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arXiv 1604.02307math.PR
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Levy半平稳过程的极限理论

On limit theory for Levy semi-stationary processes

Andreas Basse-O'Connor, Claudio Heinrich, Mark Podolskij

摘要:

本文给出了Lévy半平稳过程在填充渐近条件下幂变差的几个极限定理。Lévy半平稳过程,是一个一维的边界场的模拟,是一个带有乘法随机分量的移动平均型过程,通常被称为波动率或不稳定性。从数学的角度来看,这项工作扩展了[14]中研究的渐近理论,其中作者导出了Lévy驱动的移动平均线的平稳增量的$k$阶增量的极限理论。渐近结果在很大程度上依赖于给定的增量的顺序之间的相互作用,所考虑的功率$p>0$,驱动纯跳Lévy过程$L$的Blumenthal-Getoor指数$β\in (0,2)$和由功率$α$确定的$0$的核函数$g$的行为。本文将研究具有随机波动率/随机波动率分量的Lévy半平稳过程的一阶渐近理论,并给出概率结果的一些统计应用。

英文摘要:

In this paper we present some limit theorems for power variation of Lévy semi-stationary processes in the setting of infill asymptotics. Lévy semi-stationary processes, which are a one-dimensional analogue of ambit fields, are moving average type processes with a multiplicative random component, which is usually referred to as volatility or intermittency. From the mathematical point of view this work extends the asymptotic theory investigated in [14], where the authors derived the limit theory for $k$th order increments of stationary increments Lévy driven moving averages. The asymptotic results turn out to heavily depend on the interplay between the given order of the increments, the considered power $p>0$, the Blumenthal--Getoor index $β\in (0,2)$ of the driving pure jump Lévy process $L$ and the behaviour of the kernel function $g$ at $0$ determined by the power $α$. In this paper we will study the first order asymptotic theory for Lévy semi-stationary processes with a random volatility/intermittency component and present some statistical applications of the probabilistic results.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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