Review Reports
- Paolo Gambetti1,
- Francesco Roccazzella2,* and
- Frédéric Vrins2,3
Reviewer 1: Claudiu Vinte Reviewer 2: Xin Huang
Round 1
Reviewer 1 Report
In the manuscript titled 'Meta-learning approaches for recovery rate prediction', the authors tackle the combination of ML models trained in security-specific characteristics and a limited number of well-identified theoretically sound recovery rate determinants to predict corporate bond recovery rates.
1. The proposed approach is modern and has great potential to be used in practice. Very good synthesis of ML algorithms for predictions.
2. Overall, the manuscript is well structured and the references invoked are adequate.
3. I would kindly suggest to the authors to underline in more detail their contribution in the field and to clearly define the nature of this contribution: is it methodological, technological, an apparatus?
4. My recommendation is to accept the manuscript in its current form.
Author Response
See attached file.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Please refer to attached RefereeReport.pdf.
Comments for author File: Comments.pdf
Author Response
See attached pdf file.
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Very nice revision.