IDEAS home Printed from
   My bibliography  Save this paper

Volatility Reprojection and Forecasting Performance -- An EMM Approach toward the Multivariate Stochastic Volatility Model


  • George J. Jiang and Pieter J. van der Sluis


While the conditional volatility of time series is always dependent of the model specification, the {\\em ex post} or realized volatility series is often constructed on a model-free basis. The common proxies of daily volatility in the literature are the squared daily asset returns and the sum of squared intra-daily asset returns. In this paper, we propose to construct the underlying volatility series in a multivariate stochastic volatility (SV) model framework using the reprojection technique proposed by Gallant and Tauchen (1998). The reprojected underlying volatility series is obtained via a two-step procedure: in the first step the efficient method of moment (EMM) proposed by Gallant and Tauchen (1996) is employed to estimate the multivariate SV model of asset returns, and in the second step the underlying volatility reprojection technique is applied to the estimated multivariate SV model. The reprojected volatility series, a representation for unobservables in terms of observables, is consistent with the model specification and at the same time advantageous in volatility forecasting. While unavailability is among many issues realted to the use of intra-daily high-frequency asset returns, we show analytically that the squared daily asset return residuals as proxy of \\emph{ex-post} volatility directly leads to extremely low explanatory power in the common regression analysis of volatility forecasting. However, the performance of volatility forecasting based on reprojected volatility series is substantially improved. We also illustrate that the volatility forecasting performance based on multivariate SV model further improves over that based the univariate SV models due to the correlated movements of asset return volatility.

Suggested Citation

  • George J. Jiang and Pieter J. van der Sluis, 2001. "Volatility Reprojection and Forecasting Performance -- An EMM Approach toward the Multivariate Stochastic Volatility Model," Computing in Economics and Finance 2001 16, Society for Computational Economics.
  • Handle: RePEc:sce:scecf1:16

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item


    Stochastic Volatility; Efficient Method of Moments (EMM); Volatility Reprojection; Volatility Forecasting.;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing


    Access and download statistics


    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:sce:scecf1:16. 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: (Christopher F. Baum). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.