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Risk processes analyzed using fluid queues

Risk processes analyzed using fluid queues
使用流动队列分析风险流程
批准号:
327040-2006
负责人:
Badescu, AndreiLucian
金额:
$0.95万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2008
资助国家:
加拿大
项目状态:
已结题
起止时间:
2008-01-01 至 2009-12-31

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中文摘要
翻译
作为保险数学的一部分,集体风险理论研究与保险业务相关的随机模型。在这样的模型中,索赔的发生是由一个点过程和保险公司支付的金额,由于索赔作为一个随机变量。在这个随机框架内,而不是确定性的世界观,风险是一个关键概念。破产概率、破产前的盈余和破产时的赤字只是衡量保险业务风险的一些量。在大多数真实的情况下,能够预测某些未来事件的结果是令人感兴趣的。在保险中,能够预测索赔的频率和索赔成本是非常重要的。需要数学模型来帮助做出这些预测。然而,模型越真实,分析的难度就越大。特别是,这项研究将集中在一个数学方程,其解决方案是非常复杂的评估分析。类似的方程出现在许多其他应用的概率模型中,如扩散理论。因此,其他研究领域的一些结果可以应用于风险理论,反之亦然。我将应用于研究这种复杂模型的方法是概率导向的,而不是分析导向的。流体流动的首次通过时间,是广泛的研究,在风险模型中,以及将被应用到泡沫理论。将与现有的分析方法进行比较,主要通过计算机密集型计算,通过数值分析说明差异。
英文摘要
Collective risk theory, as a part of insurance mathematics, deals with stochastic models pertinent to an insurance business. In such a model, the occurrence of claims is described by a point process and the amount of money that an insurer has to pay due to a claim as a random variable. Within this stochastic framework, rather than a deterministic view of the world, risk is a key concept. The probability of ruin, the surplus prior to ruin and the deficit at the time of ruin are just some of the quantities that measure the risk of an insurance business. In most of the real situations it is of interest to be able to predict the outcome of some future events. In insurance, it is of huge importance to be able to predict the frequency of the claims and also the claim costs. Mathematical models are needed to help to make these predictions. However, the more realistic the model, the more difficult it is to analyze. In particular, this research will focus on the analysis of a mathematical equation whose solution is very complicated to evaluate. Similar equations appear in many other applied probability models such as queueing theory. Consequently, some of the results from other areas of research may be applied in Risk Theory and vice versa. The methods that I will apply to study such complicated models are rather probabilistically oriented than analytically oriented. First passage times for fluid flows that are extensively studied in queueing theory will be applied to the risk models as well. Comparison with the existing analytical approaches will be carried out, the differences being illustrated via numerical analysis primarily through computer-intensive calculations.
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Joint Prediction of Multiple Waiting Times with Recurrent Neural Nets
  • 批准号:
    521890-2017
  • 项目类别:
    Engage Grants Program
  • 资助金额:
    $1.82万
  • 财政年份:
    2017
  • 负责人:
    Badescu, AndreiLucian
  • 依托单位:
Topics in collective risk theory
  • 批准号:
    327040-2009
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.38万
  • 财政年份:
    2013
  • 负责人:
    Badescu, AndreiLucian
  • 依托单位:
Topics in collective risk theory
  • 批准号:
    327040-2009
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.38万
  • 财政年份:
    2012
  • 负责人:
    Badescu, AndreiLucian
  • 依托单位:
Topics in collective risk theory
  • 批准号:
    327040-2009
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.38万
  • 财政年份:
    2011
  • 负责人:
    Badescu, AndreiLucian
  • 依托单位:
国内基金
海外基金
Submesoscale Processes Associated with Oceanic Eddies
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    160万元
  • 批准年份:
    2022
  • 负责人:
    董昌明
  • 依托单位: