arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1111.0537math.STstat.TH
收藏

线性过程的精确中偏差和大偏差

Exact Moderate and Large Deviations for Linear Processes

Magda Peligrad, Hailin Sang, Yunda Zhong, Wei Biao Wu

摘要:

大中偏差概率在保险、风险分析等许多应用领域中起着重要的作用。本文研究了具有独立新息的线性过程的非对数形式的精确中偏差和大偏差渐近性。我们分析的线性过程是一般的,因此它们包括长记忆的情况。我们给出了一个渐近表示的概率尾部的规范化的总和,并指定的区域中,它可以近似为一个标准正态分布或边缘分布的创新过程。然后将结果应用于回归估计、移动平均、分数积分过程、具有规则变化指数的线性过程和线性过程的函数。我们还考虑了风险理论和金融学中的基本量--在险价值和期望损失的计算。

英文摘要:

Large and moderate deviation probabilities play an important role in many applied areas, such as insurance and risk analysis. This paper studies the exact moderate and large deviation asymptotics in non-logarithmic form for linear processes with independent innovations. The linear processes we analyze are general and therefore they include the long memory case. We give an asymptotic representation for probability of the tail of the normalized sums and specify the zones in which it can be approximated either by a standard normal distribution or by the marginal distribution of the innovation process. The results are then applied to regression estimates, moving averages, fractionally integrated processes, linear processes with regularly varying exponents and functions of linear processes. We also consider the computation of value at risk and expected shortfall, fundamental quantities in risk theory and finance.

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。

↑