Machine learning time series regressions with an application to nowcasting
| Year of publication: |
2022
|
|---|---|
| Authors: | Babii, Andrii ; Ghysels, Eric ; Striaukas, Jonas |
| Published in: |
Journal of business & economic statistics : JBES ; a publication of the American Statistical Association. - Abingdon : Taylor & Francis, ISSN 1537-2707, ZDB-ID 2043744-4. - Vol. 40.2022, 3, p. 1094-1106
|
| Subject: | Fat tails | High-dimensional time series | Mixed-frequency data | Sparse-group LASSO | Tau-mixing | Textual news data | Zeitreihenanalyse | Time series analysis | Künstliche Intelligenz | Artificial intelligence | Prognoseverfahren | Forecasting model | Regressionsanalyse | Regression analysis | Schätztheorie | Estimation theory |
-
Machine learning panel data regressions with heavy-tailed dependent data : theory and application
Babii, Andrii, (2023)
-
High-dimensional granger causality tests with an application to VIX and news
Babii, Andrii, (2024)
-
Cross-sectional expected returns : new Fama-MacBeth regressions in the era of machine learning
Han, Yufeng, (2024)
- More ...
-
Machine Learning Time Series Regressions With an Application to Nowcasting
Babii, Andrii, (2021)
-
Panel data nowcasting : the case of price-earnings ratios
Babii, Andrii, (2024)
-
Machine learning panel data regressions with heavy-tailed dependent data : theory and application
Babii, Andrii, (2023)
- More ...