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...

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Hlavní autoři: Sánchez García, Javier, Cruz Rambaud, Salvador
Médium: info:eu-repo/semantics/article
Jazyk:English
Vydáno: MDPI 2022
Témata:
VAR
machine learning
LASSO (Least Absolute Shrinkage and Selection Operator)
regularization methods
sparsity
monetary economics
financial economics
On-line přístup:http://hdl.handle.net/10835/13536

Internet

http://hdl.handle.net/10835/13536

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