English, Article, Journal or magazine article edition: A nonparametric approach to forecasting realized volatility Adam Clements; Ralf Becker

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Bookmark: http://trove.nla.gov.au/version/147785
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • A nonparametric approach to forecasting realized volatility
Author
  • Adam Clements
  • Ralf Becker
Physical Description
  • preprint
Notes
  • A well developed literature exists in relation to modeling and forecasting asset return volatility. Much of this relate to the development of time series models of volatility. This paper proposes an alternative method for forecasting volatility that does not involve such a model. Under this approach a forecast is a weighted average of historical volatility. The greatest weight is given to periods that exhibit the most similar market conditions to the time at which the forecast is being formed. Weighting occurs by comparing short-term trends in volatility across time (as a measure of market conditions) by the application of a multivariate kernel scheme. It is found that at a 1 day forecast horizon, the proposed method produces forecasts that are significantly more accurate than competing approaches.
  • Volatility, forecasts, forecast evaluation, model confidence set, nonparametric
  • RePEc:qut:auncer:2009_56
Language
  • English
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