Modelling Trading and Risk in the Market

Modelling Trading and Risk in the Market


Project leader: Matt Davison, Department of Applied Mathematics, University of Western Ontario (mdavison at


Traders in both financial markets and commodity markets must make educated decisions about when to trade and at what price. The project will develop tools to assist in this decision making process.    

Large entities such as pension- or endowment- funds are responsible for managing large portfolios of assets and must find the best return possible for their members consistent with a given risk level.   Modern financial markets have large numbers of securities available for this purpose.  Products such as variance swaps, collateralized debt obligations, and collateralized fund obligations are being studied in our project.

In order to determine not only the value of these complex contingent claims but also the best way to use them, complicated random models of asset markets must be developed.  In our project work is being done on simulating groups of traders as they create market prices, while other work is being done on fractional Brownian motion, Hidden Markov models, and delay differential equation based models. 

Those responsible for managing large provincial, federal, and corporate debts, funded by issuing many different types of bonds, are faced with a similar, though complementary, problem to that of managing large asset portfolios.  There are some crucial differences in the two tasks however.  Work is going on in this project on this debt management problem.

The measurement of risk is also important for managers.  Quantitative methods for measuring risk also address the measurement and management of financial risk in its various forms: market risk, model risk, credit risk and operational risk.

Commodity markets are increasingly important not only for industrial but also for financial applications.  For non-standard commodities, such as energy (electricity, natural gas) we are developing models for the price of the commodity as well as algorithms for pricing complicated, non-standard options. We also examine supply side issues of electrical energy. Since electricity must be generated at the same time as it is consumed but demand is highly variable, on daily, weekly, and seasonal time scales operational problems are of interest: when and in which reservoir to store water and when and which dam to use to meet electricity demand. Furthermore much existing electrical power infrastructure is beyond its natural service life and must be replaced to produce reduced pollution.

We have assembled a team of mathematicians from five Universities. Electricity supply and energy markets and their products are of particular interest to researchers at the University of Calgary and at the University of Western Ontario. At McMaster University and the University of Toronto the emphasis is on modeling stock market and credit instruments, whereas at the University of British Columbia both of these areas as well as mortgage securities are studied. We consult with energy companies, financial software companies as well as companies from the banking and insurance sectors.