Grant: Discovery Grants Program - Individual
University of Western Ontario
$16,000.00
Exotic surplus-dependent risk models and their applications
EF 2022-23
Résumé
Quantitative risk management is a central topic in the fields of insurance and finance, where researchers and practitioners seek the advanced analytic tools and computational methods for better identification, characterization, assessment, management and mitigation of the emerging risks. In the insurance industry, it is of utmost importance to develop such quantitative risk management systems for the solvency risk pertaining to the insurer's ability to meet its future financial obligations. My proposed research program is expected to make significant contributions in this research field through the development and application of analytical approaches and computational methodologies in the study of surplus processes with perturbations in its trajectory. More specifically, my research team and I will concentrate on the following three themes: (1) Stochastic modeling and optimal design with surplus-dependent features; (2) Develop and analyze (surplus-dependent) risk measures for insurance risk processes; (3) Discover potential applications in variable annuities. In Theme (1), following the recent trend in the analysis of an insurer's dynamic cash flows, risk models with surplus-dependent features will be designed and examined to meet the various needs of different parties in insurance practice. Theme (2) studies the surplus-dependent risk measures with a special focus on the drawdown related measures, in order to help provide deeper insight into the characteristics of potential hazards and assist in the early detection of extreme risks. We will also build the connections between ruin theory and risk measures via probabilistic analysis. The integrated outcomes from Themes (1) and (2) will improve the quantitative risk management of solvency risk through the innovative design of dynamic strategies and measurement of the exposures over time. Another contribution of my proposed research program is to expand on the application of exotic risk theory and surplus-dependent risk measures to the pricing and risk management of variable annuity, which is the focus of Theme (3). This research will provide innovative insights for researchers and practitioners in the insurance and finance industries, and train HQP who will be prepared to lead in the related research areas.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2019-06219
Name nom
Li, Shu
Department département
Statistical and Actuarial Sciences - Statistical and Actuarial Sciences
Organization id
36
Institution établissement
University of Western Ontario
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2019
Award amount
16000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1508
Committee name en
Mathematics and Statistics
Committee name fr
Mathématiques et statistique
Area of application code
1205
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Mathematical sciences
Area of application fr
Sciences mathématiques
Research subject code
3000
Research subject group en
Statistics and probability
Research subject group fr
Statistique et probabilité
Research subject en
Statistics and probability
Research subject fr
Statistique et probabilité
Installment
inst:4
Partie
1
Nb partie
5
Application title
Exotic surplus-dependent risk models and their applications
Application summary
Quantitative risk management is a central topic in the fields of insurance and finance, where researchers and practitioners seek the advanced analytic tools and computational methods for better identification, characterization, assessment, management and mitigation of the emerging risks. In the insurance industry, it is of utmost importance to develop such quantitative risk management systems for the solvency risk pertaining to the insurer's ability to meet its future financial obligations. My proposed research program is expected to make significant contributions in this research field through the development and application of analytical approaches and computational methodologies in the study of surplus processes with perturbations in its trajectory. More specifically, my research team and I will concentrate on the following three themes: (1) Stochastic modeling and optimal design with surplus-dependent features; (2) Develop and analyze (surplus-dependent) risk measures for insurance risk processes; (3) Discover potential applications in variable annuities. In Theme (1), following the recent trend in the analysis of an insurer's dynamic cash flows, risk models with surplus-dependent features will be designed and examined to meet the various needs of different parties in insurance practice. Theme (2) studies the surplus-dependent risk measures with a special focus on the drawdown related measures, in order to help provide deeper insight into the characteristics of potential hazards and assist in the early detection of extreme risks. We will also build the connections between ruin theory and risk measures via probabilistic analysis. The integrated outcomes from Themes (1) and (2) will improve the quantitative risk management of solvency risk through the innovative design of dynamic strategies and measurement of the exposures over time. Another contribution of my proposed research program is to expand on the application of exotic risk theory and surplus-dependent risk measures to the pricing and risk management of variable annuity, which is the focus of Theme (3). This research will provide innovative insights for researchers and practitioners in the insurance and finance industries, and train HQP who will be prepared to lead in the related research areas.