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Multivariate Realized Stock Market Volatility

  • Gregory H. Bauer
  • Keith Vorkink

We present a new matrix-logarithm model of the realized covariance matrix of stock returns. The model uses latent factors which are functions of both lagged volatility and returns. The model has several advantages: it is parsimonious; it does not require imposing parameter restrictions; and, it results in a positive-definite covariance matrix. We apply the model to the covariance matrix of size-sorted stock returns and find that two factors are sufficient to capture most of the dynamics. We also introduce a new method to track an index using our model of the realized volatility covariance matrix.

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Paper provided by Bank of Canada in its series Working Papers with number 07-20.

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Length: 62 pages
Date of creation: 2007
Date of revision:
Handle: RePEc:bca:bocawp:07-20
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