IDEAS home Printed from https://ideas.repec.org/p/unp/wpaper/200908.html
   My bibliography  Save this paper

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, 2009. "Forecasting Stocks of Government Owned Companies (GOCS):Volatility Modeling," Working Papers in Economics and Development Studies (WoPEDS) 200908, Department of Economics, Padjadjaran University, revised Sep 2009.
  • Handle: RePEc:unp:wpaper:200908
    as

    Download full text from publisher

    File URL: http://ceds.feb.unpad.ac.id/wopeds/200908.pdf
    File Function: First version, 2009
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    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. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Forecasting; Volatility Model; Risk and Return;

    JEL classification:

    • G0 - Financial Economics - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:unp:wpaper:200908. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Arief Anshory Yusuf). General contact details of provider: http://edirc.repec.org/data/lppadid.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.