• Title/Summary/Keyword: EUA price

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Analysis on Price Driver of Spread and Different Patterns of EUA and sCER (탄소배출권 EUA와 sCER의 가격 차이 패턴 및 스프레드(Spread) 결정 요인 분석)

  • Park, Soonchul;Cho, Yongsung
    • Environmental and Resource Economics Review
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    • v.22 no.4
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    • pp.759-784
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    • 2013
  • Participants can use the allowances and offsets for implementing the compliance in the Emissions Trading Scheme(ETS). There are alternative commodities which are different prices it gives the opportunities to reduce the compliance costs and get the arbitrage. This study analyzes the price driver of spread which is the difference between EUA and sCER using AR-GARCH model, EUA and CER during the Phase 2 in EU ETS. The results show that there are common elements which impacts the EUA and sCER and also different elements between them. EUA and sCER get the effects from energy price and economic criteria such as coal price and financial crisis as common elements. However them get the effects from electric price, policy criteria such as restricted CERs and difference price between EUA and ERU price as different elements. The results shows that spread will be widen if energy price increase, especially oil and electric price give more impacts the spreads. This study has the means that it explains the reason why the spreads will broaden sharply in 2012. And it also suggests the price driver of spread during the whole period of Phase 2. In addition, this study shows that political aspects maybe become the main criteria of price change with structural elements shch as energy price in Korea ETS which starts in 2015.

An Empirical Study on Price discovery between Emission Spot and Futures Markets in EU ETS Emission Markets (EU ETS 탄소시장에서 EUA 선물의 가격발견에 관한 연구)

  • Kim, Soo-Kyung
    • Management & Information Systems Review
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    • v.33 no.3
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    • pp.93-104
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    • 2014
  • This study investigates price discovery between BlueNext spot and futures in EU ETS carbon emission markets using vector error correction model, GG and Hasbruck information ratio. Especially EUA is European Union Allowances traded on the Emissions Trading Scheme. This emission asset attracts and increasing attention among operators, investors and brokers on emission markets. In this study, we found BlueNext spot and EUA futures market are cointegrated. Following the preceding studies, we judged that EUA futures market contribute to the price discovery process than BlueNext spot market when this GG and Hasbrouck information ratio for BlueNext market are larger than 0.5. In other words, the futures market of EUA plays a more dominant role in price discovery than the spot market.

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The Analysis of EU Carbon Prices Using SVECM Approach (SVECM 모형을 이용한 탄소배출권 가격 연구)

  • Bu, Gi-Duck;Jeong, Kiho
    • Environmental and Resource Economics Review
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    • v.20 no.3
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    • pp.531-565
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    • 2011
  • All previous studies analyzing multivariate time series data of EUA (European Union Allowance) price commonly used endogenous variables within the four variables and included the period from April to June of 2006 in the analysis, when the price distortion occurred. This study uses graph theory and structural vector error correction model (SVECM) to analyze the daily time series data of the EUA (European Union Allowance) price. As endogenous variables, five variables are considered for the analysis, including prices of crude oil, natural gas, electricity and coal in addition to carbon price. Data period is Phase 2 period (April 21, 2008 to March 31, 2010) to avoid the EUA price distortion of Phase 1 period (2005~2007). Further, the monthly data including the economic variables as endogenous variables are analyzed.

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The analysis of EU carbon trading and energy prices using vector error correction model (벡터오차수정모형을 이용한 유럽 탄소배출권가격 분석)

  • Bu, Gi-Duck;Jeong, Ki-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.3
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    • pp.401-412
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    • 2011
  • This study uses a vector error correction model to analyze the daily time series data of the spot price of EUA (European Union Allowance). As endogenous variables, five variables are considered for the analysis, including prices of crude oil, natural gas, electricity and coal in addition to carbon price. Data period is Phase 2 period (April 21, 2008 to March 31, 2010) to avoid Phase 1 period (2005-2007) where the EUA prices were distorted. Unit-root and cointegration test results reveal that all variables have a unit root and cointegration vectors exist, so a vector error correction model is adopted instead of a vector autoregressive model.

An Empirical Study on the effects of volatility of carbon market on stock price volatility : Focusing on Europe iron and cement sector (탄소시장의 변동성이 주가변동성에 미치는 영향에 관한 실증연구 : 유럽의 철강산업과 시멘트산업을 중심으로)

  • Lee, Dong-Woo;Kim, Young-Duk
    • International Area Studies Review
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    • v.21 no.4
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    • pp.223-245
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    • 2017
  • This study is examined interaction between carbon market with stock market using a multivariate GARCH(DCC) model. Carbon market is EU ETS EUA price, stock market is the iron and cement stock price which has relatively energy intensive and massive carbon emissions sector in the industrial sector. It also analyzed changes in the correlation between the markets through an analysis of correlation coefficients. Moreover, it checked whether there was marketability expansion(or expansion of carbon emissions reduction) through the analysis above. As a result of empirical tests, it showed that the price spillover effect was insignificant. In addition, it represented that there was a weak correlation between the two markets since the volatility spillover effect disappeared in the second phase by an external shock(a financial crisis). Moreover, it was revealed that there were no significant changes although there was a weak upward trend in terms of the correlation between the carbon market and the stock market. This implies that emission rights could not expand marketability to financial market as a commodity(or did not play its natural role of the reduction of carbon emission).