Zhongmin Luo
Personal Details
First Name: | Zhongmin |
Middle Name: | |
Last Name: | Luo |
Suffix: | |
RePEc Short-ID: | plu394 |
| |
Affiliation
Department of Economics, Mathematics and Statistics
Birkbeck College
London, United Kingdomhttp://www.ems.bbk.ac.uk/
RePEc:edi:debbkuk (more details at EDIRC)
Research output
Jump to: Working papersWorking papers
- Raymond Brummelhuis & Zhongmin Luo, 2017.
"CDS Rate Construction Methods by Machine Learning Techniques,"
Papers
1705.06899, arXiv.org.
- Brummelhuis, Raymond & Luo, Zhongmin, 2017. "CDS Rate Construction Methods by Machine Learning Techniques," MPRA Paper 79194, University Library of Munich, Germany.
Citations
Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.Working papers
- Raymond Brummelhuis & Zhongmin Luo, 2017.
"CDS Rate Construction Methods by Machine Learning Techniques,"
Papers
1705.06899, arXiv.org.
- Brummelhuis, Raymond & Luo, Zhongmin, 2017. "CDS Rate Construction Methods by Machine Learning Techniques," MPRA Paper 79194, University Library of Munich, Germany.
Cited by:
- Mathieu Mercadier & Jean-Pierre Lardy, 2019.
"Credit spread approximation and improvement using random forest regression,"
Post-Print
hal-03241566, HAL.
- Mathieu Mercadier & Jean-Pierre Lardy, 2019. "Credit Spread Approximation and Improvement using Random Forest Regression," Post-Print hal-02057019, HAL.
- Mathieu Mercadier & Jean-Pierre Lardy, 2021. "Credit spread approximation and improvement using random forest regression," Papers 2106.07358, arXiv.org.
- Mercadier, Mathieu & Lardy, Jean-Pierre, 2019. "Credit spread approximation and improvement using random forest regression," European Journal of Operational Research, Elsevier, vol. 277(1), pages 351-365.
- Ryan Ferguson & Andrew Green, 2018. "Deeply Learning Derivatives," Papers 1809.02233, arXiv.org, revised Oct 2018.
More information
Research fields, statistics, top rankings, if available.Statistics
Access and download statistics for all items
NEP Fields
NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.- NEP-CMP: Computational Economics (1) 2017-05-28. Author is listed
- NEP-RMG: Risk Management (1) 2017-05-28. Author is listed
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.
To update listings or check citations waiting for approval, Zhongmin Luo should log into the RePEc Author Service.
To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.
To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.
Please note that most corrections can take a couple of weeks to filter through the various RePEc services.