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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:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31

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中文摘要
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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.
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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