## Seismic Forward Numerical Modeling and Illumination Study

This project will use computer modelling to aid in building a geological model of the earth’s subsurface. The model is assumed to be accurate when seismic data from the model reasonably matches seismic data recorded on the surface of the earth. The movement of wave energy within the model will then be used to aid in identifying hydrocarbon signatures in the real seismic data.

## Optimal Investment Strategies

A major challenge for portfolio managers is that it is hard for them to predict the future. In practice, they would settle for being able to identify which stocks are likely to perform well and which are likely to perform badly in the next month. This project will include the investigation of algorithms for using specific collections of research data about a family of stocks to do just this, and will also be concerned with ways of assessing how best to compare the quality of alternative algorithms.

## Efficient Calculation of Greeks for Interest Rate Exotics Using the BGM Pricing Model

QUIC Financial Technologies produces software used in the pricing of contracts in financial markets. Such software is based on mathematical models. In turn these models must be calibrated to market data. The sensitivity of the prices given by the models to small changes in the input parameters, that is the derivatives of the prices, are called the ‘Greeks’ because they are usually labeled ‘delta’, ‘gamma’, ‘theta’, etc. Thus, this project will investigate new ways to calculate the Greeks.

## Portfolio Management and Energy Options

The partner company, ENMAX Energy Corporation, is a leading electricity and natural gas supplier in Alberta. Modern techniques from stochastic processes and numerical analysis are widely used in energy risk management and trading. The intern research project involved the development of an optimal portfolio of products in the energy industry as well as the study of the pricing of new forms of contracts for energy products. In addition, stochastic dynamic programming techniques were applied to investigate optimal portfolios.