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Lucia Caramellino

Publications and source records attributed to Lucia Caramellino.

26 records · Page 2Linked to original sources
arXiv2015

On Sharp Large Deviations for the bridge of a general Diffusion

We provide sharp Large Deviation estimates for the probability of exit from a domain for the bridge of a $d$-dimensional general diffusion process $X$, as the conditioning time tends to $0$. This kind of results is motivated by applications to numerical simulation. In particular we investigate the influence of the drift $b$ of $X$. It turns out that the sharp asymptotics for the exit time probability are independent of the drift, provided $b$ enjoyes a simple condition that is always satisfied in dimension $1$. On the other hand, we show that the drift can be influential if this assumption is not satisfied. }

math.PR↗
arXiv2013

On the distance between probability density functions

We give estimates of the distance between the densities of the laws of two functionals $F$ and $G$ on the Wiener space in terms of the Malliavin-Sobolev norm of $F-G.$ We actually consider a more general framework which allows one to treat with similar (Malliavin type) methods functionals of a Poisson point measure (solutions of jump type stochastic equations). We use the above estimates in order to obtain a criterion which ensures that convergence in distribution implies convergence in total variation distance; in particular, if the functionals at hand are absolutely continuous, this implies convergence in $L^{1}$ of the densities.

math.PR↗
arXiv2012

Regularity of probability laws by using an interpolation method

We study the problem of the existence and regularity of a probability density in an abstract framework based on a "balancing" with approximating absolutely continuous laws. Typically, the absolutely continuous property for the approximating laws can be proved by standard techniques from Malliavin calculus whereas for the law of interest no Malliavin integration by parts formulas are available. Our results are strongly based on the use of suitable Hermite polynomial series expansions and can be merged into the theory of interpolation spaces. We then apply the results to the solution to a stochastic differential equation with a local Hörmander condition or to the solution to the stochastic heat equation, in both cases under weak conditions on the coefficients relaxing the standard Lipschitz or Hölder continuity requests.

math.PR↗
arXiv2012

Tubes estimates for diffusion processes under a local Hörmander condition of order one

We consider a diffusion process $X_{t}$ and a skeleton curve $x_{t}(ϕ)$ and we give a lower bound for $P(\sup_{t\leq T}d(X_{t},x_{t}(ϕ))\leq R)$. This result is obtained under the hypothesis that the strong Hörmander condition of order one (which involves the diffusion vector fields and the first Lie brackets) holds in every point $x_{t}(ϕ),0\leq t\leq T.$ Here $d$ is a distance which reflects the non isotropic behavior of the diffusion process which moves with speed $\sqrt{t}$ in the directions of the diffusion vector fields but with speed $t$ in the directions of the first order Lie brackets. We prove that $d$ is locally equivalent with the standard control metric $d_{c}$ and that our estimates hold for $d_{c}$ as well.

math.PR↗
arXiv2011

Power Series Representations for European Option Prices under Stochastic Volatility Models

In the context of stochastic volatility models, we study representation formulas in terms of expectations for the power series' coefficients associated to the call price-function. As in a recent paper by Antonelli and Scarlatti the expansion is done w.r.t. the correlation between the noises driving the underlying asset price process and the volatility process. We first obtain expressions for the power series' coefficients from the generalized Hull and White formula obtained by Elisa Alòs. Afterwards, we provide representations turning out from the approach for the sensitivity problem tackled by Malliavin calculus techniques, and these allow to handle not only vanilla options. Finally, we show the numerical performance of the associated Monte Carlo estimators for several stochastic volatility models.

q-fin.PR↗
arXiv2010

Riesz transform and integration by parts formulas for random variables

We use integration by parts formulas to give estimates for the $L^p$ norm of the Riesz transform. This is motivated by the representation formula for conditional expectations of functionals on the Wiener space already given in Malliavin and Thalmaier. As a consequence, we obtain regularity and estimates for the density of non degenerated functionals on the Wiener space. We also give a semi-distance which characterizes the convergence to the boundary of the set of the strict positivity points for the density.

math.PR↗