Mathieu Mercadier

Personal Details

First Name:	Mathieu
Middle Name:
Last Name:	Mercadier
Suffix:
RePEc Short-ID:	pme946
	[This author has chosen not to make the email address public]
Terminal Degree:	(from RePEc Genealogy)

Affiliation

École Supérieure de Commerce de Clermont

Clermont-Ferrant, France
http://www.esc-clermont.fr/
RePEc:edi:escclfr (more details at EDIRC)

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

1. Mathieu Mercadier & Jean-Pierre Lardy, 2019. "Credit spread approximation and improvement using random forest regression," Post-Print hal-03241566, HAL.
   • 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.
   • 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.

   Cited by:

   1. Nielson, Jordan & Bhaganagar, Kiran & Meka, Rajitha & Alaeddini, Adel, 2020. "Using atmospheric inputs for Artificial Neural Networks to improve wind turbine power prediction," Energy, Elsevier, vol. 190(C).
   2. Mercadier, Mathieu & Strobel, Frank, 2021. "A one-sided Vysochanskii-Petunin inequality with financial applications," European Journal of Operational Research, Elsevier, vol. 295(1), pages 374-377.
      • Mathieu Mercadier & Frank Strobel, 2021. "A one-sided Vysochanskii-Petunin inequality with financial applications," Post-Print hal-03241628, HAL.
   3. Hoang Hiep Nguyen & Jean-Laurent Viviani & Sami Ben Jabeur, 2023. "Bankruptcy prediction using machine learning and Shapley additive explanations," Post-Print hal-04223161, HAL.
   4. Santiago Carbo-Valverde & Pedro Cuadros-Solas & Francisco Rodríguez-Fernández, 2020. "A machine learning approach to the digitalization of bank customers: Evidence from random and causal forests," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-39, October.
   5. Solomon Y. Deku & Alper Kara & Artur Semeyutin, 2021. "The predictive strength of MBS yield spreads during asset bubbles," Review of Quantitative Finance and Accounting, Springer, vol. 56(1), pages 111-142, January.
   6. Tolga Yalçin & Pol Paradell Solà & Paschalia Stefanidou-Voziki & Jose Luis Domínguez-García & Tugce Demirdelen, 2023. "Exploiting Digitalization of Solar PV Plants Using Machine Learning: Digital Twin Concept for Operation," Energies, MDPI, vol. 16(13), pages 1-17, June.
   7. Mohammad S. Uddin & Guotai Chi & Mazin A. M. Al Janabi & Tabassum Habib, 2022. "Leveraging random forest in micro‐enterprises credit risk modelling for accuracy and interpretability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3713-3729, July.
   8. Chengyuan Li & Haoran Zhu & Hanjun Luo & Suyang Zhou & Jieping Kong & Lei Qi & Congjun Rao, 2023. "Spread Prediction and Classification of Asian Giant Hornets Based on GM-Logistic and CSRF Models," Mathematics, MDPI, vol. 11(6), pages 1-26, March.

Articles

1. 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.
   • 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, 2019. "Credit spread approximation and improvement using random forest regression," Post-Print hal-03241566, HAL.
   • Mathieu Mercadier & Jean-Pierre Lardy, 2021. "Credit spread approximation and improvement using random forest regression," Papers 2106.07358, arXiv.org.
   See citations under working paper version above.Sorry, no citations of articles recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers 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.

1. NEP-CMP: Computational Economics (2) 2021-06-21 2021-06-28. Author is listed
2. NEP-RMG: Risk Management (2) 2021-06-21 2021-06-21. Author is listed
3. NEP-BIG: Big Data (1) 2021-06-28. Author is listed

Corrections

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