Barigozzi, Matteo and Brownlees, Christian T. (2018) Nets: network estimation for time series. Journal of Applied Econometrics. ISSN 1099-1255
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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.
Item Type: | Article |
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Official URL: | https://onlinelibrary.wiley.com/journal/10991255 |
Additional Information: | © 2018 Wiley |
Divisions: | Statistics |
Subjects: | H Social Sciences > HA Statistics |
Date Deposited: | 24 Oct 2018 15:43 |
Last Modified: | 21 Sep 2024 02:45 |
URI: | http://eprints.lse.ac.uk/id/eprint/90493 |
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