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https://hdl.handle.net/20.500.11779/716
Title: | Modeling of carbon credit prices using regime switching approach | Authors: | Çanakoğlu, Ethem Adıyeke, Esra Ağralı, Semra |
Keywords: | Structural Vector Autoregressions Eu-Ets Market Futures Price Electricity Dynamics Determinants Drivers |
Source: | Canakoglu, E., Adiyeke, E., & Agrali, S. (May 01, 2018). Modeling of carbon credit prices using regime switching approach. Journal of Renewable and Sustainable Energy, 10, 3, 35901. | Abstract: | In this study, we analyze the price dynamics of carbon certificates that are traded under the European Union's Emissions Trading System (EU-ETS). With the aim of investigating the joint relations among carbon, electricity, and fuel prices, we model historical prices using several methods and incorporating structural changes, such as econometric time series, regime switching, and multivariate vector autoregression models. We compare the results of the structural model with the results of traditional Markov switching and autoregressive models with breaks and present performance analysis based on the mean average percentage error, root mean squared error, and coefficient of determination. According to these performance tests, models with regimes outperform the approaches where breaks are defined using ex ante dummy variables. Moreover, we conclude that among regime switching models, univariate models are better than multivariate counterparts for modeling carbon price series for the analysis of both in-sample and out-of-samples. Published by AIP Publishing. | Description: | Semra Ağralı (MEF Author) | URI: | http://dx.doi.org/10.1063/1.4996653 https://hdl.handle.net/20.500.11779/716 |
ISSN: | 1941-7012 |
Appears in Collections: | Endüstri Mühendisliği Bölümü koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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10.1063@1.4996653.pdf Until 2089-02-14 | Yayıncı Sürümü - Makale | 1.45 MB | Adobe PDF | View/Open Request a copy |
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