1. Abasi Nami H (2021). Forecasting Crude Oil Prices Volatility and Value at Risk: Single and Switching Regime GARCH Models, Quarterly Energy Economics Review, 17 (68): 141-174 (In Persian)
2. Abrishami, H. Behradmehr, N. & seifi, T (2013). Forecasting of Crude Oil Price by Using Wavelet Transform, Non-Linear and Linear Models, Quarterly Journal of Applied Economics Studiesin Iran, 2(7): 41-62 (In Persian)
3. Abunoori, AA & khodadad, N (2012). Comparing the performance of ARIMA regression models and neural network with genetic algorithm (GMDH) in predicting the price of crude oil in Iran, Journal of Financial Engineering and Securities Management, 3(11): 43-62 (In Persian)
4. Ayazi, A. Amiri, M. Fartukzadeh, HR & Azar, A (2020). Strategic analysis of international oil market suppliers based on graph model, Scientific quarterly of interdisciplinary studies on strategic knowledge, 10(39): 179-206 (In Persian)
5. Baumeister, Christiane. & Lutz, Kilian. (2016). Forty Years of Oil Price Fluctuations: Why the Price of Oil May Still Surprise Us. Translated by Mehrdad Rahmani and Ali Faridzad (2019). Trend Quarterly, 25 (83,84):131-168 (In Persian) [
DOI:10.2139/ssrn.2734052]
6. Bordbar N, Heidari E (2017). The Effect of World Oil Price Fluctuations on the Return of the Energy Intensive Industries Stock in Iran, Journal of Economic Modeling Research, 8 (27):177-205 (In Persian) [
DOI:10.29252/jemr.7.27.177]
7. Deng, C. Ma, L & Zeng, T (2021). Crude Oil Price Forecast Based on Deep Transfer Learning: Shanghai Crude Oil as an Example, MDPI, 13(24): 1-13. [
DOI:10.3390/su132413770]
8. Ebrahimi, M. Hajimirzayi, MA. & Mohammadkhani, S (2011). Estimating Iran's crude oil supply pattern, Quarterly Energy Economics Review, 8(29): 113-137 (In Persian)
9. Emami meibodi A, memarzadeh A, amadeh H, ghasemi nejad A (2013). Comparing the performance of GARCH model and gravitational search algorithm (GSA) in modeling and forecasting of spot oil price of Iran, Journal of Economic Modeling Research, 4 (14):1-23 (In Persian)
10. Gojarati, D (1991). Basics of econometrics, Translated by Abrishami H (2008), Tehran: Tehran University Publications, The second volume
11. Gupta, N & Nigam, Sh (2020). Crude Oil Price Prediction using Artificial Neural Network, Procedia Computer Science, 170: 642-647 [
DOI:10.1016/j.procs.2020.03.136]
12. Hajikaram, E & darabi, R (2017). Brent Crude Oil Daily Price Forecast by Combining Principal Components Analysis and Support Vector Regression methods, Iranian Energy Economics Research; 7(25):41-60 (In Persian)
13. HajiLari Semnani, B & Khalili, S (2018). Estimation of OPEC crude oil price using binomial tree, time series and artificial neural networks, Journal of Mineral Resources Engineering,3(3): 31-41 (In Persian)
14. Jammazi, R. & Aloui, C (2012). Crude Oil Price Forecasting: Experimental Evidence from Wavelet Decomposition and Neural Network Modeling, Energy Economics, 34(3):828-841 [
DOI:10.1016/j.eneco.2011.07.018]
15. Li, X. He, K. Lai, K & Zou Y (2014). Forecasting Crude Oil Price With Multiscale Denoising Ensemble Model, Mathematic Problems in Engineering, (4): 1-9. [
DOI:10.1155/2014/716571]
16. Menhaj, MB (1998). Basics of neural networks (computational intelligence), Tehran: Publication of Dr Hesabi (In Persian)
17. Mohammadi, H. & Lixian, Su (2010). International Evidence on Crude Oil Price Dynamics: Applications of ARIMA-GARCH Models, Energy Economics, 32(5): 1001-1008. [
DOI:10.1016/j.eneco.2010.04.009]
18. Runfang, Y., Jiangze, D., Xiaoto, L. (2019). Improved Forecast Ability of Oil Market Volatility Based on combined Markov Switching and GARCHclass Model, Procedia Computer Science, 122: 415-422. [
DOI:10.1016/j.procs.2017.11.388]
19. Souri, A (2017). Econometrics (Volume 1), Tehran: Cultural publication, Sixth edition (In Persian)
20. Sadeghi, H. Zolfaghari, M & Elhaminezhd, M (2011). Comparison of Neural Networks and ARIMA in Modeling and Forecasting of Short Run Pricing of the OPEC Crude Oil Basket (With Focus on Comparative Expectations), Quarterly Energy Economics Review, 8(28): 25-47 (In Persian)
21. Takroosta A, Mohajeri P, Mohammadi T, Shakeri A, Ghasemi A (2019). An Analysis of Oil Prices Considering the Political Risk of OPEC, Journal of Economic Modeling Research; 10 (37):105-138 (In Persian) [
DOI:10.29252/jemr.10.37.105]
22. Wang, M. Tian, L. & Zhou, P (2018). A novel approach for oil price forecasting based on data fluctuation network, Energy Economic, 71:201-212 [
DOI:10.1016/j.eneco.2018.02.021]
23. Yadegari H, Mohammadi T, Amadeh H, Qasemi A, Mostafaei H (2022). Brent crude oil Price Forecast with Hybrid Model of Nonlinear Grey Model and Linear Arima Waste Correction, Quarterly Energy Economics Review, 18(72): 1-25 (In Persian)
24. Yu Lean, Dai Wei, Tang Ling (2016). A novel decomposition ensemble model with extended extreme learning machine for crude oil price forecasting. Engineering Applications of Artificial Intelligence, , 47: 110-121 [
DOI:10.1016/j.engappai.2015.04.016]
25. Zhang, Y., Yao, T., He, L., Ripple, R. (2019). Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models, International Review of Economics & Finance, 59: 302- 317. [
DOI:10.1016/j.iref.2018.09.006]
26. Zhang, K & Hong, M (2022). Forecasting crude oil price using LSTM neural networks, Data Science in Finance and Economics, 2(3):163-180. [
DOI:10.3934/DSFE.2022008]
27. Zou, Yingchao & Chen, Yanhui (2016). Multi-step-ahead Crude Oil Price Forecasting based on Grey Wave Forecasting Method, Procedia Computer Science, 91:1050 - 1056. [
DOI:10.1016/j.procs.2016.07.147]