發(fā)布時間：2018-05-25 02:18

  本文選題：重尾分布 + 負相依�。� 參考：《西北師范大學》2013年碩士論文

【摘要】：自從上個世紀60年代以來,重尾分布在應用概率領域,特別是在分支過程,排隊論及風險理論等領域有著廣泛的應用.在保險業(yè)中,許多重大的風險都是由一些大額索賠造成的,如火險,風暴險和地震險等.由于重尾分布能刻畫大額索賠這一特性.因此,人們有必要對重尾分布發(fā)生的規(guī)律進行研究,這對保險經(jīng)營過程中的風險評估與預測提供理論工具.同時,在早期的保險風險中,人們將賠付額以及索賠發(fā)生的間隔時間均視為獨立同分布的隨機變量.然而,在現(xiàn)實生活中,它們之間存在著某種相依關系. 本文仍然以重尾分布為主要對象,討論了相依索賠下風險模型的精細大偏差及其破產(chǎn)概率的漸近性.在第一章中,本文介紹了相關的重尾分布,相依的概念以及重尾相依隨機變量的研究現(xiàn)狀.在第二章中,構建了基于客戶到來風險模型,通過示性函數(shù)將賠付額精確的表達出來.在索賠額隨機變量為負相依且有共同分布屬于L∩D族下,討論了該風險模型損失過程的部分和和隨機和的精細大偏差.更進一步地,得到了該風險模型盈余過程的有限時間破產(chǎn)概率的漸近關系.大偏差概率可以應用于大額索賠保險的情形下,尤其是再保險.值得指出的是,隨機和精細大偏差的結果對于一些風險預測的評估有非常重要作用.如大型保險公司投資組合的總索賠風險的條件尾期望和價值.在風險理論中,研究破產(chǎn)概率可以為保險公司的決策者提供一個早期的風險警示,也是衡量一個保險公司及其所經(jīng)營某個險種的金融風險的極其重要的尺度.因此,風險模型破產(chǎn)概率的研究對保險公司的經(jīng)營有非常重要的指導意義.第三章中,索賠額為負相依同分布的重尾隨機變量,引進一個可測函數(shù),得到索賠額和索賠時間間隔的相依關系.假設索賠額分布為L∩D族,建立了有限時間破產(chǎn)概率的弱漸近等價式.進而,得到了連續(xù)時間的常利息力更新風險模型的結果.由破產(chǎn)概率的漸近關系得出有限時間破產(chǎn)概率對于索賠額的負相依結構是不敏感的.
[Abstract]:Since the 1960s, the heavy-tailed distribution has been widely used in the fields of applied probability, especially in branching process, queuing and risk theory. In the insurance industry, many major risks are caused by large claims, such as fire, storm and earthquake risks. Because the heavy-tailed distribution can describe the characteristics of large claims. Therefore, it is necessary to study the occurrence of heavy-tailed distribution, which provides a theoretical tool for risk assessment and prediction in the process of insurance management. At the same time, in the early insurance risk, the amount of compensation and the interval between claims are regarded as independent and distributed random variables. However, in real life, there is a certain relationship between them. In this paper, we still take the heavy-tailed distribution as the main object, and discuss the fine large deviation of risk model and the asymptotic property of ruin probability under the dependent claim. In the first chapter, we introduce the concepts of heavy-tailed distribution, dependency and the research status of heavy-tailed random variables. In the second chapter, the customer arrival risk model is constructed, and the exact expression of the compensation amount is obtained by means of the indicative function. Under the condition that the random variables of the claim amount are negative dependent and have a common distribution, the fine large deviations of the partial sum and the random sum of the loss process of the risk model are discussed. Furthermore, the asymptotic relation of the finite time ruin probability of the risk model surplus process is obtained. Large deviation probability can be applied to large claim insurance, especially reinsurance. It is worth noting that the results of random and fine large deviations are very important for the assessment of some risk forecasts. Such as large insurance company portfolio of total claim risk conditions end expectation and value. In the risk theory, the study of bankruptcy probability can provide an early risk warning for the policy makers of insurance companies, and it is also an extremely important measure to measure the financial risk of an insurance company and its type of insurance. Therefore, the study of the ruin probability of risk model has a very important guiding significance for the management of insurance companies. In chapter 3, the claim amount is a negative dependent distribution of heavy-tailed random variable. A measurable function is introduced to obtain the dependence between the claim amount and the claim time interval. The weakly asymptotically equivalent formula for the ruin probability of finite time is established, assuming that the claim amount is distributed as L 鈮，

本文編號：1931635