Structural learning with time-varying components : tracking the cross-section of financial time series

@inproceedings{Talih2005StructuralLW,
  title={Structural learning with time-varying components : tracking the cross-section of financial time series},
  author={Makram Talih},
  year={2005}
}
When modelling multivariate financial data, the problem of structural learning is compounded by the fact that the covariance structure changes with time. Previous work has focused on modelling those changes by using multivariate stochastic volatility models. We present an alternative to these models that focuses instead on the latent graphical structure that is related to the precision matrix. We develop a graphical model for sequences of Gaussian random vectors when changes in the underlying… CONTINUE READING
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