Research Areas
At the Financial Mathematics Research Group, we advance mathematics in the context of financial markets. Our work has direct industrial application and we also work extensively on theory-oriented problems in order to accurately capture nuanced characteristics of financial markets. Unlike other scientific fields, our mathematical research projects are diverse and change constantly, including working on the latest developments in machine learning and fintech. We explore data, develop new mathematical models and improve on existing models.
Funding: Our research is supported by a wide variety of grants, including MITACS, NSERC Discovery, NSERC USRA, NSERC Engage, and NSERC CRD.
To discuss research opportunities with our group, find your interest area and contact a supervising professor.
Portfolio Optimization
Our work in this area involves developing investment strategies that maximize returns and minimize risks. Members of our group have experience in building portfolios for financial institutions that are large (e.g. banks) and small (e.g. hedge funds). By studying how investments move, we can predict the risk involved and potentially provide the basis for employing alternate asset allocation strategies to optimize returns.
Supervising professors: Dr. Rubtsov and Dr. Xu
Risk Management
A prime part of our work involves understanding risk and creating models to measure and mitigate its potential impact. In the area of risk management we have been working with market risk, interest rate risk, climate change risk, systemic risk (risk of collapse of the entire financial system), among others. The results of our research were published in top-tier journals in Mathematical Finance.
Supervising professors: Drs. Ferrando, Gao, Olivares, Rubtsov, Xanthos and Xu
Derivative Pricing
In this research area, we develop approaches for pricing derivative contracts based on future valuations of its underlying assets. A core component of our work is to improve on shortfalls in standard pricing models such as Black-Scholes-Merton model. We develop a variety of models to reflect real-world phenomena such as heavy-tail distributions or running jumps. The more accurate our models, the better investors can hedge in buying or selling.
Supervising professors: Drs. Ferrando, Olivares, Rubtsov, Xanthos and Xu
Environmental Finance
We are currently one of only few mathematics groups with expertise in Environmental Finance – a growing and increasingly important research area. Our work in this field encompasses two main subjects:
Mitigation of climate change risk
In this research area we are providing answers to the following questions. How can financial institutions mitigate adverse impacts of climate change? How can financial institutions help in transitioning to lower carbon economies? How to optimize climate taxation and quantify the cost of delay in addressing potentially devastating consequences of global climate change?
Supervising professor: Dr. Olivares
Weather Derivative Contracts
Financial markets are renewing their interest in contracts involving weather-related impacts on pricing. Environmental factors such as rainfall can affect production in weather-dependent industries such as agriculture. We develop mathematical models to more accurately price weather derivative contracts within the context of climate change.
Supervising professor: Dr. Rubtsov
Emerging Topics in Finance
Our group stays current with some of the latest developments within Finance. We’re currently studying and modeling the characteristics of such advancing areas as:
- Fintech
- Blockchain, cryptocurrencies
- Data mining
- Artificial intelligence and Machine learning
- Behavioural finance
Supervising professors: Dr. Rubtsov and Dr. Xu