Dmitriy O. Afanasyev
Personal Details
First Name: | Dmitriy |
Middle Name: | O. |
Last Name: | Afanasyev |
Suffix: | |
RePEc Short-ID: | paf34 |
[This author has chosen not to make the email address public] | |
http://dmafanasyev.ru/en | |
Affiliation
Financial University under the Government of the Russian Federation
Moscow, Russiahttp://www.fa.ru/
RePEc:edi:fugrfru (more details at EDIRC)
Research output
Jump to: Working papers ArticlesWorking papers
- Afanasyev, Dmitriy & Fedorova, Elena, 2015. "The long-term trends on Russian electricity market: comparison of empirical mode and wavelet decompositions," MPRA Paper 62391, University Library of Munich, Germany.
- Afanasyev, Dmitriy & Fedorova, Elena & Popov, Viktor, 2014.
"Fine structure of the price-demand relationship in the electricity market: multi-scale correlation analysis,"
MPRA Paper
58827, University Library of Munich, Germany.
- Afanasyev, Dmitriy O. & Fedorova, Elena A. & Popov, Viktor U., 2015. "Fine structure of the price–demand relationship in the electricity market: Multi-scale correlation analysis," Energy Economics, Elsevier, vol. 51(C), pages 215-226.
Articles
- Afanasyev, Dmitriy O. & Fedorova, Elena & Ledyaeva, Svetlana, 2021. "Strength of words: Donald Trump's tweets, sanctions and Russia's ruble," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 253-277.
- Dmitriy O. Afanasyev & Elena A. Fedorova & Evgeniy V. Gilenko, 2021. "The fundamental drivers of electricity price: a multi-scale adaptive regression analysis," Empirical Economics, Springer, vol. 60(4), pages 1913-1938, April.
- Dmitriy Afanasyev & Elena Fedorova & Oleg Rogov, 2019. "On the Impact of News Tonality in International Media on the Russian Ruble Exchange Rate: Textual Analysis," HSE Economic Journal, National Research University Higher School of Economics, vol. 23(2), pages 264-289.
- Afanasyev, Dmitriy O. & Fedorova, Elena A., 2019. "On the impact of outlier filtering on the electricity price forecasting accuracy," Applied Energy, Elsevier, vol. 236(C), pages 196-210.
- Elena A. Fedorova & Svetlana O. Musienko & Igor S. Demin & Fedor Yu. Fedorov & Dmitriy O. Afanasyev, 2019. "The impact of news coverage of Russia in the media on export—import activities," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 8.
- Elena Fyodorova & Ruslan Sayakhov & Igor Demin & Dmitriy Afanasyev, 2019. "The influence of conference calls' semantic characteristics on the company market performance: Text analysis," Russian Journal of Economics, ARPHA Platform, vol. 5(3), pages 297-320, October.
- Afanasyev, D. & Fedorova, E., 2018. "External and Internal Determinants on the Electricity Market: A Multi-Scale Adaptive Causal Analysis," Journal of the New Economic Association, New Economic Association, vol. 39(3), pages 33-54.
- Afanasiev, Dmitriy (Афанасьев, Дмитрий) & Fedorova, Elena, 2016. "Currency integration of Russia and other CIS countries: what is changing in a crisis? [Валютная Интеграция России И Других Стран Снг: Что Меняется В Кризис?]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 2, pages 133-147, April.
- Afanasyev, Dmitriy O. & Fedorova, Elena A., 2016. "The long-term trends on the electricity markets: Comparison of empirical mode and wavelet decompositions," Energy Economics, Elsevier, vol. 56(C), pages 432-442.
- Afanasyev, Dmitriy O. & Fedorova, Elena A. & Popov, Viktor U., 2015.
"Fine structure of the price–demand relationship in the electricity market: Multi-scale correlation analysis,"
Energy Economics, Elsevier, vol. 51(C), pages 215-226.
- Afanasyev, Dmitriy & Fedorova, Elena & Popov, Viktor, 2014. "Fine structure of the price-demand relationship in the electricity market: multi-scale correlation analysis," MPRA Paper 58827, University Library of Munich, Germany.
Citations
Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.Working papers
- Afanasyev, Dmitriy & Fedorova, Elena & Popov, Viktor, 2014.
"Fine structure of the price-demand relationship in the electricity market: multi-scale correlation analysis,"
MPRA Paper
58827, University Library of Munich, Germany.
- Afanasyev, Dmitriy O. & Fedorova, Elena A. & Popov, Viktor U., 2015. "Fine structure of the price–demand relationship in the electricity market: Multi-scale correlation analysis," Energy Economics, Elsevier, vol. 51(C), pages 215-226.
Cited by:
- Afanasyev, Dmitriy & Fedorova, Elena, 2015. "The long-term trends on Russian electricity market: comparison of empirical mode and wavelet decompositions," MPRA Paper 62391, University Library of Munich, Germany.
- Afanasyev, D. & Fedorova, E., 2018. "External and Internal Determinants on the Electricity Market: A Multi-Scale Adaptive Causal Analysis," Journal of the New Economic Association, New Economic Association, vol. 39(3), pages 33-54.
- Balagula, Yuri, 2020. "Forecasting daily spot prices in the Russian electricity market with the ARFIMA model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 89-101.
- Qunwei Wang & Xingyu Dai & Dequn Zhou, 2020. "Dynamic Correlation and Risk Contagion Between “Black” Futures in China: A Multi-scale Variational Mode Decomposition Approach," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1117-1150, April.
- Abdullah, Mohammad & Abakah, Emmanuel Joel Aikins & Wali Ullah, G M & Tiwari, Aviral Kumar & Khan, Isma, 2023. "Tail risk contagion across electricity markets in crisis periods," Energy Economics, Elsevier, vol. 127(PB).
- Qing Peng & Fenghua Wen & Xu Gong, 2021. "Time‐dependent intrinsic correlation analysis of crude oil and the US dollar based on CEEMDAN," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 834-848, January.
- Lei Jiang & Ling Bai, 2017. "Revisiting the Granger Causality Relationship between Energy Consumption and Economic Growth in China: A Multi-Timescale Decomposition Approach," Sustainability, MDPI, vol. 9(12), pages 1-17, December.
- Fang, Guochang & Tian, Lixin & Liu, Menghe & Fu, Min & Sun, Mei, 2018. "How to optimize the development of carbon trading in China—Enlightenment from evolution rules of the EU carbon price," Applied Energy, Elsevier, vol. 211(C), pages 1039-1049.
- Wang, Haoyu & Di, Junpeng & Yang, Zhaojun & Han, Qing, 2020. "Assessment of mutual fund performance based on Ensemble Empirical Mode Decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
- Niu, Hongli, 2021. "Correlations between crude oil and stocks prices of renewable energy and technology companies: A multiscale time-dependent analysis," Energy, Elsevier, vol. 221(C).
- Dmitriy O. Afanasyev & Elena A. Fedorova & Evgeniy V. Gilenko, 2021. "The fundamental drivers of electricity price: a multi-scale adaptive regression analysis," Empirical Economics, Springer, vol. 60(4), pages 1913-1938, April.
- Afanasyev, Dmitriy O. & Fedorova, Elena A., 2016. "The long-term trends on the electricity markets: Comparison of empirical mode and wavelet decompositions," Energy Economics, Elsevier, vol. 56(C), pages 432-442.
Articles
- Afanasyev, Dmitriy O. & Fedorova, Elena & Ledyaeva, Svetlana, 2021.
"Strength of words: Donald Trump's tweets, sanctions and Russia's ruble,"
Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 253-277.
Cited by:
- Catalin Dragomirescu-Gaina & Dionisis Philippas & Stéphane Goutte, 2022.
"How to 'Trump' the energy market: evidence from the WTI-Brent spread,"
Working Papers
halshs-03843257, HAL.
- Dragomirescu-Gaina, Catalin & Philippas, Dionisis & Goutte, Stéphane, 2023. "How to ‘Trump’ the energy market: Evidence from the WTI-Brent spread," Energy Policy, Elsevier, vol. 179(C).
- Zhang, Qisi & Frömmel, Michael & Baidoo, Edwin, 2024. "Donald Trump's tweets, political value judgment, and the Renminbi exchange rate," International Review of Financial Analysis, Elsevier, vol. 93(C).
- Zhou, Wen, 2023. "Did Donald Trump's tweets on Sino–U.S. Trade affect the offshore RMB exchange rate?," Finance Research Letters, Elsevier, vol. 58(PA).
- Zhou, Peng & Guo, Dong, 2023. "Sanctions, Co-sanctions, and Counter-sanctions: A Multilateral, Evolutionary Game among Three Global Powers," Cardiff Economics Working Papers E2023/28, Cardiff University, Cardiff Business School, Economics Section.
- Catalin Dragomirescu-Gaina & Dionisis Philippas & Stéphane Goutte, 2022.
"How to 'Trump' the energy market: evidence from the WTI-Brent spread,"
Working Papers
halshs-03843257, HAL.
- Dmitriy O. Afanasyev & Elena A. Fedorova & Evgeniy V. Gilenko, 2021.
"The fundamental drivers of electricity price: a multi-scale adaptive regression analysis,"
Empirical Economics, Springer, vol. 60(4), pages 1913-1938, April.
Cited by:
- Alex Borodin & Galina Panaedova & Svetlana Frumina & Aidyn Kairbekuly & Natalia Shchegolevatykh, 2021. "Modeling the Business Environment of an Energy Holding in the Formation of a Financial Strategy," Energies, MDPI, vol. 14(23), pages 1-18, December.
- Michail I. Seitaridis & Nikolaos S. Thomaidis & Pandelis N. Biskas, 2021. "Fundamental Responsiveness in European Electricity Prices," Energies, MDPI, vol. 14(22), pages 1-14, November.
- Afanasyev, Dmitriy O. & Fedorova, Elena A., 2019.
"On the impact of outlier filtering on the electricity price forecasting accuracy,"
Applied Energy, Elsevier, vol. 236(C), pages 196-210.
Cited by:
- Gang Zhou & Zhongjie Han & Jin Fu & Guan Hua Xu & Chengjin Ye, 2020. "Iterative Online Fault Identification Scheme for High-Voltage Circuit Breaker Utilizing a Lost Data Repair Technique," Energies, MDPI, vol. 13(13), pages 1-15, June.
- Beltrán, Sergio & Castro, Alain & Irizar, Ion & Naveran, Gorka & Yeregui, Imanol, 2022. "Framework for collaborative intelligence in forecasting day-ahead electricity price," Applied Energy, Elsevier, vol. 306(PA).
- Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
- Arkadiusz Jedrzejewski & Grzegorz Marcjasz & Rafal Weron, 2021.
"Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO,"
WORking papers in Management Science (WORMS)
WORMS/21/04, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
- Arkadiusz Jędrzejewski & Grzegorz Marcjasz & Rafał Weron, 2021. "Importance of the Long-Term Seasonal Component in Day-Ahead Electricity Price Forecasting Revisited: Parameter-Rich Models Estimated via the LASSO," Energies, MDPI, vol. 14(11), pages 1-17, June.
- Li, Dongxin & Zhang, Li & Li, Lihong, 2023. "Forecasting stock volatility with economic policy uncertainty: A smooth transition GARCH-MIDAS model," International Review of Financial Analysis, Elsevier, vol. 88(C).
- Sheybanivaziri, Samaneh & Le Dréau, Jérôme & Kazmi, Hussain, 2024. "Forecasting price spikes in day-ahead electricity markets: techniques, challenges, and the road ahead," Discussion Papers 2024/1, Norwegian School of Economics, Department of Business and Management Science.
- Billé, Anna Gloria & Gianfreda, Angelica & Del Grosso, Filippo & Ravazzolo, Francesco, 2023.
"Forecasting electricity prices with expert, linear, and nonlinear models,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 570-586.
- Anna Gloria Billé & Angelica Gianfreda & Filippo Del Grosso & Francesco Ravazzolo, 2021. "Forecasting Electricity Prices with Expert, Linear and Non-Linear Models," Working Paper series 21-20, Rimini Centre for Economic Analysis.
- Daniel Manfre Jaimes & Manuel Zamudio López & Hamidreza Zareipour & Mike Quashie, 2023. "A Hybrid Model for Multi-Day-Ahead Electricity Price Forecasting considering Price Spikes," Forecasting, MDPI, vol. 5(3), pages 1-23, July.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020.
"Forecasting: theory and practice,"
Papers
2012.03854, arXiv.org, revised Jan 2022.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Manuel Zamudio López & Hamidreza Zareipour & Mike Quashie, 2024. "Forecasting the Occurrence of Electricity Price Spikes: A Statistical-Economic Investigation Study," Forecasting, MDPI, vol. 6(1), pages 1-23, February.
- Bartosz Uniejewski, 2023. "Electricity price forecasting with Smoothing Quantile Regression Averaging: Quantifying economic benefits of probabilistic forecasts," Papers 2302.00411, arXiv.org, revised Jan 2024.
- Elmore, Clay T. & Dowling, Alexander W., 2021. "Learning spatiotemporal dynamics in wholesale energy markets with dynamic mode decomposition," Energy, Elsevier, vol. 232(C).
- Qiao, Weibiao & Yang, Zhe, 2020. "Forecast the electricity price of U.S. using a wavelet transform-based hybrid model," Energy, Elsevier, vol. 193(C).
- Rainer Baule & Michael Naumann, 2021. "Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market," Energies, MDPI, vol. 14(22), pages 1-24, November.
- Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
- Uniejewski, Bartosz & Weron, Rafał, 2021.
"Regularized quantile regression averaging for probabilistic electricity price forecasting,"
Energy Economics, Elsevier, vol. 95(C).
- Bartosz Uniejewski & Rafal Weron, 2019. "Regularized Quantile Regression Averaging for probabilistic electricity price forecasting," HSC Research Reports HSC/19/04, Hugo Steinhaus Center, Wroclaw University of Technology.
- AL-Alimi, Dalal & AlRassas, Ayman Mutahar & Al-qaness, Mohammed A.A. & Cai, Zhihua & Aseeri, Ahmad O. & Abd Elaziz, Mohamed & Ewees, Ahmed A., 2023. "TLIA: Time-series forecasting model using long short-term memory integrated with artificial neural networks for volatile energy markets," Applied Energy, Elsevier, vol. 343(C).
- Shao, Zhen & Yang, Yudie & Zheng, Qingru & Zhou, Kaile & Liu, Chen & Yang, Shanlin, 2022. "A pattern classification methodology for interval forecasts of short-term electricity prices based on hybrid deep neural networks: A comparative analysis," Applied Energy, Elsevier, vol. 327(C).
- Afanasyev, Dmitriy O. & Fedorova, Elena A., 2016.
"The long-term trends on the electricity markets: Comparison of empirical mode and wavelet decompositions,"
Energy Economics, Elsevier, vol. 56(C), pages 432-442.
Cited by:
- Sun, Jie & Zhao, Xiaojun & Xu, Chao, 2021. "Crude oil market autocorrelation: Evidence from multiscale quantile regression analysis," Energy Economics, Elsevier, vol. 98(C).
- Afanasyev, D. & Fedorova, E., 2018. "External and Internal Determinants on the Electricity Market: A Multi-Scale Adaptive Causal Analysis," Journal of the New Economic Association, New Economic Association, vol. 39(3), pages 33-54.
- Arkadiusz Jedrzejewski & Grzegorz Marcjasz & Rafal Weron, 2021.
"Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO,"
WORking papers in Management Science (WORMS)
WORMS/21/04, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
- Arkadiusz Jędrzejewski & Grzegorz Marcjasz & Rafał Weron, 2021. "Importance of the Long-Term Seasonal Component in Day-Ahead Electricity Price Forecasting Revisited: Parameter-Rich Models Estimated via the LASSO," Energies, MDPI, vol. 14(11), pages 1-17, June.
- Д.О. Афанасьев1 & * & Е.А. Федорова2 & **, 2019. "Краткосрочное Прогнозирование Цены Электроэнергии На Российском Рынке С Использованием Класса Моделей Scarx," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 55(1), pages 68-84, январь.
- Fan He & Xuansen He, 2019. "A Continuous Differentiable Wavelet Shrinkage Function for Economic Data Denoising," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 729-761, August.
- Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2018.
"Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?,"
HSC Research Reports
HSC/18/05, Hugo Steinhaus Center, Wroclaw University of Technology.
- Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał, 2020. "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 466-479.
- Liu, Siyao & Fang, Wei & Gao, Xiangyun & Wang, Ze & An, Feng & Wen, Shaobo, 2020. "Self-similar behaviors in the crude oil market," Energy, Elsevier, vol. 211(C).
- Afanasyev, Dmitriy O. & Fedorova, Elena A., 2019. "On the impact of outlier filtering on the electricity price forecasting accuracy," Applied Energy, Elsevier, vol. 236(C), pages 196-210.
- Chengshi Tian & Yan Hao, 2018. "A Novel Nonlinear Combined Forecasting System for Short-Term Load Forecasting," Energies, MDPI, vol. 11(4), pages 1-34, March.
- He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2018. "Forecasting exchange rate using Variational Mode Decomposition and entropy theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 15-25.
- Karijadi, Irene & Chou, Shuo-Yan & Dewabharata, Anindhita, 2023. "Wind power forecasting based on hybrid CEEMDAN-EWT deep learning method," Renewable Energy, Elsevier, vol. 218(C).
- He, Kaijian & Liu, Youjin & Yu, Lean & Lai, Kin Keung, 2016. "Multiscale dependence analysis and portfolio risk modeling for precious metal markets," Resources Policy, Elsevier, vol. 50(C), pages 224-233.
- Loi, Tian Sheng Allan & Ng, Jia Le, 2018. "Anticipating electricity prices for future needs – Implications for liberalised retail markets," Applied Energy, Elsevier, vol. 212(C), pages 244-264.
- Afanasyev, Dmitriy O. & Fedorova, Elena A. & Popov, Viktor U., 2015.
"Fine structure of the price–demand relationship in the electricity market: Multi-scale correlation analysis,"
Energy Economics, Elsevier, vol. 51(C), pages 215-226.
See citations under working paper version above.
- Afanasyev, Dmitriy & Fedorova, Elena & Popov, Viktor, 2014. "Fine structure of the price-demand relationship in the electricity market: multi-scale correlation analysis," MPRA Paper 58827, University Library of Munich, Germany.
More information
Research fields, statistics, top rankings, if available.Statistics
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NEP Fields
NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 2 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.- NEP-CIS: Confederation of Independent States (2) 2014-11-17 2015-03-05
- NEP-ENE: Energy Economics (2) 2014-11-17 2015-03-05
- NEP-TRA: Transition Economics (2) 2014-11-17 2015-03-05
- NEP-MFD: Microfinance (1) 2015-03-05
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