Vivien Brunel

@article{brunel_1136,

title = {From the Fermi-Dirac distribution to PD curves},

author = {Vivien Brunel},

url = {https://www.emerald.com/insight/content/doi/10.1108/JRF-01-2018-0009/full/html},

year  = {2019},

date = {2019-03-18},

journal = {Journal of Risk Finance},

volume = {20},

number = {2},

pages = {138-154},

abstract = {In machine learning applications, and in credit risk modeling in particular, model performance is usually measured by using cumulative accuracy profile (CAP) and receiving operating characteristic curves. The purpose of this paper is to use the statistics of the CAP curve to provide a new method for credit PD curves calibration that are not based on arbitrary choices as the ones that are used in the industry.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{brunel_523,

title = {A general asymptotic formula for distinct partitions},

author = {Vivien Brunel},

url = {https://www.sciencedirect.com/science/article/abs/pii/S0003491618300861?via%3Dihub},

year  = {2018},

date = {2018-06-01},

journal = {Annals Of Physics},

volume = {394},

pages = {73-83},

abstract = {Many asymptotic formulas exist for unrestricted integer partitions as well as for equal partitions of integers into a finite number of parts. We use an analogy with fermion gases and the tools of statistical physics to derive asymptotic formulas for distinct partitions with a large but finite number of parts. These results are supported by the fact that we recover some other existing asymptotic results and by numerical comparisons with exact results.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{brunel_15,

title = {Expected Credit Loss vs Credit Value Adjustment: a comparative Analysis},

author = {Vivien Brunel and Stéphane Crépey and Monique Jeanblanc},

url = {https://econpapers.repec.org/article/rbqjournl/},

year  = {2016},

date = {2016-03-01},

journal = {Bankers, Markets & Investors},

volume = {141},

pages = {p6-p18},

abstract = {The recent publication of the IFRS 9 norms related to collective provisions for non defaulted instruments has settled a new vision to banking book portfolios. In this paper we show that the IFRS 9 provision measured through the Expected Credit Loss (ECL), inspired from a market vision on loan books, is very similar to the Credit Value Adjustment (CVA) for derivative exposures. However, even if the underlying formulas are identical, the metrics and parameters are not the same. Hence, though ECL and CVA measure similar effects, they involve different modelling challenges.},

note = {https://EconPapers.repec.org/RePEc:rbq:journl:i:141:p:6-18},

keywords = {},

pubstate = {published},

tppubtype = {article}

}