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Modelling and Forecasting of Price Volatility: An Application of GARCH and EGARCH Models

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  • Lama, A.
  • Jha, G.K.
  • Paul, R.K.
  • Gurung, B.

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Suggested Citation

  • Lama, A. & Jha, G.K. & Paul, R.K. & Gurung, B., 2015. "Modelling and Forecasting of Price Volatility: An Application of GARCH and EGARCH Models," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 28(1).
    • Handle: RePEc:ags:aerrae:206582
    DOI: 10.22004/ag.econ.206582
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    References listed on IDEAS

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    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. Jordaan, Henry & Grove, Bennie & Jooste, Andre & Alemu, A.G., 2007. "Measuring the Price Volatility of Certain Field Crops in South Africa using the ARCH/GARCH Approach," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 46(3), pages 1-17, September.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    4. Masahito Kobayashi & Xiuhong Shi, 2005. "Testing for EGARCH Against Stochastic Volatility Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(1), pages 135-150, January.
    5. Nelson, Daniel B & Cao, Charles Q, 1992. "Inequality Constraints in the Univariate GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 229-235, April.
    6. M. Karanasos & J. Kim, 2003. "Moments of the ARMA--EGARCH model," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 146-166, June.
    7. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Tirngo Dinku & Gardachew Worku, 2022. "Asymmetric GARCH models on price volatility of agricultural commodities," SN Business & Economics, Springer, vol. 2(11), pages 1-17, November.
    2. Ufuk Beyaztas & Beste H. Beyaztas, 2019. "On Jackknife-After-Bootstrap Method for Dependent Data," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1613-1632, April.
    3. Yu-Min Lian & Jia-Ling Chen & Hsueh-Chien Cheng, 2022. "Predicting Bitcoin Prices via Machine Learning and Time Series Models," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(5), pages 1-2.
    4. Balli, Faruk & de Bruin, Anne & Chowdhury, Md Iftekhar Hasan, 2019. "Spillovers and the determinants in Islamic equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).

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