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Modelling and forecasting monthly Brent crude oil prices: a long memory and volatility approach. (2021). Ismail, Mohd Tahir ; Algounmeein, Remal Shaher.
In: Statistics in Transition New Series.
RePEc:exl:29stat:v:22:y:2021:i:1:p:29-54.

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  1. AAMIR, M., SHABRI, A. B., (2015). Modelling and Forecasting Monthly Crude Oil Prices of Pakistan: A Comparative Study of ARIMA, GARCH and ARIMAGARCH Models. Sci.Int. (Lahore), 27(3), pp. 2365−2371.
    Paper not yet in RePEc: Add citation now
  2. AKRON, N., ISMAIL, Z., (2017). A hybrid GA-FEEMD for forecasting crude oil prices. Indian Journal of Science and Technology, 10(31), pp. 1−6.
    Paper not yet in RePEc: Add citation now
  3. AKTER, N., NOBI, A., (2018). Investigation of the Financial Stability of S&P 500 Using Realized Volatility and Stock Returns Distribution. Journal of Risk Financial Management, 11(22), pp. 1−10.

  4. AL-GOUNMEEIN, R. S., ISMAIL, M. T., (2020). Forecasting the Exchange Rate of the Jordanian Dinar versus the US Dollar Using a Box-Jenkins Seasonal ARIMA Model. International Journal of Mathematics and Computer Science, 15(1), pp. 27−40.
    Paper not yet in RePEc: Add citation now
  5. ALZGHOOL, R., (2017). Parameters estimation for GARCH (p,q) model: QL and AQL approaches. Electronic Journal of Applied Statistical Analysis, 10(1), pp.180−193.
    Paper not yet in RePEc: Add citation now
  6. AMBACH, D., AMBACH, O., (2018). Forecasting the oil price with a periodic regression ARFIMA-GARCH process. IEEE Second International Conference on Data Stream Mining & Processing, Lviv, Ukraine, pp. 212−217.
    Paper not yet in RePEc: Add citation now
  7. AUE, A., HORVATH, L. and PELLATT, D. F., (2017). Functional generalized autoregressive conditional heteroskedasticity. Journal of Time Series Analysis, 38(1), pp. 3−21.

  8. BAHAR, A., NOH, N. M. and ZAINUDDIN, Z. M., (2017). Forecasting model for crude oil price with structural break. Malaysian Journal of Fundamental and Applied Sciences, pp. 421−424.
    Paper not yet in RePEc: Add citation now
  9. BERAN, J., (1994). Statistics for Long Memory Processes, Chapman and Hall, p. 315.
    Paper not yet in RePEc: Add citation now
  10. BHARDWAJ, G., SWANSON, N. R., (2006). An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series. Journal of Econometrics 131, pp. 539−578.

  11. BOX, G. E. P., JENKINS, G. M. and REINSEL, G. C., (2008). Time series analysis forecasting and control, Fourth Edition, Wiley & Sons, Inc, p. 746.
    Paper not yet in RePEc: Add citation now
  12. CRYER, J. D., CHAN, K., (2008). Time Series Analysis With Application in R, Second Edition, Springer, p. 491.
    Paper not yet in RePEc: Add citation now
  13. DIEBOLD, F. X., INOUE, A., (2001). Long Memory and Regime Switching. Journal of Econometrics, 105, pp. 131−159.

  14. FAZELABDOLABADI, B., (2019). A hybrid Bayesian-network proposition for forecasting the crude oil price. Financial Innovation, 5(30), pp. 1−21.

  15. FRANCQ, C., ZAKOIAN, J. M., (2019). GARCH Models: Structure, Statistical Inference and Financial Applications, Second Edition, John Wiley & Sons Ltd, p. 487.
    Paper not yet in RePEc: Add citation now
  16. GRANGER, C. W. J., HYUNG, N., (2004). Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns. Journal of Empirical Finance, 11, pp. 399−421.

  17. HE, X. J., (2018). Crude Oil Prices Forecasting: Time Series vs. SVR Models. Journal of International Technology and Information Management, 27(2), pp. 25−42.
    Paper not yet in RePEc: Add citation now
  18. IQELAN, B. M., (2015). Time Series Modeling of Monthly Temperature Data of Jerusalem / Palestine. MATEMATIKA, 31(2), pp. 159−176.
    Paper not yet in RePEc: Add citation now
  19. ISMAIL, M. T., AWAJAN, A. M., (2017). A new hybrid approach EMD-EXP for shortterm forecasting of daily stock market time series data. Electronic Journal of Applied Statistical Analysis, 10(2), pp. 307−327.
    Paper not yet in RePEc: Add citation now
  20. JIBRIN, S. A., MUSA, Y., ZUBAIR, U. A. and SAIDU, A. S., (2015). ARFIMA Modelling and Investigation of Structural Break(s) in West Texas Intermediate and Brent Series, CBN Journal of Applied Statistics, 6(2), pp. 59−79.
    Paper not yet in RePEc: Add citation now
  21. KANG, S. H., YOON, S., (2013). Modeling and forecasting the volatility of petroleum futures prices. Energy Economics, 36, pp. 354−362.

  22. KARIA, A. A., BUJANG, I. and AHMAD, I., (2013). Fractionally integrated ARMA for crude palm oil prices prediction: case of potentially over difference. Journal of Applied Statistics, 40(12), pp. 2735−2748.

  23. LO, A. W., (1991). Long-term memory in stock market prices. Econometrica, 59(5), pp. 1279−1313.

  24. MANDELBROT, B., (1972). Statistical Methodology for Nonperiodic Cycles: From the Covariance to R/S Analysis. Annals of Economic and Social Measurement, 1(3), pp. 259−290.

  25. MANERA, M., MCALEER, M. and GRASSO, M., (2004). Modelling dynamic conditional correlations in the volatility of spot and forward oil price returns, 2nd International Congress on Environmental Modelling and Software - Osnabrück, Germany, 183, pp. 1−6.

  26. MIAH, M., RAHMAN, A., (2016). Modelling Volatility of Daily Stock Returns: Is GARCH(1,1) Enough?. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS), 18(1), pp. 29−39.
    Paper not yet in RePEc: Add citation now
  27. MONTGOMERY, D. C., JENNINGS, C. L. and KULAHCI, M., (2015). Introduction To Time Series Analysis And Forecasting, Second Edition, Wiley & Sons, Inc, p. 643.
    Paper not yet in RePEc: Add citation now
  28. MOSTAFAEI, H., SAKHABAKHSH, L., (2012). Using SARFIMA Model to Study and Predict the Iran’s Oil Supply. International Journal of Energy Economics and Policy, 2(1), pp. 41−49.

  29. NYANGARIKA, A., MIKHAYLOV, A. and RICHTER, U. H., (2019). Oil Price Factors: Forecasting on the Base of Modified Auto-regressive Integrated Moving Average Model. International Journal of Energy Economics and Policy, 9(1), pp. 149−159.

  30. OHANISSIAN, A., RUSSELL, J. R. and TSAY, R. S., (2008). True or Spurious Long Memory? A New Test. Journal of Business & Economic Statistics, 26(2), pp. 161−175.

  31. OLATAYO, T. O., ADEDOTUN, A. F., (2014). On the Test and Estimation of Fractional Parameter in ARFIMA Model: Bootstrap Approach. Applied Mathematical Sciences, 8(96), pp.4783−4792.
    Paper not yet in RePEc: Add citation now
  32. PALMA, W., (2007). Long-Memory Time Series: Theory and Methods, John Wiley & Sons, Inc, p. 285.
    Paper not yet in RePEc: Add citation now
  33. R. S. Al-Gounmeein, M. T. Ismail: Modelling and forecasting monthly… BOUTAHAR, M., MARIMOUTOU, V. and NOUIRA, L., (2007). Estimation Methods of the Long Memory Parameter: Monte Carlo Analysis and Application. Journal of Applied Statistics, 34(3), pp. 261−301.
    Paper not yet in RePEc: Add citation now
  34. R. S. Al-Gounmeein, M. T. Ismail: Modelling and forecasting monthly… PRETIS, F., SCHNEIDER, L., SMERDON, J. E. and HENDRY, D. F., (2016). Detecting volcanic eruptions in temperature reconstructions by designed break-indicator saturation. Journal of Economic Surveys, 30(3), pp. 403−429.

  35. RAMZAN, S., RAMZAN, S. and ZAHID, F. M., (2012). Modeling and Forecasting Exchange Rate Dynamics In Pakistan Using ARCH Family of Models. Electronic Journal of Applied Statistical Analysis, 5(1), pp. 15−29.
    Paper not yet in RePEc: Add citation now
  36. REISEN, V. A., (1994). Estimation of the Fractional Difference Parameter in the ARIMA(p,d,q) Model Using the Smoothed Periodogram. Journal of Time Series Analysis, 15(3), pp. 335−350.

  37. SEHGAL, N., PANDEY, K. K., (2015). Artificial intelligence methods for oil price forecasting: a review and evaluation, Springer-Verlag Berlin Heidelberg, DOI: 10.1007/s12667-015-0151-y.
    Paper not yet in RePEc: Add citation now
  38. STATISTICS IN TRANSITION new series, March 2021 53 LEE, C. Y., HUH, S. Y., (2017). Forecasting Long-Term Crude Oil Prices Using a Bayesian Model with Informative Priors. Sustainability. 9, 190, DOI: 10.3390/su9020190.

  39. TELBANY, S., SOUS, M., (2016). Using ARFIMA Models in Forecasting Indicator of the Food and Agriculture Organization. IUGJEBS, 24(1), pp. 168−187.
    Paper not yet in RePEc: Add citation now
  40. TENDAI, M., CHIKOBVU, D., (2017). Modelling international tourist arrivals and volatility to the Victoria Falls Rainforest, Zimbabwe: Application of the GARCH family of models. African Journal of Hospitality, Tourism and Leisure, 6(4), pp. 1−16.
    Paper not yet in RePEc: Add citation now
  41. YIN, X., PENG, J. and TANG, T., (2018). Improving the Forecasting Accuracy of Crude Oil Prices. Sustainability. 10, 454, DOI: 10.3390/su10020454.

  42. YU, L., WANG, S. and LAI, K. K., (2008). Forecasting crude oil price with an EMDbased neural network ensemble learning paradigm. Energy Economics, 30, pp. 2623−2635.

  43. YU, L., ZHANG, X. and WANG, S., (2017). Assessing Potentiality of Support Vector Machine Method in Crude Oil Price Forecasting. EURASIA Journal of Mathematics, Science and Technology Education, 13(12), pp. 7893-7904.
    Paper not yet in RePEc: Add citation now

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