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Nets: network estimation for time series

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  • Barigozzi, Matteo
  • Brownlees, Christian T.

Abstract

We model a large panel of time series as a var where the autoregressive matrices and the inverse covariance matrix of the system innovations are assumed to be sparse. The system has a network representation in terms of a directed graph representing predictive Granger relations and an undirected graph representing contemporaneous partial correlations. A lasso algorithm called nets is introduced to estimate the model. We apply the methodology to analyse a panel of volatility measures of ninety bluechips. The model captures an important fraction of total variability, on top of what is explained by volatility factors, and improves out-of-sample forecasting.

Suggested Citation

  • Barigozzi, Matteo & Brownlees, Christian T., 2018. "Nets: network estimation for time series," LSE Research Online Documents on Economics 90493, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:90493
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    More about this item

    Keywords

    networks; multivariate time series; var; lasso; forecasting;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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