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PhD in administration - Financial Engineering

Students wanted

Would you like to do your PhD in a community of world-renowned researchers? This exciting learning experience will introduce you to university-level research and teaching.

Credit risk

Description

Evaluation of counterparts risk, effects of netting and margin call.

Supervising professor

Geneviève Gauthier

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Econometrics of financial and textual data

Description

Development of econometric methods and applications to financial markets, risk management, and asset allocation.

Supervising professor

David Ardia

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High frequency limit order book data

Description

Understanding the dynamics of high frequency limit order book data and forecasting market conditions by exploiting information content of high frequency limit order book data via machine learning.

Supervising professor

Tolga Cenesizoglu

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Mean Field Games in Energy and Financial Markets

Description

Modeling energy and financial markets as large-population dynamic games (more specifically mean field games) and addressing problems such as optimal trading, equilibrium pricing, and contract design.

Supervising professor

Dena Firoozi

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Modelling extreme values – Weather derivatives and environmental issues

Description

Explore how modelling of extreme values and modelling of dependence can be applied to weather derivatives and environmental issues.

Supervising professor

Debbie J. Dupuis

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Pricing idiosyncratic variance and jumps

Description

The trading of variance has grown exponentially in the last decade. But our understanding of what drives returns in a variance portfolio is still rudimentary. We seek to explore the pricing of variance on individual assets, accounting for potential jumps.

Supervising professor

Christian Dorion

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Real options and energy

Description

Development of dynamic optimization algorithms with hydro-power applications. Machine Learning and Approximate Dynamic Programming. Optimal design of contracts on energy markets.

Supervising professor

Michel Denault

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Realized variance and particle filters

Description

Model estimation using high frequency data and filtering approaches.

Supervising professor

Geneviève Gauthier

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Program details
Type
PhD
credits  
90 credits
Schedule
  • Full time
Time
  • Day
Level
PhD  

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English-language Programs > PhD in Administration > PhD in Administration – Financial Engineering > Students wanted