I. S. Crépey. XVA Analysis–Probabilistic, Risk Measure, and Machine Learning Issues. Chapman & Hall/CRC  Financial Mathematics Series, 2025 (forthcoming).

II. S. Crépey. Financial Modeling, A Backward Stochastic Differential Equations Perspective (with exercises, corrected problems and Matlab scripts). Springer Finance Textbook Series, June 2013. Abstracts by chapters

III. S. Crépey and T. Bielecki (with an introductory dialogue by D. Brigo). Counterparty Risk and Funding, A Tale of Two Puzzles. Chapman & Hall/CRC  Financial Mathematics Series, June 2014. Sample Summary

Climate Risk

1.  S. Crépey, S. Drapeau and M. Tadese. Comparison of Tax and Cap-and-Trade Carbon Pricing Schemes. Working paper arXiv: 2510.15941, 2025.

2. S. Crépey, M. Tadese and G. Vermandel. Sensitivity analysis of emission markets: a Radner equilibrium approach in discrete time. Working paper arXiv:2411.06185v2, 2025.

Neural nets in Finance

3.  S. Bossu,  S. Crépey, and H. D. Nguyen. Spanning multi-asset payoffs with ReLUs. Mathematical Finance 35(3), 682-707, 2025.

4. S. Crépey, N. Lehdili, N. Madhar, and M. Thomas.  Anomaly detection on financial time series by principal component analysis and neural networks regressions. Algorithms 15(10), 385, 2022 (doi.org/10.3390/a15100385, 38 pages).

5.  M. Chataigner, S. Crépey, and J. Pu. Nowcasting networks. Journal of Computational Finance 24(3), DOI: 10.21314/JCF.2020.404 pages 1-39, 2020.

6.  M. Chataigner, S. Crépey, and M. Dixon. Deep local volatility. Risks 8(82), 18 pages, 2020. Special Issue Machine Learning in Finance, Insurance and Risk Management. Feature Paper invited by Guest Editor.

Stochastic Approximation (for VaR and ES, mainly)

7.  D. Barrera, S. Crépey, B. Diallo, G. Fort, E. Gobet, and U. Stazhynski. Stochastic approximation schemes for economic capital and risk margin computations. ESAIM: Proceedings and Surveys (65) 182-218, 2019.

8.  S. Crépey, N. Frikha, and A. Louzi. A multilevel stochastic approximation algorithm for unbiased value-at-risk and expected shortfall estimation. Finance and Stochastics 29, 1015-1074, 2025.

9.  S. Crépey, N. Frikha, A. Louzi, and G. Pagès. Asymptotic error analysis of multilevel stochastic approximations for the value-at-risk and expected shortfall. Electronic Journal of Probability 29 (198) 1-56, 2024.

10.  S. Crépey, N. Frikha, A. Louzi, and J. Spence. An adaptive multilevel stochastic approximation algorithm for value-at-risk estimation. Working paper.

11. S. Crépey, G. Fort, E. Gobet, and U. Stazhynski. Uncertainty Quantification for Stochastic Approximation Limits Using Chaos Expansion. SIAM/ASA Journal on Uncertainty Quantification 8(3), 1061-1089, 2020.  Also extended abstract version (in French).

XVA Analysis

12.  Y. Armenti, C. Zhou and S. Crépey. The sustainable Black-Scholes equations. In Actuarial Science and Quantitative Finance: ICASQF2016, Cartagena, Colombia, June 2016, Springer Proceedings in Mathematics & Statistics, Springer, pp. 155-167, 2017.

13.  C. Albanese, S. Crépey, R. Hoskinson, and B. Saadeddine. XVA analysis from the balance sheet. Quantitative Finance 21 (1), 99-123, 2021.

14.  S. Crépey. Invariance times transfer properties. Probability, Uncertainty and Quantitative Risk 9(4), 431-452, 2024.

15.  S. Crépey. Positive XVAs. Frontiers of Mathematical Finance 1(3), 425-465, 2022 (doi: 10.3934/fmf.2022003).

16.  S. Crépey, W. Sabbagh, and S. Song. When capital is a funding source: the anticipated backward stochastic differential equations of X-value adjustments. SIAM Journal on Financial Mathematics  11(1), 99–130, 2020.

17.  C. Albanese, S. Caenazzo  and S. Crépey. Credit, funding, margin, and capital valuation adjustments for bilateral portfolios. Probability, Uncertainty and Quantitative Risk 2(7), 26 pages, 2017 (DOI 10.1186/s41546-017-0019-2).

18.  L. Abbas-Turki, S. Crépey, and B. Diallo. XVA principles, nested  Monte Carlo, and GPU optimizations. International Journal of Theoretical and Applied Finance (21), 1850030, 2018.

19.  L. Abbas-Turki,  B. Li, S. Crépey, and B. Saadeddine. Pathwise CVA regressions with oversimulated defaults. Mathematical Finance 33(2), pages 274-307, 2023.

20.   S. Crépey, H. D. Nguyen, and B. Saadeddine. CVA sensitivities, hedging, and risk. Long arXiv version of the eponymous Risk Magazine July 2024 paper.

21.  L. Abbas-Turki, B. Li, S. Crépey, and B. Saadeddine.  An explicit scheme for pathwise XVA computations. Journal of Computational Finance 28(4), pages 1-36, 2025.

22.  C. Albanese, M. Chataigner and S. Crépey. Wealth transfers, indifference pricing, and   XVA compression schemes. In From Probability to Finance - Lecture note of BICMR   summer school on financial mathematics, pages 219-248, Y. Jiao (ed.). Springer Mathematical Lectures from Peking University Series, Springer, 2020.

23.  M. Chataigner and S. Crépey. Credit valuation adjustment compression by genetic optimization. Risks 7(4), 100, 2019. Special Issue Advances in Credit Risk Modeling and Management. Feature Paper invited by Guest Editor.

24.  C. Albanese, Y. Armenti, and S. Crépey. XVA metrics for CCP optimisation. Statistics & Risk Modeling 37(1-2), 25–53, 2020. 

25.  C. Albanese, S. Crépey, and S. Iabichino.  Quantitative reverse stress testing, bottom up. Quantitative Finance 23(5), 863-875, 2023.

26.  D. Bastide, S. Crépey, S. Drapeau and M. Tadese. Derivatives risks as costs in a one period network model. Frontiers of Mathematical Finance 2(3), 283-312, 2023.

27.  D. Bastide and S. Crépey. Provisions and economic capital for credit Losses.  Quantitative Finance 25(4), 617–631, 2025.

28.  D. Bastide, S. Crépey, S. Drapeau and M. Tadese. Resolving a clearing member's default: a Radner equilibrium approach. Mathematics and Financial Economics 19, 183–223, 2025.

29.  C. Benezet and S. Crépey. Handling model risk with XVAs. Frontiers of Mathematical Finance 3(4), 490-519, 2024.

30.  C. Benezet, S. Crépey and Dounia Essaket. Hedging valuation adjustment for callable claims. Working paper.

Machine Learning in Finance

31.  D. Barrera, S. Crépey, E. Gobet, H. D. Nguyen and B. Saadeddine.  Statistical learning of value-at-risk and expected shortfall. Forthcoming in  Mathematical Finance.

32.  M. Chataigner, A. Cousin, S. Crépey, M. Dixon, and D. Gueye. Beyond surrogate modeling: Learning the local volatility via shape constraints. SIAM Journal on Financial Mathematics / Short Communications 12(3), SC58-SC69, 2021.

33.  S. Crépey and M. Dixon. Gaussian process regression for derivative portfolio modeling and application to CVA computations. Journal of Computational Finance 24(1), 1-35, 2020.

Central counterparties (CCPs) and Systemic Risk

34. Y. Armenti and S. Crépey. Central clearing valuation adjustment. SIAM Journal on Financial Mathematics 8 (1) 274-313, 2017.

35. Y. Armenti, S. Crépey, S. Drapeau and A. Papapantoleon. Multivariate shortfall risk allocation and systemic risk. SIAM Journal on Financial Mathematics  9 (1) 90-126, 2018. And beta version with more Chebyshev polynomial interpolation details.

Random Times, Enlargement of Filtration, and BSDEs Stopped Before a Random Time

36.  S. Crépey and S. Song. Invariance times. Annals of Probability 45 (6B), 4632-4674, 2017.

37.  S. Crépey and S. Song. BSDEs of counterparty risk. Stochastic Processes and Applications 125 (8), 3023-3052, 2015.

38.  S. Crépey and S. Song  Invariance properties in the dynamic Gaussian copula model.  ESAIM: Proceedings and Surveys  56, 22-41, 2017.

Counterparty Risk and Funding

39.  S. Crépey and S. Song. Counterparty risk and funding: Immersion and beyond. Finance and Stochastics 20 (4), pp. 910-930, 2016.

40.  S. Crépey, R. Gerboud, Z. Grbac and N. Ngor. Counterparty risk and funding: the four wings of the TVA. International Journal of Theoretical and Applied Finance March 2013.

41.  S. Crépey. Bilateral  counterparty risk under funding constraints – Part I: Pricing.  Mathematical Finance online first January 2013.

42.  S. Crépey. Bilateral  counterparty risk under funding constraints – Part II: CVA.  Mathematical Finance online first January 2013.  

43.  S. Crépey. Preface to the special issue ‘Frontiers of Counterparty Risk’, International Journal of Theoretical and Applied Finance March 2013. 

Portfolio Credit Risk

44.  T. Bielecki, A. Cousin, S. Crépey, A. Herbertsson. Dynamic Hedging of Portfolio Credit Risk in a Markov Copula Model. Journal of Optimization Theory and Application 161 (1), 90-102, 2014. 

45.  T. Bielecki, A. Cousin, S. Crépey, A. Herbertsson. A Bottom-Up Dynamic Model of Portfolio Credit Risk - Part I: Markov Copula Perspective. In Recent Advances in Financial Engineering 2012, pages 25-49, A. Takahashi,  Y. Muromachi and T. Shibata, eds.,  World Scientific, 2014.

46.  T. Bielecki, A. Cousin, S. Crépey, A. Herbertsson. A Bottom-Up Dynamic Model of Portfolio Credit Risk - Part II: Common-Shock Interpretation, Calibration and Hedging issues. In Recent Advances in Financial Engineering 2012, pages 50-74, A. Takahashi,  Y. Muromachi and T. Shibata, eds.,  World Scientific, 2014.

47.  A. Cousin, S. Crépey and Y.-H Kan. Delta-hedging correlation risk? Review of Derivatives Research 15 (1) 25-56, 2012.

48.  T. Bielecki, S. Crépey, A. Herbertsson. Markov chain models of portfolio credit risk. Short version of the eponymous paper in Oxford Handbook of Credit Derivatives, A. Lipton and A. Rennie, eds.

49.  T.R. Bielecki, S. Crépey, M. Jeanblanc. Up and down credit risk. Quantitative Finance 10 (10) 1137-1151,  2010.

50.  T.R. Bielecki, S. Crépey, M. Jeanblanc and M. Rutkowski. Valuation of Basket Credit Derivatives in the Credit Migrations Environment. Handbook of Financial Engineering 2007. 

Simulation Methods for Prices

51.  S. Crépey and T. M. Nguyen. Nonlinear Monte Carlo schemes for counterparty risk on credit derivatives.  Springer Proceedings in Mathematics / Challenges in Derivatives Markets, Springer, pp. 53-82, 2016.

52.  S. Crépey and A. Rahal. Simulation/Regression Pricing Schemes for CVA Computations on CDO Tranches. Communications in Statistics – Theory and Methods 43 (7), 1390-1408, 2014.

53.  J.-F. Chassagneux and S. Crépey. Doubly reflected BSDEs with call protection and their approximation. ESAIM: Probability and Statistics, 18, 613-641, 2014.

54.  S. Crépey and A. Rahal. Pricing convertible bonds with call protection. Journal of Computational Finance 15 (2), 37-75, Winter 2011/12.

55.  R. Carmona, S. Crépey. Particle methods for the estimation of Markovian credit portfolios loss distribution. International Journal of Theoretical and Applied Finance 13 ( 4),  577-602, 2010. 

Counterparty Credit Risk

56.  S. Crépey, M. Jeanblanc and D. L. Wu. Informationally Dynamized Gaussian Copula. International Journal of Theoretical and Applied Finance March 2013.

57.  V. Brunel, S. Crépey and M. Jeanblanc. Expected credit loss vs. credit value adjustment: A Comparative Analysis. Bankers, Markets and Investors nº 141, 6-18, 2016.

58.  T. Bielecki, S. Crépey. Dynamic Hedging of Counterparty Exposure. The Musiela Festschrift, T. Zariphopoulou, M. Rutkowski and Y. Kabanov (eds.), Springer, pp. 47-71, 2014.eds, Springer.

59.  S. Assefa, T. Bielecki, S. Crépey, M. Jeanblanc. CVA computation for counterparty risk assessment in credit portfolios. Short version of the eponymous paper in Credit Risk Frontiers, T. Bielecki, D. Brigo and F. Patras (eds.), Wiley, pp. 397-436, 2011.

60.  T. Bielecki, S. Crépey, M. Jeanblanc and B. Zargari. Valuation and Hedging of CDS Counterparty Exposure in a Markov Copula Model. International Journal of Theoretical and Applied Finance  15 (1) 1250004, 2012.

61.  S. Crépey, M. Jeanblanc and B. Zargari. Counterparty Risk on a CDS in a Markov Chain Copula Model with Joint Defaults. Recent Advances in Financial Engineering 2009, M. Kijima, C. Hara, Y. Muromachi and K. Tanaka, eds, World Scientific, pp. 91-126, 2010.

Reflected BSDEs, Defaultable American and Game Options, and Convertible Bonds

62.  T.R. Bielecki, S. Crépey, M. Jeanblanc and M. Rutkowski. Convertible Bonds in a Defaultable Diffusion Model. Convertible Bonds in a Defaultable Diffusion Model. Stochastic Analysis with Financial Applications,  A. Kohatsu-Higa, N. Privault and S.J. Sheu eds, pp. 255-298, Birkhäuser / Springer Basel, 2011.

63.  S. Crépey. About the Pricing Equations in Finance. Paris-Princeton Lectures in Mathematical Finance 2010, Lecture Notes in Mathematics, Springer, pp.63-203, 2011.

64.  S. Crépey, A. Matoussi. Reflected and Doubly Reflected BSDEs with Jumps: A Priori Estimates and Comparison Principle. Annals of Applied Probability, 18 (5), 2041-69 (2008).

65.  T.R. Bielecki, S. Crépey, M. Jeanblanc and M. Rutkowski. Defaultable Options in a Markovian Intensity Model of Credit Risk. Updated Version of the paper published under the same title in Mathematical Finance, 2008.

66.  T.R. Bielecki, S. Crépey, M. Jeanblanc and M. Rutkowski. Valuation and Hedging of Defaultable Game Options in a Hazard Process Model. Journal of Applied Mathematics and Stochastic Analysis, Article ID 695798, 33 pages, 2009 (and Long Preprint Version).

67.  T.R. Bielecki, S. Crépey, M. Jeanblanc and M. Rutkowski. Arbitrage Pricing of Defaultable Game Options with Applications to Convertible Bonds. Quantitative Finance, 8 (8), 795 – 810, 2008.

Multiple Curves Interest Rate Models

68.  S Crépey, Z. Grbac, N. Ngor and D. Skovmand. A Lévy HJM multiple-curve model with application to CVA computation. Quantitative Finance 15 (3), 401-419, 2015.

69.  S. Crépey, Z. Grbac and H. N. Nguyen. A multiple-curve HJM model of interbank risk. Mathematics and Financial Economics 6(3) 155-190, 2012. 

Model Calibration

70.  S. Crépey, A. Macrina, N. Nguyen and D. Skovmand. Rational multi-curve models with counterparty-risk valuation adjustments. Quantitative Finance 16 (6), 847-866, 2016.

71.  T. Bielecki, A. Cousin, S. Crépey, A. Herbertsson. A Bottom-Up Dynamic Model of Portfolio Credit Risk with Stochastic Intensities and Random Recoveries. Communications in Statistics – Theory and Methods 43 (7), 1362-1389, 2014.

72.  S. Crépey. Tikhonov Regularization. Encyclopedia of Quantitative Finance, editor Rama Cont, pp. 1807-1812, 2010.

73.  S. Crépey. Calibration of the local volatility in a trinomial tree using Tikhonov regularization. Inverse Problems, 19 (2003), 91-127. 

Local Volatility

74.  S. Crépey Calibration of the local volatility in a generalized Black-Scholes model using Tikhonov regularization. SIAM Journal on Mathematical Analysis, 34 (5), 1183-1206, 2003.

75.  S. Crépey. Delta-hedging Vega Risk? Quantitative Finance 4, 559–579, 2004.

Differential Games

76.  P. Bernhard, S. Crépey and A. Rapaport. Comparison of two numerical schemes for barrier and value of a simple pursuit-evasion game. Advances in Dynamic Games and Applications. E. Altman and O. Pourtallier (eds.), Birkhaüser, 253-273, 2001.

a.   S. Crépey, H. D. Nguyen, and B. Saadeddine. CVA sensitivities, hedging, and risk.  Risk Magazine July 2024 1-6 (see also the eponymous long arXiv version).

b.   C. Albanese, S. Crépey, and S. Iabichino.  A Darwinian theory of model risk. Risk Magazine, July 2021.

c.    Frederic Siboulet, Ranjeet Kumar, Raphael Douady, and Stéphane Crépey. IBOR Inside out transition and challenges. Wilmott Magazine janvier 2019.

d.   C. Albanese, S. Caenazzo  and S. Crépey, Capital and funding. Risk Magazine, pp. 71-76, May 2016.

e.   S. Crépey. XVA: About CVA, DVA, FVA and other market adjustments. Opinions & Débats 5, June 2014.

f.    S. Crépey and R. Douady. LOIS: credit and liquidity. Risk Magazine June 2013. Short version The whys of the LOIS: credit skew and funding rates volatility Bloomberg Brief / Risk 24 May 2013, pp.6-7

g.   T. Bielecki, A. Cousin, S. Crépey, A. Herbertsson. In search of a grand unifying theory. Creditflux Newsletter Analysis, pp.20-21, July 2013. Web full version The Bottom-Up Top-Down Puzzle Solved, creditflux.com

h.   S. Crépey. Counterparty risk and funding: putting things together. Creditflux Newsletter Analysis, pp.14-15, Dec 2011.