Oil price future regarding unconventional oil production and its near-term deployment: A system dynamics approach
Author
Abstract
Suggested Citation
DOI: 10.1016/j.energy.2021.119878
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.References listed on IDEAS
- Bekiros, Stelios & Gupta, Rangan & Paccagnini, Alessia, 2015.
"Oil price forecastability and economic uncertainty,"
Economics Letters, Elsevier, vol. 132(C), pages 125-128.
- Stelios D. Bekiros & Rangan Gupta & Alessia Paccagnini, 2015. "Oil price forecastability and economic uncertainty," Open Access publications 10197/7345, School of Economics, University College Dublin.
- Stelios Bekiros & Rangan Gupta & Alessia Paccagnini, 2015. "Oil Price Forecastability and Economic Uncertainty," Working Papers 201518, University of Pretoria, Department of Economics.
- Stelios Bekiros & Rangan Gupta & Alessia Paccagnini, 2015. "Oil Price Forecastability and Economic Uncertainty," Working Papers 298, University of Milano-Bicocca, Department of Economics, revised Apr 2015.
- Dongkuan Xu & Tianjia Chen & Wei Xu, 2015. "A support vector machine-based ensemble prediction for crude oil price with VECM and STEPMRS," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 38(1/2/3), pages 18-48.
- Yu, Lean & Wang, Zishu & Tang, Ling, 2015. "A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting," Applied Energy, Elsevier, vol. 156(C), pages 251-267.
- Jiang Wu & Yu Chen & Tengfei Zhou & Taiyong Li, 2019. "An Adaptive Hybrid Learning Paradigm Integrating CEEMD, ARIMA and SBL for Crude Oil Price Forecasting," Energies, MDPI, vol. 12(7), pages 1-23, April.
- Farzanegan, Mohammad Reza & Raeisian Parvari, Mozhgan, 2014.
"Iranian-Oil-Free Zone and international oil prices,"
Energy Economics, Elsevier, vol. 45(C), pages 364-372.
- Mohammad Reza Farzanegan & Mozhgan Raeisian Parvari, 2014. "Iranian-Oil-Free Zone and International Oil Prices," MAGKS Papers on Economics 201427, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
- E, Jianwei & Bao, Yanling & Ye, Jimin, 2017. "Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 412-427.
- Safari, Ali & Davallou, Maryam, 2018. "Oil price forecasting using a hybrid model," Energy, Elsevier, vol. 148(C), pages 49-58.
- Murat, Atilim & Tokat, Ekin, 2009. "Forecasting oil price movements with crack spread futures," Energy Economics, Elsevier, vol. 31(1), pages 85-90, January.
- Wang, Minggang & Zhao, Longfeng & Du, Ruijin & Wang, Chao & Chen, Lin & Tian, Lixin & Eugene Stanley, H., 2018. "A novel hybrid method of forecasting crude oil prices using complex network science and artificial intelligence algorithms," Applied Energy, Elsevier, vol. 220(C), pages 480-495.
- Hosseini, Seyed Hossein & Shakouri G., Hamed, 2016. "A study on the future of unconventional oil development under different oil price scenarios: A system dynamics approach," Energy Policy, Elsevier, vol. 91(C), pages 64-74.
- Qudrat-Ullah, Hassan & Seong, Baek Seo, 2010. "How to do structural validity of a system dynamics type simulation model: The case of an energy policy model," Energy Policy, Elsevier, vol. 38(5), pages 2216-2224, May.
- Sepehr Ramyar & Farhad Kianfar, 2019. "Forecasting Crude Oil Prices: A Comparison Between Artificial Neural Networks and Vector Autoregressive Models," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 743-761, February.
- Zhang, Jin-Liang & Zhang, Yue-Jun & Zhang, Lu, 2015. "A novel hybrid method for crude oil price forecasting," Energy Economics, Elsevier, vol. 49(C), pages 649-659.
- Taiyong Li & Min Zhou & Chaoqi Guo & Min Luo & Jiang Wu & Fan Pan & Quanyi Tao & Ting He, 2016. "Forecasting Crude Oil Price Using EEMD and RVM with Adaptive PSO-Based Kernels," Energies, MDPI, vol. 9(12), pages 1-21, December.
- Ani Shabri & Ruhaidah Samsudin, 2014. "Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-10, July.
- Chai, Jian & Guo, Ju-E. & Meng, Lei & Wang, Shou-Yang, 2011. "Exploring the core factors and its dynamic effects on oil price: An application on path analysis and BVAR-TVP model," Energy Policy, Elsevier, vol. 39(12), pages 8022-8036.
- Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2013.
"Forecasting the Price of Oil,"
Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 427-507,
Elsevier.
- Ron Alquist & Lutz Kilian & Robert J. Vigfusson, 2011. "Forecasting the price of oil," International Finance Discussion Papers 1022, Board of Governors of the Federal Reserve System (U.S.).
- Kilian, Lutz & Alquist, Ron & Vigfusson, Robert J., 2011. "Forecasting the Price of Oil," CEPR Discussion Papers 8388, Centre for Economic Policy Research.
- Ron Alquist & Lutz Kilian & Robert Vigfusson, 2011. "Forecasting the Price of Oil," Staff Working Papers 11-15, Bank of Canada.
- Nademi, Arash & Nademi, Younes, 2018. "Forecasting crude oil prices by a semiparametric Markov switching model: OPEC, WTI, and Brent cases," Energy Economics, Elsevier, vol. 74(C), pages 757-766.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Li, Xuemei & Liu, Xiaoxing, 2023. "Functional classification and dynamic prediction of cumulative intraday returns in crude oil futures," Energy, Elsevier, vol. 284(C).
- Hendalianpour, Ayad & Liu, Peide & Amirghodsi, Sirous & Hamzehlou, Mohammad, 2022. "Designing a System Dynamics model to simulate criteria affecting oil and gas development contracts," Resources Policy, Elsevier, vol. 78(C).
- Ren, Xiaohang & Li, Yiying & Qi, Yinshu & Duan, Kun, 2022. "Asymmetric effects of decomposed oil-price shocks on the EU carbon market dynamics," Energy, Elsevier, vol. 254(PB).
- Mazen Hafez & Mahyar Ghazvini & Myeongsub Kim, 2022. "On the Stability of Particle–Particle Interaction during Gravitational Settling," Energies, MDPI, vol. 15(22), pages 1-14, November.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Li, Jinchao & Zhu, Shaowen & Wu, Qianqian, 2019. "Monthly crude oil spot price forecasting using variational mode decomposition," Energy Economics, Elsevier, vol. 83(C), pages 240-253.
- Piersanti, Giovanni & Piersanti, Mirko & Cicone, Antonio & Canofari, Paolo & Di Domizio, Marco, 2020. "An inquiry into the structure and dynamics of crude oil price using the fast iterative filtering algorithm," Energy Economics, Elsevier, vol. 92(C).
- Bekiroglu, Korkut & Duru, Okan & Gulay, Emrah & Su, Rong & Lagoa, Constantino, 2018. "Predictive analytics of crude oil prices by utilizing the intelligent model search engine," Applied Energy, Elsevier, vol. 228(C), pages 2387-2397.
- Li, Xuemei & Liu, Xiaoxing, 2023. "Functional classification and dynamic prediction of cumulative intraday returns in crude oil futures," Energy, Elsevier, vol. 284(C).
- Abdollahi, Hooman & Ebrahimi, Seyed Babak, 2020. "A new hybrid model for forecasting Brent crude oil price," Energy, Elsevier, vol. 200(C).
- Taiyong Li & Yingrui Zhou & Xinsheng Li & Jiang Wu & Ting He, 2019. "Forecasting Daily Crude Oil Prices Using Improved CEEMDAN and Ridge Regression-Based Predictors," Energies, MDPI, vol. 12(19), pages 1-25, September.
- Zhao, Yuan & Zhang, Weiguo & Gong, Xue & Wang, Chao, 2021. "A novel method for online real-time forecasting of crude oil price," Applied Energy, Elsevier, vol. 303(C).
- Yu, Hongchu & Fang, Zhixiang & Lu, Feng & Murray, Alan T. & Zhang, Hengcai & Peng, Peng & Mei, Qiang & Chen, Jinhai, 2019. "Impact of oil price fluctuations on tanker maritime network structure and traffic flow changes," Applied Energy, Elsevier, vol. 237(C), pages 390-403.
- Abdollahi, Hooman, 2020. "A novel hybrid model for forecasting crude oil price based on time series decomposition," Applied Energy, Elsevier, vol. 267(C).
- Arash Sioofy Khoojine & Mahboubeh Shadabfar & Yousef Edrisi Tabriz, 2022. "A Mutual Information-Based Network Autoregressive Model for Crude Oil Price Forecasting Using Open-High-Low-Close Prices," Mathematics, MDPI, vol. 10(17), pages 1-20, September.
- Manickavasagam, Jeevananthan & Visalakshmi, S. & Apergis, Nicholas, 2020. "A novel hybrid approach to forecast crude oil futures using intraday data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
- Guo, Jingjun & Zhao, Zhengling & Sun, Jingyun & Sun, Shaolong, 2022. "Multi-perspective crude oil price forecasting with a new decomposition-ensemble framework," Resources Policy, Elsevier, vol. 77(C).
- Radosław Puka & Bartosz Łamasz, 2020. "Using Artificial Neural Networks to Find Buy Signals for WTI Crude Oil Call Options," Energies, MDPI, vol. 13(17), pages 1-20, August.
- Chen, Haixin & Liu, Yancheng & Li, Xiangjie & Gu, Xiang & Fan, Kun, 2024. "Oil market regulatory: An ensembled model for prediction," Finance Research Letters, Elsevier, vol. 67(PA).
- Karasu, Seçkin & Altan, Aytaç, 2022. "Crude oil time series prediction model based on LSTM network with chaotic Henry gas solubility optimization," Energy, Elsevier, vol. 242(C).
- He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
- Nicholas Apergis, 2023. "Forecasting energy prices: Quantile‐based risk models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 17-33, January.
- Han, Liyan & Lv, Qiuna & Yin, Libo, 2017. "Can investor attention predict oil prices?," Energy Economics, Elsevier, vol. 66(C), pages 547-558.
- Akdoğan, Kurmaş, 2020. "Fundamentals versus speculation in oil market: The role of asymmetries in price adjustment?," Resources Policy, Elsevier, vol. 67(C).
- Zied Ftiti & Kais Tissaoui & Sahbi Boubaker, 2022. "On the relationship between oil and gas markets: a new forecasting framework based on a machine learning approach," Annals of Operations Research, Springer, vol. 313(2), pages 915-943, June.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:222:y:2021:i:c:s0360544221001274. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/a/eee/energy/v222y2021ics0360544221001274.html