Practical and Flexible Curriculum
The Quantitative Finance Qualification
Practical Quant Finance Qualification
The CQF program curriculum features six core modules, with exams in modules two to four, and a capstone project after module six. Tailor your learning with Advanced Electives to align with your career goals and deepen your expertise.
Option 1 - Full ProgramThe program can be taken in full by completing the six modules and two chosen electives in six months. This option provides you with instant access to all the materials and to Lifelong Learning. |
Option 2 - Level I & IILevel I is comprised of modules one to three and your first two exams. Level II consists of modules 4 through 6, your last exam and final project, chosen electives and Lifelong Learning. |
In module one, we will introduce you 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.
In module two, you will learn about the classical portfolio theory of Markowitz, the capital asset pricing model and recent developments of these theories. We 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.
In module three, we will explore the importance of the Black- Scholes theory as a theoretical and practical pricing model which is built on the principles of delta hedging and no arbitrage. You will learn about the theory and results in the context of equities and currencies using different kinds of mathematics to make you familiar with techniques in current use.
In module four, you will be introduced to the latest data science and machine learning techniques used in finance. Starting with a comprehensive overview of the topic, you will learn essential mathematical tools followed by a deep dive into the topic of supervised learning, including regression methods, k-nearest neighbors, support vector machines, ensemble methods and many more.
In module five, you will learn several more methods used for machine learning in finance. Starting with unsupervised learning, deep learning and neural networks, we will move into natural language processing and reinforcement learning. You will study the theoretical framework, but more importantly, analyze practical case studies exploring how these techniques are used within finance.
In the first part of module six, we will review the multitude of interest rate models used within the industry, focusing on the implementation and limitations of each model. In the second part, you will learn about credit and how credit risk models are used in quant finance, including structural, reduced form as well as copula models.
Your advanced electives are the final element in our core program. These give you the opportunity to explore an area that’s most relevant or interesting to you. Select two electives from the extensive choice below to complete the CQF qualification. You will also have access to every advanced elective as part of the Lifelong Learning library.
