Preprint

Volatility estimation with functional gradient descent for very high-dimensional financial time series

  • Bühlmann, Peter ETH Zürich, Switzerland
    2002

23

English We propose a functional gradient descent algorithm (FGD) for estimating volatility and conditional covariances (given the past) for very high-dimensional financial time series of asset price returns. FGD is a kind of hybrid of nonparametric statistical function estimation and numerical optimization. Our FGD algorithm is computationally feasible in multivariate problems with dozens up to... Show more…
Language
  • English
Classification
Economics
License
License undefined
Identifiers
  • RERO DOC 5387
Persistent URL
https://susi.usi.ch/usi/documents/318042