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Forecasting Stocks of Government Owned Companies (GOCS):Volatility Modeling

Author

Listed:
  • Erie Febrian

    (Finance & Risk Management Study Group (FRMSG) FE UNPAD)

  • Aldrin Herwany

    (Research Division, Laboratory of Management FE UNPAD)

Abstract

The development in forecasting techniques has been quite significant, which is indicated by the evolution on how researchers perceive characteristics of financial data. The researchers used to employ mean in their prediction model, but nowadays they tend to employ variance in developing the model. In addition, they also move from the static approaches (e.g., Autoregreesive (AR), Moving Average (MA), ARMA and ARIMA) to the dynamic ones (especially estimation model employing volatility change that just won Nobel prize in 2004). In this research, we try to develop the best prediction model by using volatility model, such as ARCH, GARCH, TARCH and EGARCH, and employing listed stocks of government-owned companies (GOCs) as the sample. The result proves that the employed volatility model and its derivatives are fairly accurate in predicting fluctuation of GOCs stock prices, which are reflected by the associated returns. In addition, the resulted model is capable to measure risk of the observed stock, as well as appropriate price of an asset.

Suggested Citation

  • Erie Febrian & Aldrin Herwany, 2010. "Forecasting Stocks of Government Owned Companies (GOCS):Volatility Modeling," Working Papers in Business, Management and Finance 201002, Department of Management and Business, Padjadjaran University, revised Feb 2010.
    • Handle: RePEc:unp:wpaman:201002
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    References listed on IDEAS

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    3. Torben G. Andersen & Tim Bollerslev & Peter Christoffersen & Francis X. Diebold, 2007. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Chapters, in: The Risks of Financial Institutions, pages 513-544, National Bureau of Economic Research, Inc.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
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    More about this item

    Keywords

    Forecasting; Volatility Model; Risk and Return;
    All these keywords.

    JEL classification:

    • G0 - Financial Economics - - General

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