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Andrii Babii

Biographic Data

ID8920496
NAMEAndrii Babii
GIVEN NAMESAndrii
FAMILY NAMEBabii
SIGNATUREBABII A
AFFILIATIONSUniversity of North Carolina at Chapel Hill
ORCID0000-0002-3996-6051
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
WORKS AS AUTHOR3
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2022
LATEST PUBLICATION YEAR2024
H-INDEX0
  • Panel data nowcasting

    Open Access•Andrii Babii, Ryan Ball et al.•ARTICLE•Journal of Applied Econometrics•2024

    The paper uses structured machine learning regressions for nowcasting with panel data consisting of series sampled at different frequencies. Motivated by the problem of predicting corporate earnings for a large cross‐section of firms with macroeconomic, financial, and news time series sampled at different frequencies, we focus on the sparse‐group LASSO regularization which can take advantage of the mixed‐frequency time series panel data structure…

  • Machine Learning Time Series Regressions With an Application to Nowcasting

    Andrii Babii, Éric Ghysels et al.•ARTICLE•Journal of Business and Economic…•2022

    This article introduces structured machine learning regressions for high-dimensional time series data potentially sampled at different frequencies. The sparse-group LASSO estimator can take advantage of such time series data structures and outperforms the unstructured LASSO. We establish oracle inequalities for the sparse-group LASSO estimator within a framework that allows for the mixing processes and recognizes that the financial and the macroe…

  • High-Dimensional Mixed-Frequency IV Regression

    Andrii Babii•ARTICLE•Journal of Business and Economic…•2022

No prominent works on this page.

  • Machine Learning Time Series Regressions With an Application to Nowcasting

    Andrii Babii, Éric Ghysels et al.•ARTICLE•Journal of Business and Economic…•2022

    This article introduces structured machine learning regressions for high-dimensional time series data potentially sampled at different frequencies. The sparse-group LASSO estimator can take advantage of such time series data structures and outperforms the unstructured LASSO. We establish oracle inequalities for the sparse-group LASSO estimator within a framework that allows for the mixing processes and recognizes that the financial and the macroe…

  • High-Dimensional Mixed-Frequency IV Regression

    Andrii Babii•ARTICLE•Journal of Business and Economic…•2022

  • Panel data nowcasting

    Open Access•Andrii Babii, Ryan Ball et al.•ARTICLE•Journal of Applied Econometrics•2024

    The paper uses structured machine learning regressions for nowcasting with panel data consisting of series sampled at different frequencies. Motivated by the problem of predicting corporate earnings for a large cross‐section of firms with macroeconomic, financial, and news time series sampled at different frequencies, we focus on the sparse‐group LASSO regularization which can take advantage of the mixed‐frequency time series panel data structure…

Computer Science (3 works) · Econometrics (3 works) · Mathematics (3 works) · Monetary Policy and Economic Impact (3 works) · Statistics (3 works) · Artificial Intelligence (2 works) · Estimator (2 works) · Financial Risk and Volatility Modeling (2 works) · Machine learning (2 works) · Nowcasting (2 works)

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