The alternative route to Financial Mathematics

The financial mathematics postgraduate curriculum will include core classes on mathematical methods, statistics, and financial modeling. Additional financial mathematics course offerings focus on corporate finance, derivatives pricing and hedging, financial forecasting, risk management, and data science. Electives may also include advanced topics in computational finance, algorithmic trading, and specific programming languages such as Python, for example. 

In a FinMath MSc program, students write dissertations based on their own research in finance; some may then continue on for a PhD, while others will re-enter to job market after graduation. The typical MSc program runs from 1.5-2 years on campus for full-time students and 3-4 years for part-time students. Although there is some flexibility in the duration of the program, students are highly committed to their university studies for an extended period, taking valuable time away from their careers and handling significant educational and personal expenses while enrolled in university.

An alternative to the MSc in FinMath: The Certificate in Quantitative Finance (CQF)

A popular alternative to the MSc in FinMath is the Certificate in Quantitative Finance (CQF), a rigorous and thorough introduction to financial mathematics that makes use of distance learning options and takes a friendly and flexible approach to the timeframe for program completion. The CQF covers a vast range of topics in quant finance, starting with a series of intensive Primers on mathematics, finance, and Python programming, which ensure that all delegates will start from a fresh base of knowledge related to the central themes that will arise during the program. The course then proceeds through a series of six modules, taught online to delegates around the world. The CQF can be completed anywhere from six months to three years from the start date and students will develop and implement what they have learned through a final practical project instead of a dissertation. 

About the CQF

Throughout each of the six CQF modules, the students work directly with quant models to gain experience with direct implementation. The assessments for the program require delegates to accomplish three objectives: 

1) Derive the theory on which the model is based, 
2) Build and implement the model from the ground up, and 
3) Analyse the output of the model, offering an insightful critique of the results. 

This learning process supports the development of “desk-ready” skills, a feature that has clear value to employers in all corners of the financial industry. In addition to the modules and lectures, there is ample support for students over the course of the CQF program, including specialized tutorials, programming labs, in-depth workshops, and one-on-one faculty consultation when students need assistance with particular questions.
 
As part of the CQF’s commitment to continuous education, CQF alumni will have permanent access to Lifelong Learning, a video library hosting a wide array of extra lectures as well as the latest CQF syllabus. 
 

CQF Program Structure

The CQF syllabus covers the following themes in the two levels of the program. This tiered structure supports flexibility in the approach to completing the program. Most delegates may go straight through, graduating with their cohort in six months, while others may choose to pause between Level 1 and Level 2, resuming the program within one of the next few cohorts in order to finish by year three.

Level 1

• Module 1 - Building Blocks of Quantitative Finance 

In Module 1, you will be introduced to the rules of applied Itô calculus as a modeling framework. You will build tools using both stochastic calculus and martingale theory and learn how to use simple stochastic differential equations and their associated Fokker- Planck and Kolmogorov equations.
 

• Module 2 - Quantitative Risk & Return 

In Module 2, you will learn about the modern portfolio theory of Markowitz (MPT), the capital asset pricing model (CAPM), and recent developments around these theories. You will investigate quantitative risk and return, looking at econometric models such as the ARCH framework and risk management metrics such as VaR and how they are used in the industry.
 

• Module 3 - Equities & Currencies 

In Module 3, you will explore the history and importance of the Black-Scholes formula as a theoretical and practical pricing model. You will learn about the key concepts behind this model and study results in the context of equities and currencies using different kinds of mathematics to familiarize you with the techniques currently in use.

Level 2

• Module 4 - Data Science & Machine Learning l 

In Module 4, you will be introduced to the latest data science and machine learning techniques used in finance. Starting with a comprehensive overview of these topics, you will learn essential mathematical tools followed by a deep dive into supervised learning, including regression methods, k-nearest neighbors, support vector machines, ensemble methods, and many other techniques commonly found in machine learning today.
 

• Module 5 - Data Science & Machine Learning ll  

In Module 5, you will learn about and apply an additional set of methods used in machine learning. Starting with unsupervised learning, deep learning, and neural networks, you will move into natural language processing and reinforcement learning. You will study the theoretical frameworks and analyze practical case studies exploring how these techniques are used in quantitative finance.
 

• Module 6 - Fixed Income & Credit 

In the first part of Module 6, you will review the multitude of interest rate models used in the fixed income industry, focusing on the implementation and limitations of each model. In the second part of Module 6, you will focus on credit and learn how credit risk models are used in quantitative finance, including structural, reduced form, and copula models.
 

• Module 7 - Advanced Electives

Your advanced electives are the final element in the CQF program. The electives provide the opportunity to explore an area that’s most relevant or interesting to you. You will select two electives from an extensive menu in order to complete the final project and obtain the CQF designation.

Additional CQF requirements include passing a series of take-home exams, and submission of the final project, including working code in the programming language of your choice.

Although the MSc in Financial Mathematics has appealing aspects for those seeking a deeper education in quantitative finance, the CQF provides an exciting, flexible and rigorous alternative. Soon entering its 19th year of existence, the CQF provides you with the tools, theoretical understanding, and direct experience required to thrive in the financial industry today.  

For further information about the CQF qualification, download the brochure and join an information session.