Panel Data Nowcasting: The Case of Price-Earnings Ratios

• URL: http://arxiv.org/abs/2307.02673v1
• Date: Wed, 5 Jul 2023 22:04:46 GMT
• Title: Panel Data Nowcasting: The Case of Price-Earnings Ratios
• Authors: Andrii Babii and Ryan T. Ball and Eric Ghysels and Jonas Striaukas
• Abstract summary: 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, we focus on the sparse-group LASSO regularization.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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 structures. Our empirical results show the superior performance of our machine learning panel data regression models over analysts' predictions, forecast combinations, firm-specific time series regression models, and standard machine learning methods.

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