Nowcasting Recessions using the SVM Machine Learning Algorithm
Abstract
We introduce a novel application of Support Vector Machines (SVM), an important Machine Learning algorithm, to determine the beginning and end of recessions in real time. Nowcasting, "forecasting" a condition about the present time because the full information about it is not available until later, is key for recessions, which are only determined months after the fact. We show that SVM has excellent predictive performance for this task, and we provide implementation details to facilitate its use in similar problems in economics and finance.
Keywords
Cite
@article{arxiv.1903.03202,
title = {Nowcasting Recessions using the SVM Machine Learning Algorithm},
author = {Alexander James and Yaser S. Abu-Mostafa and Xiao Qiao},
journal= {arXiv preprint arXiv:1903.03202},
year = {2019}
}
Comments
My company policy about sharing research papers has been changed. As a result, I would like to withdraw the paper, with the full understanding that previous version will remain accessible. Thank you very much