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Grant: Discovery Grants Program - Individual

Concordia University

$12,000.00

Stochastic dynamics in financial modeling

FY 2011-12

Summary
In modeling financial variables mathematically it is important to consider dynamics which lead to tractable solutions while at the same time capture qualitative features of empirical data. The proposed research program involves the study of various stochastic equations, their properties, and their application to modeling in finance. In particular we shall focus on the pricing and hedging of various term-structure derivatives, commodity contracts, default (credit) risk, and insurance products. Attention shall also be given to the foundations and analytic tools necessary to implement the models effectively. The main class of stochastic equations to be considered are forward-backward stochastic differential equations (FBSDEs, for short). A FBSDE is a coupled system of stochastic equations of which certain components evolve forward in time from an initial condition and other components evolve backward in time from a random terminal condition. Several problems in the literature have been solved by characterizing financial models in terms of FBSDEs. We plan to consider various new models for factors of the economy and derivative securities in terms of FBSDEs that are more general than those previously considered and better capture qualitative features of observed financial data. We shall first incorporate spikes or jumps in the price processes to model the unpredictable events that traditional financial models do not allow. A price process that allows parameters to switch between a finite number of values, modeling a change in financial or economic fundamentals over time, is called a regime-switching model. To better model changes in financial or economic conditions over time we plan to incorporate regime-switching in the dynamics for the factors of the economy and allow these to influence price processes of assets, interest rates, and commodities. Innovative new numerical methods for solving FBSDEs shall also be developed to allow our theoretical results to be applied by practitioners and industry professionals.
Program
Discovery Grants Program - Individual
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
341777-2010
Name nom
Hyndman, Cody
Department département
Mathematics and Statistics
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2011
Competition year année de concours
2010
Award amount
12000
Program id
RGPIN
Program nane en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1508
Committee name en
Mathematics and Statistics
Committee name fr
Mathématiques et statistique
Area of application code
1200
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Advancement of knowledge
Area of application fr
Avancement des connaissances
Research subject code
3007
Research subject group en
Statistics and probability
Research subject group fr
Statistique et probabilité
Research subject en
Stochastic processes
Research subject fr
Processus stochastiques
Partie
2
Nb partie
5
Application title
Stochastic dynamics in financial modeling
Keyword
NSERC
Application summary
In modeling financial variables mathematically it is important to consider dynamics which lead to tractable solutions while at the same time capture qualitative features of empirical data. The proposed research program involves the study of various stochastic equations, their properties, and their application to modeling in finance. In particular we shall focus on the pricing and hedging of various term-structure derivatives, commodity contracts, default (credit) risk, and insurance products. Attention shall also be given to the foundations and analytic tools necessary to implement the models effectively. The main class of stochastic equations to be considered are forward-backward stochastic differential equations (FBSDEs, for short). A FBSDE is a coupled system of stochastic equations of which certain components evolve forward in time from an initial condition and other components evolve backward in time from a random terminal condition. Several problems in the literature have been solved by characterizing financial models in terms of FBSDEs. We plan to consider various new models for factors of the economy and derivative securities in terms of FBSDEs that are more general than those previously considered and better capture qualitative features of observed financial data. We shall first incorporate spikes or jumps in the price processes to model the unpredictable events that traditional financial models do not allow. A price process that allows parameters to switch between a finite number of values, modeling a change in financial or economic fundamentals over time, is called a regime-switching model. To better model changes in financial or economic conditions over time we plan to incorporate regime-switching in the dynamics for the factors of the economy and allow these to influence price processes of assets, interest rates, and commodities. Innovative new numerical methods for solving FBSDEs shall also be developed to allow our theoretical results to be applied by practitioners and industry professionals.