Professor
Joined School 1987
BSc (Western),
MSc (Australian National),
PhD (Western)
| paforsyt@uwaterloo.ca | |
| Web | http://www.scicom.uwaterloo.ca/~paforsyt |
| Voice | 519-888-4567 x34415 |
| Fax | 519-885-1208 |
|
| Peter Forsyth
Professor Joined School 1987 BSc (Western),
|
Peter's research interests span a variety of areas in Scientific Computation, including finite element methods and sparse matrix solution techniques. Recently, he has been applying these methods to the emerging area of computational finance.
Financial derivative securities, such as options and futures, can be viewed as a form of insurance. These instruments are routinely used by large corporations to hedge currency fluctuations, uncertain energy costs and commodity price volatility.
Many financial contracts contain embedded options. As a result, individual investors are often unaware that they frequently buy and sell options. Some examples of these embedded options include mortgage prepayment privileges, equity linked GICs, and fixed rate natural gas home heating contracts.
A derivative contract is based on an underlying asset. The standard model for the underlying asset price movement assumes that prices evolve according to a random walk with a drift. It is possible for an option seller to set up a hedging portfolio, which is then dynamically rebalanced in response to changes in the underlying asset price. Then, regardless of the random movement of the asset price, the seller of the option is able to pay out the value of the this contract at expiry.
However, there is strong evidence that the normal market behavior assumed by the standard model is punctuated by occasional large jumps or drops in prices (e.g. subprime mortgages). These jump diffusion models present difficult computational challenges for pricing and hedging embedded options. Jump diffusion is an effective way of modelling financial "Black Swans."
Peter's current research is focused on developing algorithms which are used to price and hedge options embedded in pension plan guarantees, convertible bonds, and employee stock options. He has also developed methods for determining optimal hedging strategies for markets which can be modeled by jump diffusion processes.
Blundon Memorial Lecturer (2010); IAM-MITACS-PIMS Distinguished Lecturer (2006); Faculty of Mathematics Fellow, University of Waterloo (2003-2006)
After graduating in 1979, Peter was a Senior Simulation Scientist with the Computer Modeling Group (Calgary), where he developed software for modeling petroleum reservoirs. After leaving CMG, he was the founding President of Dynamic Reservoir Systems (DRS). DRS was eventually purchased by Duke Engineering, and continues to market the original DRS software.
Since joining the University of Waterloo, Peter has carried out research related consulting for such organizations as TransCanada Pipelines (pipeline simulation), Boeing Corporation (sparse matrix solution methods), the Electric Power Research Institute (high level radioactive waste disposal) and Los Alamos National Laboratory (simulation of pollutant transport).
More recently, Peter has collaborated with Credit Suisse (optimal portfolio allocation), Tata Consulting Services (optimal stochastic control), Morgan Stanley (optimal trade execution), Sun Life Financial (hedging of pension plan guarantees), RBC Financial Group (valuation of demand deposits), TG Information Network (exotic option pricing), ITO33 (convertible bond pricing), and Bell Mobility (optimal timing of capacity upgrades).
J. Wang and P.A. Forsyth. Numerical Solution of the Hamilton Jacobi Bellman Formulation for continuous time mean variance asset allocation. Journal of Economic Dynamics and Control, 34:207-230, 2010.
Z. Chen and P.A. Forsyth. Implications of a regime-switching model on natural gas storage valuation and optimal operation. Quantitative Finance, 10:159-176, 2010.
J.S. Kennedy, P.A. Forsyth and K.R. Vetzal. Dynamic hedging under jump diffusion with transaction costs. Operations Research, 57:541-559, 2009.
J. Wang and P.A. Forsyth. Maximal use of central differencing for Hamilton-Jacobi-Bellman PDEs in Finance. SIAM Journal on Numerical Analysis, 46:1580-1601, 2008.
Z. Chen and P.A. Forsyth. Numerical scheme for the impulse control formulation for pricing variable annuities with a Guaranteed Minimum Withdrawal Benefit (GMWB). Numerische Mathematik, 109:535-569, 2008.
David R. Cheriton School of Computer Science
University of Waterloo
Waterloo, Ontario, Canada N2L 3G1
Tel: 519-888-4567 x33293
Fax: 519-885-1208
Contact | Feedback: cs-webmaster@cs.uwaterloo.ca | David R. Cheriton School of Computer Science | Faculty of Mathematics
Last modified: Tuesday, 11-Jan-2011 14:53:37 EST
