مدل‌سازی قیمت روزانه نفت‌خام اوپک با استخراج رفتار غیرخطی نمایی واریانس از حافظه بلندمدت

Alvarez-Ramirez, J. and Alvarez, J. and Rodriguez, E (2008). Short-term predictability of crude oil markets: a detrended fluctuation analysis approach. Energy Economics, Vol. 30(5), pp. 2645-2656.

Alvarez-Ramirez, J. and Cisneros, M. and Ibarra-Valdez, C. and Soriano, A. (2002). Multifractal Hurst analysis of crude oil prices. Physica A: Statistical Mechanics and its Applications, Vol. 313(3-4), pp. 651-670.

Baillie, R. and Chung, C. and Tieslau, M. (1996). Analyzing inflation by the fractionally integrated ARFIMA-GARCH model. Journal of Applied Econometrics, Vol. 11, pp. 23-40.

Barsky, R. B. and Kilian, L. (2001). Do we really know that oil caused the great stagflation? A monetary alternative. NBER Macroeconomics annual, Vol. 16, pp. 137-183.

Bernanke, B. S. and Gertler, M. and Watson, M. and Sims, C. A. and Friedman, B. M. (1997). Systematic monetary policy and the effects of oil price shocks. Brookings papers on economic activity, Vol. 1997(1), pp. 91-157.

Bhardwaj, G. and Swanson, N. R. (2006). An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series. Journal of Econometrics, Vol. 131(1-2), pp. 539-578.

Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroscedasticity. Journal of Econometric, Vol. 31(3), pp. 307-327.

Bristone, M., Prasad, R., & Abubakar, A. A. (2020). CPPCNDL: Crude oil price prediction using complex network and deep learning algorithms. Petroleum, 6(4), 353-361.

Chen, Y. and Zou, Y. and Zhou, Y. and Zhang, C. (2016). Multi-step-ahead crude oil price forecasting based on grey wave forecasting method. Procedia Computer Science, Vol. 91, pp. 1050-1056.

Cheung, Y. W. and Diebold, F. X. (1994). On maximum likelihood estimation of the differencing parameter of fractionally-integrated noise with unknown mean. Journal of econometrics, Vol. 62(2), pp. 301-316.

Choi, K. and Zivot, E. (2007). Long memory and structural changes in the forward discount: An empirical investigation. Journal of International Money and Finance, Vol. 26(3), pp. 342-363.

Diebold, F. X. and Inoue, A. (2001). Long memory and regime switching. Journal of econometrics, Vol. 105(1), pp. 131-159.

Diebold, F. X. and Rudebusch, G. D. (1989). Long memory and persistence in aggregate output. Journal of monetary economics, Vol. 24(2), pp. 189-209.

Dittmann, I. and Granger, C. W. (2002). Properties of nonlinear transformations of fractionally integrated processes. Journal of Econometrics, Vol. 110(2), pp. 113-133.

Doornik, J. A. and Ooms, M. (2003). Computational aspects of maximum likelihood estimation of autoregressive fractionally integrated moving average models. Computational Statistics and Data Analysis, Vol. 42(3), pp.333-348.

Dowd, K. (2003). An introduction to market risk measurement. John Wiley and Sons.

Elder, J. and Serletis, A. (2008). Long memory in energy futures prices. Review of Financial Economics, Vol. 17(2), pp. 146-155.

Engle, R. F. and Smith, A. D. (1999). Stochastic permanent breaks. Review of Economics and statistics, Vol. 81(4), pp. 553-574.

Erbil, M. N. (2011). Is fiscal policy procyclical in developing oil-producing countries?. International Monetary Fund, (No. 11-171).

Finn, M. G. (2000). Perfect competition and the effects of energy price increases on economic activity. Journal of Money, Credit and banking, Vol (32), 400-416.

Geweke, J. and Porter‐Hudak, S. (1983). The estimation and application of long memory time series models. Journal of time series analysis, Vol. 4(4), pp. 221-238.

Granger, C. W. and Joyeux, R. (1980). An introduction to long‐memory time series models and fractional differencing. Journal of time series analysis, Vol. 1(1), pp. 15-29.

Gupta, N. and Nigam, S. (2020). Crude Oil Price Prediction using Artificial Neural Network. Procedia Computer Science, Vol. 170, pp. 642-647.

Hamilton, J. D. (1994). Time series analysis, Princeton. NJ: Princeton university press, Vol. 2, pp. 690-696.

Hassler, U. and Wolters, J. (1995). Long memory in inflation rates: International evidence. Journal of Business and Economic Statistics, Vol. 13(1), pp. 37-45.

Herrera, A. M. Hu, L. and Pastor, D. (2018). Forecasting crude oil price volatility. International Journal of Forecasting, Vol. 34(4), pp. 622-635.

Hosking, J. R. (1981). Fractional differencing. Biometrika, Vol. 68(1), pp. 165-176.

Hurst, H. E. (1951). Long-term storage capacity of reservoirs. Trans, Amer, Soc, Civil Eng., Vol. 116, pp. 770-799.

Hyung, N., Franses, P. H., & Penm, J. (2006). Structural breaks and long memory in US inflation rates: Do they matter for forecasting? Research in International Business and Finance, 20(1), 95-110.

Kim, I. M. and Loungani, P. (1992). The role of energy in real business cycle models. Journal of Monetary Economics, Vol. 29(2), pp. 173-189.

Kristjanpoller, W. and Minutolo, M. C. (2016). Forecasting volatility of oil price using an artificial neural network-GARCH model. Expert Systems with Applications, Vol. 65, pp. 233-241.

Lo, A. W. (1989). Long-term memory in stock market prices. National Bureau of Economic Research, (No. w2984)

Mandelbrot, B. B. and Wallis, J. R. (1969), Computer experiments with fractional Gaussian noises: Part 1, averages and variances. Water resources research, Vol. 5(1), pp. 228-241.

Obstfeld, M. and Rogoff, K. (1995). Exchange rate dynamics redux. Journal of political economy, Vol. 103(3), pp. 624-660.

Robinson, P. M. (1995). Log-periodogram regression of time series with long range dependence. The annals of Statistics, pp. 1048-1072.

Rotemberg, J. J. and Woodford, M. (1996). Imperfect competition and the effects of energy price increases on economic activity. National Bureau of Economic Research, (No. w5634).

Sowell, F. (1992). Maximum likelihood estimation of stationary univariate fractionally integrated time series models. Journal of econometrics, Vol. 53(1-3), pp. 165-188.

Tsay, W. J. (2008). Analysing inflation by the ARFIMA model with Markov-switching fractional differencing parameter. The Institute of Economics.

Vo, M. (2011). Oil and stock market volatility: A multivariate stochastic volatility perspective. Energy Economics, Vol. 33(5), pp. 956-965.

Wang, Y. Wu, C. and Wei, Y. (2011). Can GARCH-class models capture long memory in WTI crude oil markets?. Economic Modelling, Vol. 28(3), pp. 921-927.

Wei, Y. Wang, Y. and Huang, D. (2010). Forecasting crude oil market volatility: Further evidence using GARCH-class models. Energy Economics, Vol. 32(6), pp. 1477-1484.

Xiu, J. and Jin, Y. (2007). Empirical study of ARFIMA model based on fractional differencing. Physica A: Statistical Mechanics and its Applications, Vol. 377(1), pp. 138-154