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Grant: Discovery Grants Program - Individual

Toronto Metropolitan University

$23,000.00

Some Topics in Robust Mathematical Finance

FY 2024-25

Summary
Model uncertainty is pervasive in finance and economics, and has been gaining more and more attention in recent years. I propose to study the two fundamental subjects in mathematical finance, Pricing and Risk Measurement, under uncertainty, using the robust approach, which is currently a leading research trend in mathematical finance. 1. Robust pricing theory. The goal is to establish robust versions of the Fundamental Theorem of Asset Pricing (FTAP) and the Superhedging Theorem (ST), which are cornerstones of the classical mathematical pricing theory. Although many efforts have been devoted to this area by various researchers, a relatively comprehensive theory is still to be established. Goals: - establish a general version of FTAP and ST in the robust setting; - systematically investigate capacitary function spaces. 2. Risk measurement under uncertainty. The goal is to study how risk measurement is affected by uncertainty and how to take uncertainty into account in risk measurement. Goals: - study risk measures on capacitary function spaces; - determine risk aggregation bounds under dependence uncertainty subject to correlation constraint.
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2018-04179
Name nom
Gao, Niushan
Department département
Mathematics
Organization id
43
Institution établissement
Toronto Metropolitan University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2018
Award amount
23000
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
405
Area of application group en
Environment
Area of application group fr
Environnement
Area of application en
Modelling and mathematical simulation of natural processes
Area of application fr
Modélisation et simulation mathématique des processus naturels
Research subject code
2960
Research subject group en
Applied mathematics
Research subject group fr
Mathématiques appliquées
Research subject en
Mathematical modelling
Research subject fr
Modélisation mathématique
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Some Topics in Robust Mathematical Finance
Keywords
robust risk measures; robust pricing and hedging; model uncertainty; dependence uncertainty; capacitary function spaces
Application summary
Model uncertainty is pervasive in finance and economics, and has been gaining more and more attention in recent years. I propose to study the two fundamental subjects in mathematical finance, Pricing and Risk Measurement, under uncertainty, using the robust approach, which is currently a leading research trend in mathematical finance. 1. Robust pricing theory. The goal is to establish robust versions of the Fundamental Theorem of Asset Pricing (FTAP) and the Superhedging Theorem (ST), which are cornerstones of the classical mathematical pricing theory. Although many efforts have been devoted to this area by various researchers, a relatively comprehensive theory is still to be established. Goals: - establish a general version of FTAP and ST in the robust setting; - systematically investigate capacitary function spaces. 2. Risk measurement under uncertainty. The goal is to study how risk measurement is affected by uncertainty and how to take uncertainty into account in risk measurement. Goals: - study risk measures on capacitary function spaces; - determine risk aggregation bounds under dependence uncertainty subject to correlation constraint.
Toronto Metropolitan University - $23,000 Grant (2024… | Canada Spends