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Eyal Neuman

Publications and source records attributed to Eyal Neuman.

45 records · Page 3Linked to original sources

Fractional Brownian motion with zero Hurst parameter: a rough volatility viewpoint

Rough volatility models are becoming increasingly popular in quantitative finance. In this framework, one considers that the behavior of the log-volatility process of a financial asset is close to that of a fractional Brownian motion with Hurst parameter around 0.1. Motivated by this, we wish to define a natural and relevant limit for the fractional Brownian motion when $H$ goes to zero. We show that once properly normalized, the fractional Brownian motion converges to a Gaussian random distribution which is very close to a log-correlated random field.

math.PR↗

Pathwise Uniqueness for the Stochastic Heat Equation with Hölder Continuous Drift and Noise Coefficients

We study the solutions of the stochastic heat equation with multiplicative space-time white noise. We prove a comparison theorem between the solutions of stochastic heat equations with the same noise coefficient which is Hölder continuous of index $γ>3/4$, and drift coefficients that are Lipschitz continuous. Later we use the comparison theorem to get sufficient conditions for the pathwise uniqueness for solutions of the stochastic heat equation, when both the white noise and the drift coefficients are Hölder continuous.

math.PR↗

On Uniqueness and Blowup Properties for a Class of Second Order SDEs

As the first step for approaching the uniqueness and blowup properties of the solutions of the stochastic wave equations with multiplicative noise, we analyze the conditions for the uniqueness and blowup properties of the solution $(X_t,Y_t)$ of the equations $dX_t= Y_tdt$, $dY_t = |X_t|^αdB_t$, $(X_0,Y_0)=(x_0,y_0)$. In particular, we prove that solutions are nonunique if $0<α<1$ and $(x_0,y_0)=(0,0)$ and unique if $1/2<α<1$ and $(x_0,y_0)\neq(0,0)$. We also show that blowup in finite time holds if $α>1$ and $(x_0,y_0)\neq(0,0)$.

math.PR↗

On the Maximal Displacement of Subcritical Branching Random Walks

We study the maximal displacement of a one dimensional subcritical branching random walk initiated by a single particle at the origin. For each $n\in\mathbb{N},$ let $M_{n}$ be the rightmost position reached by the branching random walk up to generation $n$. Under the assumption that the offspring distribution has a finite third moment and the jump distribution has mean zero and a finite probability generating function, we show that there exists $ρ>1$ such that the function \[ g(c,n):=ρ^{cn} P(M_{n}\geq cn), \quad \mbox{for each }c>0 \mbox{ and } n\in\mathbb{N}, \] satisfies the following properties: there exist $0<\underlineδ\leq \overlineδ < {\infty}$ such that if $c<\underlineδ$, then $$ 0<\liminf_{n\rightarrow\infty} g (c,n)\leq \limsup_{n\rightarrow\infty} g (c,n) {\leq 1}, $$ while if $c>\overlineδ$, then \[ \lim_{n\rightarrow\infty} g (c,n)=0. \] Moreover, if the jump distribution has a finite right range $R$, then $\overlineδ < R$. If furthermore the jump distribution is "nearly right-continuous", then there exists $κ\in (0,1]$ such that $\lim_{n\rightarrow \infty}g(c,n)=κ$ for all $c<\underlineδ$. We also show that the tail distribution of $M:=\sup_{n\geq 0}M_{n}$, namely, the rightmost position ever reached by the branching random walk, has a similar exponential decay (without the cutoff at $\underlineδ$). Finally, by duality, these results imply that the maximal displacement of supercritical branching random walks conditional on extinction has a similar tail behavior.

math.PR↗

Optimal Portfolio Liquidation in Target Zone Models and Catalytic Superprocesses

We study optimal buying and selling strategies in target zone models. In these models the price is modeled by a diffusion process which is reflected at one or more barriers. Such models arise for example when a currency exchange rate is kept above a certain threshold due to central bank intervention. We consider the optimal portfolio liquidation problem for an investor for whom prices are optimal at the barrier and who creates temporary price impact. This problem will be formulated as the minimization of a cost-risk functional over strategies that only trade when the price process is located at the barrier. We solve the corresponding singular stochastic control problem by means of a scaling limit of critical branching particle systems, which is known as a catalytic superprocess. In this setting the catalyst is a set of points which is given by the barriers of the price process. For the cases in which the unaffected price process is a reflected arithmetic or geometric Brownian motion with drift, we moreover give a detailed financial justification of our cost functional by means of an approximation with discrete-time models.

q-fin.PM↗

The Multifractal Nature of Volterra-Lévy Processes

We consider the regularity of sample paths of Volterra-Lévy processes. These processes are defined as stochastic integrals $$ M(t)=\int_{0}^{t}F(t,r)dX(r), \ \ t \in \mathds{R}_{+}, $$ where $X$ is a Lévy process and $F$ is a deterministic real-valued function. We derive the spectrum of singularities and a result on the 2-microlocal frontier of $\{M(t)\}_{t\in [0,1]}$, under regularity assumptions on the function $F$.

math.PR↗

Pathwise Uniqueness of the Stochastic Heat Equations with Spatially Inhomogeneous White Noise

We study the solutions of the stochastic heat equation driven by spatially inhomogeneous multiplicative white noise based on a fractal measure. We prove pathwise uniqueness for solutions of this equation when the noise coefficient is Hölder continuous of index $γ>1-\fracη{2(η+1)}$. Here $η\in(0,1)$ is a constant that defines the spatial regularity of the noise.

math.PR↗

Monte Carlo for estimating exponential convolution

In this note we study the numerical stability problem that may take place when calculating the cumulative distribution function of the {\it Hypoexponential} random variable. This computation is extensively used during the execution of Monte Carlo network reliability estimation algorithms. In spite of the fact that analytical formulas are available, they can be unstable in practice. This instability occurs frequently when estimating very small failure probabilities $(10^{-30}-10^{-40})$ that can happen for example while estimating the unreliability of telecommunication systems. In order to address this problem, we propose a simple unbiased estimation algorithm that is capable of handling a large number of variables. We show that the proposed estimator has a bounded relative error and that it compares favorably with other existing methods.

stat.AP↗

Sample Path Properties of Volterra Processes

We consider the regularity of sample paths of Volterra processes. These processes are defined as stochastic integrals $$ M(t)=\int_{0}^{t}F(t,r)dX(r), \ \ t \in \mathds{R}_{+}, $$ where $X$ is a semimartingale and $F$ is a deterministic real-valued function. We derive the information on the modulus of continuity for these processes under regularity assumptions on the function $F$ and show that $M(t)$ has "worst" regularity properties at times of jumps of $X(t)$. We apply our results to obtain the optimal Hölder exponent for fractional Lévy processes.

math.PR↗