arXiv subjects

Grigori Jasnovidov

Publications and source records attributed to Grigori Jasnovidov.

8 recordsLinked to original sources

arXiv2024

Parisian Ruin for Insurer and Reinsurer under Quota-Share Treaty

In this contribution we study asymptotics of the simultaneous Parisian ruin probability of a two-dimensional fractional Brownian motion risk process. This risk process models the surplus processes of an insurance and a reinsurance companies, where the net loss is distributed between them in given proportions. We also propose an approach for simulation of Pickands and Piterbarg constants appearing in the asymptotics of the ruin probability.

math.PR↗

arXiv2023

Fractional Brownian Motion Ruin Model with Random Inspection Time

In this contribution we study the asymptotics of \begin{eqnarray*} P(\exists t\ge 0 : B_H(L(t))-cL(t)>u), \quad u \to \infty, \end{eqnarray*} where $B_H, H\in (0,1)$ is a fractional Brownian motion, $L(t)$ is a non-negative pure jumps Lévy process independent of $B_H$, $c>0$.

math.PR↗

arXiv2023

On the speed of convergence of discrete Pickands constants to continuous ones

In this manuscript, we address open questions raised by Dieker \& Yakir (2014), who proposed a novel method of estimation of (discrete) Pickands constants $\mathcal{H}^δ_α$ using a family of estimators $ξ^δ_α(T), T>0$, where $α\in(0,2]$ is the Hurst parameter, and $δ\geq0$ is the step-size of the regular discretization grid. We derive an upper bound for the discretization error $\mathcal{H}_α^0 - \mathcal{H}_α^δ$, whose rate of convergence agrees with Conjecture 1 of Dieker & Yakir (2014) in case $α\in(0,1]$ and agrees up to logarithmic terms for $α\in(1,2)$. Moreover, we show that all moments of $ξ_α^δ(T)$ are uniformly bounded and the bias of the estimator decays no slower than $\exp\{-\mathcal CT^α\}$, as $T$ becomes large.

math.PR↗

arXiv2023

On the speed of convergence of Piterbarg constants

In this paper we derive an upper bound for the difference between the continuous and discrete Piterbarg constants. Our result allows us to approximate the classical Piterbarg constants by their discrete counterparts using Monte Carlo simulations with an explicit error rate

math.PR↗

arXiv2022

Extremes of Reflecting Gaussian Processes on Discrete Grid

For $\{X(t), t \in G_δ\}$ a centered Gaussian process with stationary increments and a.s. sample paths on a discrete grid $G_δ=\{0,δ,2δ, ...\}$, where $δ>0$, we investigate the stationary reflected process $$Q_{δ,X}(t) = \sup\limits_{s\in [t,\infty)\cap G_δ}\big( X(s)-X(t)-c(s-t)\big), \ t \in G_δ$$ with $c>0$. We derive the exact asymptotics of $$\mathbb P\{\sup\limits_{t\in [0,T]\cap G_δ} Q_{δ,X}(t)>u\} \quad \text{and} \quad \mathbb P\{\inf\limits_{t\in [0,T]\cap G_δ} Q_{δ,X}(t)>u\},$$ as $u\to\infty$, with $T>0$. It appears that $φ=\lim_{u\to\infty} \frac{σ^2(u)}{u}$ determines the asymptotics, leading to three qualitatively different scenarios: $φ=0$, $φ\in(0,\infty)$ and $φ=\infty$.

math.PR↗

arXiv2021

Sojourn Ruin of a Two-Dimensional Fractional Brownian Motion Risk Process

This paper derives the asymptotic behavior of $$\mathbb{P} \{ \int\limits_0^\infty \mathbb{I}\Big(B_H(s)-c_1s>q_1u, B_H(s)-c_2s>q_2u\Big)ds>T_u\},\quad u \to \infty,$$ where $B_H$ is a fractional Brownian motion, $c_1,c_2,q_1,q_2>0,\ H \in (0,1), \ T_u \ge 0$ is a measurable function and $\mathbb{I}(\cdot)$ is the indicator function.

math.PR↗

arXiv2020

Simultaneous ruin probability for two-dimensional fractional Brownian motion risk process over discrete grid, with supplements

This paper derives the asymptotic behavior of the following ruin probability $$P\{\exists t \in G(δ):B_H(t)-c_1t>q_1u,B_H(t)-c_2t>q_2u\}, \ \ \ u \rightarrow \infty,$$ where $B_H$ is a standard fractional Brownian motion, $c_1,q_1,c_2,q_2>0$ and $G(δ)$ denotes a regular grid $\{0,δ, 2δ,...\}$ for some $δ>0$. The approximation depends on $H$, $δ$ (only when $H\leq 1/2$) and the relations between parameters $c_1,q_1,c_2,q_2$.

math.PR↗

arXiv2020

Approximation of ruin probability and ruin time in discrete Brownian risk models

We analyze the classical Brownian risk models discussing the approximation of ruin probabilities (classical, γ-reflected, Parisian and cumulative Parisian) for the case that ruin can occur only on specific discrete grids. A practical and natural grid of points is for instance G(1) = {0,1,2,...}, which allows us to study the probability of the ruin on the first day, second day, and so one. For such a discrete setting, there are no explicit formulas for the ruin probabilities mentioned above. In this contribution we derive accurate approximations of ruin probabilities for uniform grids by letting the initial capital to grow to infinity.

math.PR↗