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Volatility timing and portfolio selection: How best to forecast volatility

Author

Listed:
  • Adam E Clements

    (QUT)

  • Annastiina Silvennoinen

    (QUT)

Abstract
Within the context of volatility timing and portfolio selection this paper considers how best to estimate a volatility model. Two issues are dealt with, namely the frequency of data used to construct volatility estimates, and the loss function used to estimate the parameters of a volatility model. We find support for the use of intraday data for estimating volatility which is consistent with earlier research. We also find that the choice of loss function is important and show that a simple mean squared error loss, overall provides the best forecasts of volatility upon which to form optimal portfolios.

Suggested Citation

  • Adam E Clements & Annastiina Silvennoinen, 2011. "Volatility timing and portfolio selection: How best to forecast volatility," NCER Working Paper Series 76, National Centre for Econometric Research.
  • Handle: RePEc:qut:auncer:2011_7
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    File URL: http://www.ncer.edu.au/papers/documents/WPNo76.pdf
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    More about this item

    Keywords

    Volatility; volatility timing; utility; portfolio allocation; realized volatility;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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