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Expansions for Gaussian processes and Parseval frames

G. Pagès , H. Luschgy
Electronic Journal of Probability, 2009, 14 (42), pp.1198-1221
Journal articles hal-00437672v1

Computing VaR and CVaR using stochastic approximation and adaptive unconstrained importance sampling

O. Bardou , N. Frikha , G. Pagès
Monte Carlo Methods and Applications, 2009, 15 (3), pp.173-210
Journal articles hal-00497588v1

Quantization methods

G. Pagès
R. Cont. Encyclopedia of Quantitative Finance, Wiley, Volume 3, pp. 1451-1455, 2010
Book sections hal-00497652v1

When are swing options bang-bang?

G. Pagès , O. Bardou , S. Bouthemy
International Journal of Theoretical and Applied Finance, 2010, 13 (6), pp.867-899
Journal articles hal-00610170v1

Asymptotically optimal quantization schemes for Gaussian processes on Hilbert spaces.

G. Pagès , H. Luschgy , B. Wilbertz
ESAIM: Probability and Statistics, 2010, 14, pp.93-116. ⟨10.1051/ps:2008026⟩
Journal articles hal-00610171v1

Recursive Marginal Quantization of the Euler Scheme of a Diffusion Process

G. Pagès , A. Sagna
Applied Mathematical Finance, 2015, 22 (5), pp.463-498
Journal articles hal-01261313v1

Optimal posting distance of limit orders: a stochastic algorithm approach

S. Laruelle , C.-A. Lehalle , G. Pagès
Mathematics and Financial Economics, 2013, 7 (3), pp.359-403
Journal articles hal-00839247v1

Convergence of Langevin-Simulated Annealing algorithms with multiplicative noise

Pierre Bras , Gilles Pagès
2021
Preprints, Working Papers, ... hal-03891234v1

Moment estimates for Lévy Processes

G. Pagès , H. Luschgy
Electronic Communications in Probability, 2008, 13 (41), pp.422-434
Journal articles hal-00355227v1

Convex ordering for stochastic Volterra equations and their Euler schemes

Benjamin Jourdain , Gilles Pagès
2022
Preprints, Working Papers, ... hal-03862241v1

Functional quantization for numerics with an application to option pricing

G. Pagès , J. Printems
Monte Carlo Methods and Applications, 2005, 11 n.4, pp.407-446
Journal articles hal-00085419v1

Monotone convex order for the McKean-Vlasov processes

Yating Liu , Gilles Pagès
Stochastic Processes and their Applications, 2022, 152, pp.312-338. ⟨10.1016/j.spa.2022.06.003⟩
Journal articles hal-03205372v1
Image document

Risk Quantization by Magnitude and Propensity

Olivier P. Faugeras , Gilles Pages
2021
Preprints, Working Papers, ... hal-03233068v1

Quadratic optimal functional quantization of stochastic processes and numerical applications

G. Pagès
Monte Carlo and Quasi-Monte Carlo Methods, Ulm 2006, 2006, Ulm, Germany. pp.101-143
Conference papers hal-00211923v1

Optimal quantization for finance : From random vectors to stochastic processes

G. Pagès , J. Printems
A. Bensoussan and Q. Zhang. Mathematical modeling and numerical methods in finance, North-Holland, pp.595-648, 2009, Handbook of Numerical analysis, vol. XV, special volume
Book sections hal-00392177v1

GPGPUs in computational finance: massive parallel computing for American style options

G. Pagès , B. Wilbertz
Concurrency and Computation: Practice and Experience, 2011, Special Issue, 12 p. ⟨10.1002/cpe.1774⟩
Journal articles hal-00662165v1

First-order schemes in the numerical quantization method

G. Pagès , V. Bally , J. Printems
Mathematical Finance, 2003, 13 n.1, pp.1-16
Journal articles hal-00103809v1

Optimal Delaunay et Voronoi quantization methods for pricing American options

G. Pagès , B. Wilbertz
Numerical methods in Finance. Workshop Numerical methods in Finance, 2010,, 2010, Bordeaux, France. pp.171-217
Conference papers hal-00707862v1

Functional co-monotony of processes with applications to peacocks and barrier options

G. Pagès
C. Donati-Martin, A. Lejay, A. Rouault. Séminaire de Probabilités XLV, Springer, pp.365-400, 2013, Lecture Notes in Mathematics 2078
Book sections hal-00916457v1
Image document

Langevin algorithms for Markovian Neural Networks and Deep Stochastic control

Pierre Bras , Gilles Pagès
2022
Preprints, Working Papers, ... hal-03980632v1

Quantization-based approximation of reflected BSDEs with extended upper bounds for recursive quantization

Rancy El Nmeir , Gilles Pagès
2022
Preprints, Working Papers, ... hal-03890783v1

Recursive computation of invariant distributions of Feller processes

Gilles Pagès , Clément Rey
Stochastic Processes and their Applications, 2020, 130 (1), pp.328-365. ⟨10.1016/j.spa.2019.03.008⟩
Journal articles hal-03891155v1

Recursive computation of the invariant distributions of Feller processes: Revisited examples and new applications

Gilles Pagès , Clément Rey
2022
Preprints, Working Papers, ... hal-03890803v1

Monotone convex order for the McKean–Vlasov processes

Yating Liu , Gilles Pagès
Stochastic Processes and their Applications, 2022, 152, pp.312-338. ⟨10.1016/j.spa.2022.06.003⟩
Journal articles hal-03891164v1

Dynamic Programming versus supervised learning

Gilles Pagès , Olivier Pironneau
Numerical Control: Part A, 23, Elsevier, pp.467-497, 2022, Handbook of Numerical Analysis, ⟨10.1016/bs.hna.2021.12.014⟩
Book sections hal-03891198v1

Multi-asset American options and parallel quantization

A. Bronstein , G. Pagès , J. Portès
Methodology and Computing in Applied Probability, 2013, 15 (3), pp.547-561. ⟨10.1007/s11009-011-9265-4⟩
Journal articles hal-00858355v1

Functional quantization and small ball probabilities for Gaussian processes

G. Pagès , H. Luschgy , S. Graf
Journal of Theoretical Probability, 2003, 16 n.4, pp.1047-1062
Journal articles hal-00104809v1

Local distortion and µ-mass of the cells of one dimensional asymptotically optimal quantizers

S. Delattre , G. Pagès , J.C. Fort
Communications in Statistics - Theory and Methods, 2004, 33 n.5, pp.1087-1118
Journal articles hal-00102261v1

A quantization tree method for pricing and hedging multidimensional American options

G. Pagès , V. Bally , J. Printems
Mathematical Finance, 2005, 15 n.1, pp.119-168
Journal articles hal-00101786v1

Optimal quadratic quantization for numerics: the Gaussian case

G. Pagès , J. Printems
Monte Carlo Methods and Applications, 2003, 9 n.2, pp.135-165
Journal articles hal-00104800v1