PhD in administration – Financial Engineering

Be part of a community of multidisciplinary researchers, with solid internationally recognized expertise. Do your PhD in a rigorous milieu, renowned for its resources and the quality of support available for junior researchers.

Overview

Your PhD in short

Offered by HEC Montréal jointly with Concordia and McGill universities and the Université du Québec à Montréal (UQAM). This partnership gives you access to resources (faculty and courses) rarely available elsewhere in the world.

This specialization offers a variety of high-level courses in finance and mathematics. The mathematics courses are recognized by the Institut des sciences mathématiques (ISM) and may be taken by PhD in mathematics students at the main universities in the region.

Full-time program allowing you to complete your studies in 4 years.

Tuition fees waived and competitive funding for the first four years of your studies.

“I acquired cutting-edge knowledge on a number of current topics, surrounded by dynamic and motivated researchers. It was a highly stimulating and interesting experience!”

–

Frédéric Godin, PhD. Assistant Professor, Concordia University

Program characteristics

Doctoral
90 credits

Full-time

On-site

Côte-des-Neiges

For a career in academia or business

Around

40%

of graduates from this specialization
between 2006 to 2022 hold positions
as professors at universities in
Canada or the United States.

Nearly

60%

are working as executives or consultants
for leading firms or investment funds,
e.g. Deloitte, KPMG, PSP Investment and
the Abu Dhabi Investment Authority.

Among the best

The work of PhD students in the Financial Engineering specialization has been recognized for its outstanding quality and has earned them many awards and scholarships.

Papers based on dissertations by PhD students in the Financial Engineering specialization are published in top-tier journals in the field, including:

European Journal of Operational Research
Journal of Banking and Finance
Journal of Economic Dynamics and Control
Journal of Risk and Insurance
The Energy Journal
The Review of Financial Studies
Quantitative Finance

Varied research interests

Credit risk
Derivatives pricing
Dynamic optimization
Energy market
High-frequency data
Machine learning
Mean field games
Monte Carlo simulation
Numerical methods
Operational research
Optimal hedging
Optimization
Risk management
Probability and statistics
Statistical methods
Stochastic control
Stochastic processes
Text mining

Our PhD students and candidates

See the list of students in this specialization on Google Scholar

Top-flight research infrastructure

PhD students in this specialization benefit from the best possible infrastructure, allowing them to carry out advanced research in financial engineering.

National Bank Capital Markets trading room
Computing and Data Mining Laboratory (LACED) and its computing grid
Access to major databases, including CRSP, Compustat, TAQ, Thomson Financial, FISD, TRACE, WRDS, OptionMetrics and Moody’s Credit Risk

World-class research in financial engineering

HEC Montréal offers doctoral students in financial engineering an exceptional scientific milieu, with a research chair and two professorships.

Canada Research Chair in Decision Making Under Uncertainty, held by Professor Érick Delage
Canada Research Chair in Risk Management, directed by Professor Georges Dionne
Research Professorship in derivatives analysis: Professor Jean-Guy Simonato
Research Professorship in Financial Engineering : Professor Geneviève Gauthier
Research Professorship in financial risk factors and derivatives: Professor Christian Dorion
Research Professorship in Sentometrics : Professor David Ardia
Research Professorship in statistics: Professor Debbie J. Dupuis

The professors are members of various internationally renowned research centres or institutes:

All the members of the Decision Sciences group have individual grants from the Natural Sciences and Engineering Research Council of Canada (NSERC).

An internationally renowned multidisciplinary team

Members of the Department of Decision Sciences associated with the Financial Engineering specialization

Members of the Department of Finance associated with the Financial Engineering specialization

The doctoral program in administration requires a minimum of 90 credits, structured across three phases: preparatory coursework, specialization, and the dissertation.

The program typically spans between three and six years.

Phase I – Preparation (if necessary, maximum 1 year)

The preparatory phase courses allow you to acquire the necessary knowledge before starting the PhD-level courses. These are generally graduate-level courses and do not count toward the program’s total of 90 credits.

Phase II – Specialization (maximum 2 years)

At least 7 seminars among those proposed, respecting the minimum required for each type
Uncredited workshop Responsible Conduct of Research: From Norms to Practice
Writing of scientific paper
Comprehensive exam

Minimum 5 specialization seminars

MATH 80622A

Analysis of Extreme Values with Application in Financial Engineering

Subject

Mathématiques

Program

PhD

Location

Côte-des-Neiges

Instruction mode

On-site learning

Credits

3

The risks related to extreme events on financial markets are very difficult to quantify. The theory of extreme values is an important statistical discipline allowing for a more proper modeling of rare events. The proper analysis of extreme values, including methods of estimation, quantification of uncertainty, diagnostics, and maximal utilization of available data are considered in the course. We also make extensive use of R, a freely available language and environment for statistical computing and graphics.

See the course webpage
FINA 80222A

Contingent Claims in Incomplete Markets

Subject

Finance

Program

PhD

Location

Côte-des-Neiges

Instruction mode

On-site learning

Credits

3

Examples include jump-diffusion models, models with priced correlation risk and the corresponding innovations in the modeling of the pricing kernel. We will also discuss the backtesting of risk management strategies in the context of incomplete markets. Development of the ability to implement the methods studied and critically read the current and forthcoming literature in the field.

Themes covered

1. Brief review of contingent claims and of the notion of market (in)completeness. The hypotheses underlying to the Black-Merton-Scholes model and the associated pricing kernel. 2. The volatility smile model-free volatility measures (RV and VIX) and option-implied distributions. We will revisit the Black-Scholes implied volatility smile and some of its potential explanations. We will then consider different model-free volatility measures and see how variance swaps and/or option data can be used to extract information about the risk-adjusted distribution of returns. Finally we will introduce the notion of variance risk premia a concept that we will further revisit when we study dynamic volatility models.

Selected papers: Andersen Bollerslev Christoffersen and Diebold (2006); The CBOE Volatility Index - VIX (2009); Demeterfi Derman Kamal and Zou (1999); Martin (2013); Bollerslev and Todorov (2011) . 3.Stochastic volatility models and the pricing kernel. Conditionally normal GARCH models and the pricing kernel in discrete time. Component models.

We will introduce stochastic volatility and GARCH models highlighting the pricing kernel used or implied by the different models. We will review some stylized facts on volatility and see how the different models accommodate these (or not). In particular we will discuss volatility models in which volatility process is separat

See the course webpage
FINA 80224A

Continuous-time Corporate Finance

Subject

Finance

Program

PhD

Instruction mode

On-site learning

Credits

3

The body of literature on continuous-time corporate finance has substantially grown over the last four decades and has been the subject of surveys and of recent reference books such as Moreno-Bromberg and Rochet (2018) and Galai et al. (2018). The course is structured around six topics: Corporate investment, capital structure, financial distress, corporate control, corporate risk management and the empirical implementation of continuous-time models. For each of these topics, the instructor will review the economic and financial questions and present the modelling approaches in the literature. Students will present one paper chosen among the selected reading list. The instructor will then organize a discussion around that presentation and the other papers in the reading list. Students will also be asked to work on a project.

Themes covered

- Corporate investments: Real options strategic exercise of real options (option games) liquidity constraints.

- Capital structure: Static trade-off agency conflicts informational asymmetry dynamic capital structure interactions with investment policy.

- Financial distress: Debt renegotiations strategic debt service bankruptcy procedure.

- Corporate control: Mergers and acquisitions industry competition.

- Corporate risk management: Risk management and firm value liquidity constraints.

- Empirical implementation: Estimation of structural models convexity bias and other issues in testing capital structure models.

See the course webpage
MATH 80680A

Dynamic Optimisation in Management

Subject

Mathématiques

Program

PhD

Location

Côte-des-Neiges

Instruction mode

On-site learning

Credits

3

At the end of the course, the students should be able to identify a business management situation presenting a dynamic optimization problem, represent this problem using a suitable mathematical model, and solve it using one of the available techniques of dynamic optimization.

See the course webpage
FINA 80223A

Macro Asset Pricing

Subject

Finance

Program

PhD

Instruction mode

On-site learning

Credits

3

This class is intended for Ph.D. students interested in doing research in theoretical and empirical asset pricing with an emphasis on macro finance. The objective of this class is to familiarize students with a number of research areas and tools that are particularly important in the recent asset pricing and international finance literature. A large emphasis will be devoted to the analysis of risk premia in various financial markets and to foster our understanding on the role of investor preferences as a fundamental driver in asset pricing. We will cover the latest research focusing on the empirical determination and the theoretical explanation of various risk premia, such those present in exchange rates, sovereign debt valuation, equity markets, and corporate asset prices.

See the course webpage
MATH 80614A

Numerical Methods in Quantitative Finance

Subject

Mathématiques

Program

PhD

Location

Côte-des-Neiges

Instruction mode

On-site learning

Credits

3

The course is designed for the study of numerical methods in finance, with an emphasis on numerical methods for the pricing of contingent claims. The reading material covers earlier developments as well as current research issues. Some of the material will be presented in class by the instructors. However, the course will generally involve presentations and discussions of the assigned readings by the students.

Themes covered

Monte Carlo simulation

Solution of partial differential equations

Fourier Transform

Filtering and estimation of latent variables

Artificial intelligence

Risk measures

See the course webpage
MATH 80624A

Quantitative Risk Management Using Robust Optimization

Subject

Mathématiques

Program

PhD

Location

Côte-des-Neiges

Instruction mode

On-site learning

Credits

3

More specifically, students will become familiar with the main tools that are used in the application of the robust optimization paradigm: convex theory, data-driven uncertainty sets design, adjustable decision rules, tractable reformulation, and decomposition algorithms for problems of infinite size. The course will also cover a set of practical applications where the use of such tools is called-for. Applications will be inspired from a diversified range of fields of practice.

Themes covered

1) Why is there a recent surge of interest in robust optimization?

2) Robust counterpart of Linear Programs

3) Data-driven Uncertainty Set Design

4) Robust Nonlinear Programming

5) Adjustable Robust Linear Programming

6) Value of Flexibility Using Tractable Decision Rules

7) Globalized Robust Counterparts

8) Distributionally Robust Optimization

9) Robust Markov Decision Processes

10) Robust Preference Optimization

11) Pareto Robust Optimization

12) A Survey of Recent Applications

See the course webpage
MATH 80637A

Special Topics in Financial Engineering

Subject

Mathématiques

Program

PhD

Instruction mode

On-site learning

Credits

3

This course covers advanced topics in Financial Engineering. This course is typically taught by a team of professors.

See the course webpage

You may also choose any other equivalent course offered in the joint program.

1 pedagogy seminar

MNGT 80470A

Teaching in Business Education

Subject

Management

Program

PhD

Location

Côte-des-Neiges

Instruction mode

On-site learning

Credits

3

Themes covered

- Teaching conceptions and learning models
- Current trends in business education
- Teaching methods
- Course planning and preparation
- Technology and teaching
- Self-assessment of the SMT
- Pedagogical innovation in business education
- Developing oneself as a teacher

Important notes

Course in French : MNGT 80470

See the course webpage

You may also choose any other equivalent course offered in the joint program.

Maximum 1 elective seminar

Phase III – Dissertation (maximum 3 years)

Writing of the dissertation
Public presentation of the dissertation proposal
Defence

Deadlines for submitting admission applications

Fall term: no later than January 5th
Winter term: no admissions
Summer term: no admissions

Currently studying in a master's program?

You can apply for admission to a doctoral program, even if you have not yet completed your current program (MSc or MBA). If your application is accepted, your admission will be conditional upon you receiving your degree before the start of the doctoral program, meaning before late August.

Conditions and required documents

Admission requirements

Degree required

You must hold one of the following degrees, or a degree deemed equivalent by the program administration:

Master of Science (MSc)
Master of Business Administration (MBA)
Graduate degree in a related field

Minimum GPA

You must have earned an average that the School deems excellent for all years of university studies.

Admission test

The admission test (GRE, TAGE MAGE or GMAT) is optional but strongly recommended to support your application.

Language requirements

Documents required for admission

You will need to provide documents as part of the admission process.

Check the list of required documents

Capacity is limited for certain programs. HEC Montréal does not guarantee that all eligible applicants will be accepted.

Program funding

At least $30,000 per year for your first 4 years of study.

This amount may include various sources of funding: bursaries, remuneration for teaching activities, research activities, etc.

A letter detailing the funding offer will be sent when you are admitted.

Financial support from the Office of Research and Knowledge Transfer

Maximum of $5,000 for the duration of studies

Depending on available funding, the Office of Research and Knowledge Transfer may grant assistance of up to $5,000 for the duration of your studies. The aim is to support your efforts in scientific research and publication, and to help you in your job search. Learn more about funded activities.

Estimated annual fees for the first 4 years of studies

For your first 4 years of studies, you will receive a tuition waver. During this time, you must pay institutional fees and medical insurance fees as applicable.

Canadian students
$0 for tuition fees $1,700 for mandatory institutional fees
Approximately $1,700 per year

Canadian students

$0 for tuition fees

$1,700 for mandatory institutional fees

Approximately $1,700 per year

International students
$0 for tuition fees $1,700 for mandatory institutional fees $700 for health insurance
Approximately $2,400 per year

International students

$0 for tuition fees

$1,700 for mandatory institutional fees

$700 for health insurance

Approximately $2,400 per year

Estimated annual fees starting the 5th year of studies

Canadian students
$2,700 for tuition fees $1,700 for mandatory institutional fees
Approximately $4,400 per year

Canadian students

$2,700 for tuition fees

$1,700 for mandatory institutional fees

Approximately $4,400 per year

French or French Belgian student
$2,700 for tuition fees $1,700 for mandatory institutional fees $700 for health insurance
Approximately $5,100 per year

French or French Belgian student

$2,700 for tuition fees

$1,700 for mandatory institutional fees

$700 for health insurance

Approximately $5,100 per year

International students
$3,300 for tuition fees $1,700 for mandatory institutional fees $700 for health insurance
Approximately $5,700 per year

International students

$3,300 for tuition fees

$1,700 for mandatory institutional fees

$700 for health insurance

Approximately $5,700 per year

Other financial resources

HEC Montréal encourages you to apply for bursaries with Quebec and Canadian funding agencies (annual competitions). Student Services (SAE) offers support for preparing your applications.

For any questions, email analyste.bourses [at] hec.ca (analyste[dot]bourses[at]hec[dot]ca).

Admission

Apply for admission

Information

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