Machine Learning Regularization Methods in High-Dimensional Monetary and Financial VARs

Machine Learning Regularization Methods in High-Dimensional Monetary and Financial VARs

Vector autoregressions (VARs) and their multiple variants are standard models in economic and financial research due to their power for forecasting, data analysis and inference. These properties are a consequence of their capabilities to include multiple variables and lags which, however, turns into...

Täydet tiedot

Bibliografiset tiedot
Päätekijät: Sánchez García, Javier, Cruz Rambaud, Salvador
Aineistotyyppi: info:eu-repo/semantics/article
Kieli:English
Julkaistu: MDPI 2022
Aiheet:
VAR
machine learning
LASSO (Least Absolute Shrinkage and Selection Operator)
regularization methods
sparsity
monetary economics
financial economics
Linkit:http://hdl.handle.net/10835/13536

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