The product of dependent random variables with applications to a discrete-time risk model

preprint2016arXivOpen access

Abstract

Let XX be a real valued random variable with an unbounded distribution FF and let YY be a nonnegative valued random variable with a unbounded distribution GG, which satisfy that \begin{eqnarray*} P(X>x|Y=y)\sim h(y)P(X>x) \end{eqnarray*} holds uniformly for y≥0y\geq0 as x→∞x\to \infty. Under the condition that G‾(bx)=o(H‾(x))\overline{G}(bx)=o(\overline H(x)) holds for all constant b>0b>0, we proved that F∈L(γ)F\in\mathcal{L}(γ) for some γ≥0γ\geq 0 implied H∈L(γ/βG)H\in \mathcal{L}(γ/β_G) and that F∈S(γ)F\in\mathcal{S}(γ) for some γ≥0γ\geq 0 implied H∈S(γ/βG)H\in \mathcal{S}(γ/β_G), where HH is the distribution of the product XYXY, and βGβ_G is the right endpoint of GG, that is, βG=sup⁡{y: G(y)<1}∈(0,∞],β_G=\sup\{y:~G(y)<1\}\in (0,\infty], and when βG=∞β_G=\infty, γ/βGγ/β_G is understood as 0. Furthermore, in a discrete-time risk model in which the net insurance loss and the stochastic discount factor are equipped with a dependence structure, a general asymptotic formula for the finite-time ruin probability is obtained when the net insurance loss has a subexponential tail.

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