conditional variances reached the maximum in the sample period, and the entrance of Phase III may explain the phenomenon as significant changes occurred in the cap-and-trade system and the prohibition of banking of residual allowances [40]. Besides, the results in Figures 4 and 5 consist with the finding of Kim [40] and Zhang [2], whose research sample period covers Phase III.…”

Section: Correlation Between Spot and Futures Price Futures Price Corsupporting

confidence: 65%

“…Intuitively, carbon spot and futures returns were volatile in the first half of 2013, the conditional variances reached the maximum in the sample period, and the entrance of Phase III may explain the phenomenon as significant changes occurred in the cap-and-trade system and the prohibition of banking of residual allowances [40]. Besides, the results in Figures 4 and 5 consist with the finding of Kim [40] and Zhang [2], whose research sample period covers Phase III. In addition, it can also be noticed that compared with the variances in each calendar year, the variation at the beginning of each year is much more volatile, which may be ascribed to the "yearly complaint event."…”

Section: Correlation Between Spot and Futures Price Futures Price Corsupporting

confidence: 65%

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The Linkages of Carbon Spot-Futures: Evidence from EU-ETS in the Third Phase

et al. 2020

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Based on the prices selected from European Energy Exchange (EEX) from 2013 to 2018, we investigate the inter-correlation of carbon spot and futures markets. Specifically, we adopt the widely used DCC-GARCH model and VAR-BEKK-GARCH model to conduct a comprehensive analysis on the carbon market, i.e., the dynamic correlation and volatility spillover between carbon spot and carbon futures. Moreover, we develop a hedge strategy based on the VAR-BEKK-GARCH model and calculate the hedging effectiveness (HE) value to evaluate the strategy performance. The empirical results show that (i) during our sample period, carbon spot and futures markets are highly correlated, (ii) carbon spot overflows to the futures market and vice versa, and (iii) the HE value is equal to 0.9370, indicating a good performance for the hedging strategy. Then, we provide further discussion on the relationship between carbon spot and futures markets by replacing our dataset with the data of phase II. The results do not change our conclusions on the dynamic correlation and volatility spillover. However, the HE value of phase III is higher than that of phase II, which indicates that the carbon futures market of phase III is not only an available market to hedge risk from the contemporaneous carbon spot market but also has a better hedge effectiveness than phase II.

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Section: Correlation Between Spot and Futures Price Futures Price Corsupporting

confidence: 65%

Section: Correlation Between Spot and Futures Price Futures Price Corsupporting

confidence: 65%

The Linkages of Carbon Spot-Futures: Evidence from EU-ETS in the Third Phase

et al. 2020

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“…When demand returns to normal levels, prices will fall. Besides the mean reverting characteristic, the spot price is proportion to its variance in the current CO 2 emission market [7]. This important property improves the assessment of production costs incorporating CO 2 costs since the introduction of emission trading system, or supports emissions-related investment decisions.…”

Section: Discussionmentioning

confidence: 99%

“…The authors proposed that the CO 2 emissions allowance spot price process should have a time-and price-dependent volatility structure. Recently, Kim et al [7] estimated the dynamics of EUA futures prices based on Heston's stochastic volatility model with or without jumps, and their empirical results revealed three important features of EUA futures prices: significant stochastic volatility, noticeable leverage effect, and inclusion of jumps.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Differential Equation Models for the Price of European CO2 Emissions Allowances

Cai

Pan

2017

Sustainability

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Abstract:Understanding the stochastic nature of emissions allowances is crucial for risk management in emissions trading markets. In this study, we discuss the emissions allowances spot price within the European Union Emissions Trading Scheme: Powernext and European Climate Exchange. To compare the fitness of five stochastic differential equations (SDEs) to the European Union allowances spot price, we apply regression theory to obtain the point and interval estimations for the parameters of the SDEs. An empirical evaluation demonstrates that the mean reverting square root process (MRSRP) has the best fitness of five SDEs to forecast the spot price. To reduce the degree of smog, we develop a new trading scheme in which firms have to hand many more allowances to the government when they emit one unit of air pollution on heavy pollution days, versus one allowance on clean days. Thus, we set up the SDE MRSRP model with Markovian switching to analyse the evolution of the spot price in such a scheme. The analysis shows that the allowances spot price will not jump too much in the new scheme. The findings of this study could contribute to developing a new type of emissions trading.

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“…Interesting recent research has been undertaken on analyses of price and volatility from the perspective of derivative markets and alternative volatility models, such as the price impact, trading volume and volatilities associated with mission permits and the announcement of realized emissions in [23] Hitzemann, Uhrig-Homburg, and Ehrhart (2015); a Bayesian approach to the stochastic volatility of future prices of emission allowances in [24] Kim, Park, and Ryu (2017); and the empirical performance of reduced form models for emission permit prices in [25] Hitzemann and Uhrig-Homburg (2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling Latent Carbon Emission Prices for Japan: Theory and Practice

Chang

McAleer

2019

Energies

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Climate change and global warming are significantly affected by carbon emissions that arise from the burning of fossil fuels, specifically coal, oil, and gas. Accurate prices are essential for the purposes of measuring, capturing, storing, and trading in carbon emissions at regional, national, and international levels, especially as carbon emissions can be taxed appropriately when the price is known and widely accepted. This paper uses a novel Capital (K), Labor (L), Energy (E) and Materials (M) (or KLEM) production function approach to calculate the latent carbon emission prices, where carbon emission is the output and capital (K), labor (L), energy (E) (or electricity), and materials (M) are the inputs for the production process. The variables K, L, and M are essentially fixed on a daily or monthly basis, whereas E can be changed more frequently, such as daily or monthly, so that changes in carbon emissions depend on changes in E. If prices are assumed to depend on the average cost pricing, the prices of carbon emissions and energy may be approximated by an energy production model with a constant factor of proportionality, so that carbon emission prices are a function of energy prices. Using this novel modeling approach, this paper estimates the carbon emission prices for Japan using seasonally adjusted and unadjusted monthly data on the volumes of carbon emissions and energy, as well as energy prices, from December 2008 to April 2018. The econometric models show that, as sources of electricity, the logarithms of coal and oil, though not Liquefied Natural Gas (LNG,) are statistically significant in explaining the logarithm of carbon emissions, with oil being more significant than coal. The models generally displayed a high power in predicting the latent prices of carbon emissions. The usefulness of the empirical findings suggest that the methodology can also be applied for other countries where carbon emission prices are latent.

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Stochastic volatility of the futures prices of emission allowances: A Bayesian approach

Cited by 23 publications

References 21 publications

The Linkages of Carbon Spot-Futures: Evidence from EU-ETS in the Third Phase

The Linkages of Carbon Spot-Futures: Evidence from EU-ETS in the Third Phase

Stochastic Differential Equation Models for the Price of European CO2 Emissions Allowances

Modeling Latent Carbon Emission Prices for Japan: Theory and Practice

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