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

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Author Info

  • Erie Febrian

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

  • Aldrin Herwany

    ()
    (Research Division, Laboratory of Management FE UNPAD)

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    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.

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    File URL: http://lp3e.fe.unpad.ac.id/wopeds/200908.pdf
    File Function: First version, 2009
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    Bibliographic Info

    Paper provided by Department of Economics, Padjadjaran University in its series Working Papers in Economics and Development Studies (WoPEDS) with number 200908.

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    Length: 17 pages
    Date of creation: Sep 2009
    Date of revision: Sep 2009
    Handle: RePEc:unp:wpaper:200908

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    Keywords: Forecasting; Volatility Model; Risk and Return;

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    1. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
    2. Aggarwal, Reena & Inclan, Carla & Leal, Ricardo, 1999. "Volatility in Emerging Stock Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(01), pages 33-55, March.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
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