Monitoring Privately-held Firms' Default Risk in Real Time: A Signal-Knowledge Transfer Learning Model

Monitoring Privately-held Firms' Default Risk in Real Time: A Signal-Knowledge Transfer Learning Model
READ MORE...
Volume/Issue: Volume 2024 Issue 115
Publication date: June 2024
ISBN: 9798400278396
$20.00
Add to Cart by clicking price of the language and format you'd like to purchase
Available Languages and Formats
English
Prices in red indicate formats that are not yet available but are forthcoming.
Summary

We develop a mixed-frequency, tree-based, gradient-boosting model designed to assess the default risk of privately held firms in real time. The model uses data from publicly-traded companies to construct a probability of default (PD) function. This function integrates high-frequency, market-based, aggregate distress signals with low-frequency, firm-level financial ratios, and macroeconomic indicators. When provided with private firms' financial ratios, the model, which we name signal-knowledge transfer learning model (SKTL), transfers insights gained from 35 thousand publicly-traded firms to more than 4 million private-held ones and performs well as an ordinal measure of privately-held firms' default risk.