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Measures and Models for Dependent Actuarial Risks

Measures and Models for Dependent Actuarial Risks
相关精算风险的衡量标准和模型
批准号:
RGPIN-2015-05447
负责人:
Mailhot, Mélina
金额:
$1.17万
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:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

项目摘要

项目成果

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中文摘要
翻译
我的研究方向是精算科学中的风险管理领域。投资组合管理的一个主要缺点是系统地考虑降低风险。由于监管或会计规则的原因,投资组合的所有风险不可能总是被汇总。此外,即使它们可以存在,也可能需要单独考虑它们或在同类群体中考虑它们,以便进行风险比较,或进行更准确和保守的保护。在我的五年研究计划中,我将通过一个多元的框架来研究这个问题。后者最近被引入精算科学领域,用于风险测量。它在加拿大和大多数发达国家的学者和从业者中越来越受欢迎。*******我计划开发封闭形式的表达式,研究多变量风险度量的性质。将开发一种新的多变量风险度量,即多变量风险截尾值(mTTVaR),以测量特定封闭概率范围内的损失。基于多变量数据的自然风险统计将被重新研究,因为基于总风险的夫妇排序限制了它的使用。我将研究不同的顺序,以提供更易于处理、稳健、可靠和实用的统计数据。我将开发多元置信区域的估计器,并将它们与多元接受集进行比较。我们将区分具有非常相似定义的实际多变量风险度量,除了考虑多变量集的方式不同,提供不同的统计数据。我还打算用精算科学中常见的多变量随机过程和分布提供多变量风险度量的封闭形式表达式。基于多元风险尾值和mTTVaR的精算模型适用性的统计检验将被开发和研究。******我的计划的第二部分是致力于多元风险措施的应用。我将基于金融和精算的观点,研究使用多变量风险度量对保险、再保险和金融产品定价的影响。我将研究一些特定的原则,以优化联合互惠再保险合同,如同时设置份额份额和调整因子。优化将基于联合生存和盈利分配。最后,我们将推广多元再保险合同的结果。保护风险不受同类依赖风险组合的影响有几个用途。它允许为每个风险分配价值,对它们进行比较,评估每个业务线,并为风险管理目的或偿付能力要求分配资本。******挑战是创新和原创的。他们将为研究生、学者和从业人员提供有趣的研究项目。
英文摘要
My proposed research lies in the area of risk management in actuarial science. A major drawback of portfolio management is the systematic consideration of risk mitigation. All risks of a portfolio cannot always be aggregated, because of regulation or accounting rules. Moreover, even if they can be, it might be desirable to consider them individually or in homogeneous groups, for risk comparison, or for more accurate and conservative protections. In my five-year research program, I will investigate this issue through a multivariate framework. The latter has recently been introduced in the actuarial science field for risk measurement. It is gaining popularity, both with academics and practitioners in Canada, and across most developed countries. *******I plan on developing closed-form expressions and studying properties of multivariate risk measures. A new multivariate risk measure, multivariate Truncated Tail Value-at-Risk (mTTVaR) will be developed, to measure losses in a particular closed range of probabilities. Multivariate data-based natural risk statistics will be reinvestigated, since couple ordering based on aggregate risks restricts its use. I will study different ordrings to provide statistics that are more tractable, robust, reliable and practical. I will develop estimators for multivariate confidence regions and compare them with multivariate acceptance sets. We will distinguish actual multivariate risk measures that have very similar definitions, exept for differences in the way multivariate sets are being considered, providing different statistics. I also intend provide closed-form expressions of multivariate risk measures with common multivariate stochastic processes and distributions in actuarial science. A statistical test for the suitability of actuarial models, based on multivariate Tail Value-at-Risk and mTTVaR will be developed and studied.******A second part of my program is dedicated to the application of multivariate risk measures. I will study the impact of using multivariate risk measures on the pricing of insurance, reinsurance and financial products, based on financial and actuarial points of view. I will investigate some particular principles, to optimize joint reciprocal reinsurance contracts, e.g. when both the quota-share and adjustment factors are set simultaneously. The optimization will be based on the joint survival and profitability distributions. Finally, we will extend the results for a multivariate reinsurance contract. Protecting risks from homogeneous classes of portfolios of dependent risks is useful for several purposes. It allows to allocate values to each risk, to compare them, to evaluate each business line and to allocate capital for risk management purposes or solvency requirements.******The challenges are innovative and original. They will provide interesting research projects for graduate students, academics and practitionners.
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Measures and Models for Dependent Actuarial Risks
  • 批准号:
    RGPIN-2015-05447
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.17万
  • 财政年份:
    2022
  • 负责人:
    Mailhot, Mélina
  • 依托单位:
Measures and Models for Dependent Actuarial Risks
  • 批准号:
    RGPIN-2015-05447
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.17万
  • 财政年份:
    2021
  • 负责人:
    Mailhot, Mélina
  • 依托单位:
Measures and Models for Dependent Actuarial Risks
  • 批准号:
    RGPIN-2015-05447
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.17万
  • 财政年份:
    2020
  • 负责人:
    Mailhot, Mélina
  • 依托单位:
Measures and Models for Dependent Actuarial Risks
  • 批准号:
    RGPIN-2015-05447
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.17万
  • 财政年份:
    2019
  • 负责人:
    Mailhot, Mélina
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
新型手性NAD(P)H Models合成及生化模拟