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September 2011 - August 2014

## Publications

Publications (50)

In this paper we fill a gap in the literature by providing exact and explicit expressions for the correlation of general Hawkes processes together with its intensity process. Our methodology relies on the Poisson imbedding representation and on recent findings on Malliavin calculus and pseudo-chaotic representation for counting processes.

We derive quantitative bounds in the Wasserstein distance for the approximation of stochastic integrals with respect to Hawkes processes by a normally distributed random variable. In the case of deterministic and nonnegative integrands, our estimates involve only the third moment of the integrand in addition to a variance term using a squared norm...

We derive quantitative bounds in the Wasserstein distance for the approximation of stochastic integrals with respect to Hawkes processes by a normally distributed random variable. In the case of deterministic and non-negative integrands, our estimates involve only the third moment of integrand in addition to a variance term using a square norm of t...

We introduce and study an alternative form of the chaotic expansion for counting processes using the Poisson imbedding representation; we name this alternative form \textit{pseudo-chaotic expansion}. As an application, we prove that the coefficients of this pseudo-chaotic expansion for any linear Hawkes process are obtained in closed form, whereas...

In this paper we provide an expansion formula for Hawkes processes which involves the addition of jumps at deterministic times to the Hawkes process in the spirit of the well-known integration by parts formula (or more precisely the Mecke formula) for Poisson functional. Our approach allows us to provide an expansion of the premium of a class of cy...

In this paper, following Nourdin-Peccati's methodology, we combine the Malliavin calculus and Stein's method to provide general bounds on the Wasserstein distance between functionals of a compound Hawkes process and a given Gaussian density. To achieve this, we rely on the Poisson embedding representation of an Hawkes process to provide a Malliavin...

We investigate Weierstrass functions with roughness parameter $\gamma$ that are H\"older continuous with coefficient $H={\log\gamma}/{\log \frac12}.$ Analytical access is provided by an embedding into a dynamical system related to the baker transform where the graphs of the functions are identified as their global attractors. They possess stable ma...

In this paper we provide an alternative framework to tackle the first-best Principal-Agent problem under CARA utilities. This framework leads to both a proof of existence and uniqueness of the solution to the Risk-Sharing problem under very general assumptions on the underlying contract space. Our analysis relies on an optimal decomposition of the...

In this paper we provide an It{\^o}-Tanaka-Wentzell trick in a non semimartingale context. We apply this result to the study of a fractional SDE with irregular drift coefficient.

In this paper, we investigate a stochastic Hardy-Littlewood-Sobolev inequality. Due to the stochastic nature of the inequality, the relation between the exponents of intgrability is modified. This modification can be understood as a regularization by noise phenomenon. As a direct application, we derive Strichartz estimates for the white noise dispe...

In this paper we provide a valuation formula for different classes of actuarial and financial contracts which depend on a general loss process, by using the Malliavin calculus. In analogy with the celebrated Black-Scholes formula, we aim at expressing the expected cash flow in terms of a building block. The former is related to the loss process whi...

In this paper, we study the existence of densities (with respect to the Lebesgue measure) for marginal laws of the solution (Y,Z) to a quadratic growth BSDE. Using the (by now) well-established connection between these equations and their associated semi-linear PDEs, together with the Nourdin-Viens formula, we provide estimates on these densities.

In this paper we address an open question formulated in [17]. That is, we
extend the It{\^o}-Tanaka trick, which links the time-average of a
deterministic function f depending on a stochastic process X and F the solution
of the Fokker-Planck equation associated to X, to random mappings f. To this
end we provide new results on a class of adpated and...

In this paper we study a utility maximization problem with random horizon and
reduce it to the analysis of a specific BSDE, which we call BSDE with singular
coefficients, when the support of the default time is assumed to be bounded. We
prove existence and uniqueness of the solution for the equation under interest.
Our results are illustrated by nu...

In this paper, we provide a strong formulation of the stochastic G{\^a}teaux
differentiability in order to study the sharpness of a new characterization,
introduced in [6], of the Malliavin-Sobolev spaces. We also give a new internal
structure of these spaces in the sense of sets inclusion.

We prove functional central and non-central limit theorems for generalized
variations of the anisotropic d-parameter fractional Brownian sheet (fBs) for
any natural number d. Whether the central or the non-central limit theorem
applies depends on the Hermite rank of the variation functional and on the
smallest component of the Hurst parameter vecto...

In this paper we provide new conditions for the Malliavin differentiability
of solutions of Lipschitz or quadratic BSDEs. Our results rely on the
interpretation of the Malliavin derivative as a G\^ateaux derivative in the
directions of the Cameron-Martin space. Incidentally, we provide a new
formulation for the characterization of the Malliavin-Sob...

In this paper, we study the existence of densities (with respect to the
Lebesgue measure) for marginal laws of the solution $(Y,Z)$ to a quadratic
growth BSDE. Using the (by now) well-established connection between these
equations and their associated semi-linear PDEs, together with the
Nourdin-Viens formula, we provide estimates on these densities...

In this Note we study a class of BSDEs which admits a particular singularity
in their driver. More precisely, we assume that the driver is not integrable
and degenerates when approaching to the terminal time of the equation.

The paper analyzes risk assessment for cash flows in continuous time using
the notion of convex risk measures for processes. By combining a decomposition
result for optional measures, and a dual representation of a convex risk
measure for bounded \cd processes, we show that this framework provides a
systematic approach to the both issues of model a...

The problem of optimal investment with CRRA (constant, relative
risk aversion) preferences, subject to dynamic risk constraints on trading strategies,
is the main focus of this paper. Several works in the literature, which deal either
with optimal trading under static risk constraints or with VaR-based dynamic risk
constraints, are extended. The ma...

We introduce a new class of Backward Stochastic Differential Equations in
which the $T$-terminal value $Y_{T}$ of the solution $(Y,Z)$ is not fixed as a
random variable, but only satisfies a weak constraint of the form
$E[\Psi(Y_{T})]\ge m$, for some (possibly random) non-decreasing map $\Psi$ and
some threshold $m$. We name them BSDEs with weak te...

In this paper we study BSDEs arising from a special class of backward stochastic partial differential equations (BSPDEs) that is intimately related to utility maximization problems with respect to arbitrary utility functions. After providing existence and uniqueness we discuss the numerical realizability. Then we study utility maximization problems...

In this paper we deal with the utility maximization problem with a general
utility function. We derive a new approach in which we reduce the utility
maximization problem with general utility to the study of a fully-coupled
Forward-Backward Stochastic Differential Equation (FBSDE).

We extend the work of Delong and Imkeller (2010)Â [6] and [7] concerning backward stochastic differential equations with time delayed generators (delay BSDEs). We give moment and a priori estimates in general Lp-spaces and provide sufficient conditions for the solution of a delay BSDE to exist in Lp. We introduce decoupled systems of SDEs and delay...

In this paper we prove that every random variable of the form $F(M_T)$ with
$F:\real^d \to\real$ a Borelian map and $M$ a $d$-dimensional continuous Markov
martingale with respect to a Markov filtration $\mathcal{F}$ admits an exact
integral representation with respect to $M$, that is, without any orthogonal
component. This representation holds tru...

This paper studies the problem of optimal investment with CRRA (constant, relative risk aversion) preferences, subject to dynamic risk constraints on trading strategies. The market model considered is continuous in time and incomplete; furthermore, financial assets are modeled by Itô processes. The dynamic risk constraints (time, state dependent) a...

This paper studies the problem of optimal investment with CRRA (constant,
relative risk aversion) preferences, subject to dynamic risk constraints on
trading strategies. The market model considered is continuous in time and
incomplete. the prices of financial assets are modeled by It\^o processes. The
dynamic risk constraints, which are time and st...

We prove central and non-central limit theorems for the Hermite variations of the anisotropic fractional Brownian sheet $W^{\alpha, \beta}$ with Hurst parameter $(\alpha, \beta) \in (0,1)^2$. When $0<\alpha \leq 1-\frac{1}{2q}$ or $0<\beta \leq 1-\frac{1}{2q}$ a central limit theorem holds for the renormalized Hermite variations of order $q\geq 2$,...

Let $B$ be a fractional Brownian motion with Hurst parameter $H=1/6$. It is known that the symmetric Stratonovich-style Riemann sums for $\int g(B(s))\,dB(s)$ do not, in general, converge in probability. We show, however, that they do converge in law in the Skorohod space of c\`adl\`ag functions. Moreover, we show that the resulting stochastic inte...

In this Note we consider a quadratic backward stochastic differential equation (BSDE) driven by a continuous martingale $M$ and whose generator is a deterministic function. We prove (in Theorem \ref{theorem:main}) that if $M$ is a strong homogeneous Markov process and if the BSDE has the form \eqref{BSDE} then the unique solution $(Y,Z,N)$ of the B...

In this paper we consider a class of BSDEs with drivers of quadratic growth, on a stochastic basis generated by continuous local martingales. We first derive the Markov property of a forward-backward system (FBSDE) if the generating martingale is a strong Markov process. Then we establish the differentiability of a FBSDE with respect to the initial...

We construct superefficient estimators of Stein type for the intensity parameter λ>0 of a Poisson process, using integration
by parts and superharmonic functionals on the Poisson space.

We consider the nonparametric functional estimation of the drift of a Gaussian process via minimax and Bayes estimators. In this context, we construct superefficient estimators of Stein type for such drifts using the Malliavin integration by parts formula and superharmonic functionals on Gaussian space. Our results are illustrated by numerical simu...

In this thesis we apply the Malliavin calculus to statistical estimation of parameters of stochastic processes and to derive limit theorems for the weighted quadratic variations of one or two-parameter fractional processes and to multidimensional normal approximation of probability measures. In Chapter 1 we construct Stein type estimators for the d...

We construct an estimation and de-noising procedure for an input signal perturbed by a continuous-time Gaussian noise, using the local and occupation times of Gaussian processes. The method relies on the almost-sure minimization of a Stein Unbiased Risk Estimator (SURE) obtained through integration by parts on Gaussian space, and applied to shrinka...

In this paper we consider the nonparametric functional estimation of the drift of Gaussian processes using Paley-Wiener and Karhunen-Lo\`eve expansions. We construct efficient estimators for the drift of such processes, and prove their minimaxity using Bayes estimators. We also construct superefficient estimators of Stein type for such drifts using...

We combine Stein's method with Malliavin calculus in order to obtain explicit bounds in the multidimensional normal approximation (in the Wasserstein distance) of functionals of Gaussian fields. Our results generalize and refine the main findings by Peccati and Tudor (2005), Nualart and Ortiz-Latorre (2007), Peccati (2007) and Nourdin and Peccati (...

In this article, we state and prove a central limit theorem for the finite-dimensional laws of the quadratic variations process of certain fractional Brownian sheets. The main tool of this article is a method developed by Nourdin and Nualart in [1818.
Nourdin , I. , and
Nualart , D. 2008 . Central limit theorems for multiple Skorohod integrals. P...

We derive the asymptotic behavior of weighted quadratic variations of fractional Brownian motion $B$ with Hurst index $H=1/4$. This completes the only missing case in a very recent work by I. Nourdin, D. Nualart and C. A. Tudor. Moreover, as an application, we solve a recent conjecture of K. Burdzy and J. Swanson on the asymptotic behavior of the R...

In this paper we give a central limit theorem for the weighted quadratic variations process of a two-parameter Brownian motion. As an application, we ∑ [nt] j=1 |∆i,jY | 2 of a two-show that the discretized quadratic variations ∑ [ns] i=1 parameter diffusion Y = (Y(s,t))(s,t)∈[0,1] 2 observed on a regular grid Gn is an asymptotically normal estimat...

Using integration by parts on Gaussian space
we construct a Stein Unbiased Risk Estimator (SURE)
for the drift of Gaussian processes, based on their
local and occupation times.
By almost-sure minimization of the SURE risk of
shrinkage estimators we derive an estimation and de-noising
procedure for an input signal perturbed by a
continuous-ti...

In recent years infinite-dimensional stochastic analysis methods have been introduced in the field of estimation for Gaussian channels. The aim of this note is to study the application of similar methods to Poisson channels. In particular we show that the conditional mean estimator of a Poisson channel can be expressed as a discrete logarithmic Mal...

In the framework of a nonparametric functional estimation for the drift of a Brownian motion Xt we construct Stein type estimators of the form Xt+DtlogF which are superefficient when F is a superharmonic functional on the Wiener space for the Malliavin derivative D. To cite this article: N. Privault, A. Réveillac, C. R. Acad. Sci. Paris, Ser. I 343...

In this paper we consider a class of BSDE with drivers of quadratic growth, on a stochastic basis generated by continuous local martingales. We first derive the Markov property of a forward-backward system (FBSDE) if the generating martingale is a strong Markov process. Then we establish the dierentiability of a FBSDE with respect to the initial va...

Dans cette thèse nous appliquons le calcul de Malliavin à l'estimation statistique de paramètres de certains processus stochastiques et à l'obtention de théorèmes de la limite centrale pour les variations quadratiques à poids de processus fractionnaires et/ou à deux paramètres ainsi qu'à l'approximation gaussienne de mesures de probabilités multidi...