Quantitative Finance using Python or C++

In modern financial markets, expertise in Rates and FX must go beyond theory. Leading institutions expect professionals to understand the programming languages that power pricing, trading and risk systems. With Python widely adopted across quantitative teams and C++ embedded in core infrastructure, the ability to bridge financial models and real-world implementation is a distinct advantage. This course equips you with the intellectual depth and technical capability expected at the highest levels of global finance.

This exclusive programme bridges financial theory and real-world practice in Rates and FX. Led by a senior Deutsche Bank practitioner, it combines rigorous quantitative foundations with hands-on programming in Python and C++, giving you the skills to model, analyse, and implement solutions in today’s markets.

Flexible hybrid learning lets you join us in London or connect online, while expert-led sessions, practical exercises, and real-world case studies equip you with the knowledge and technical confidence to operate at the forefront of global banking.

Who is it for?

This course is designed for finance professionals with a strong foundation in financial engineering and mathematics. Ideal for those aiming to progress into quantitative analyst or market risk roles, it develops advanced technical expertise through flexible hybrid learning, equipping you to stand out in global banking.

Timetable

Designed for busy professionals, the course runs for two hours one evening a week, for a duration of 10 weeks. You can join in London or online, making it easy to fit around your work commitments.

City St George's Short Courses follow the academic year, with courses available across three terms:

• Autumn - October
• Spring - January
• Summer - April

Benefits

• Expert-led industry insight – Learn directly from the Director of Rates and FX at Deutsche Bank, gaining practical perspective from the front line of global financial markets.
• True hybrid flexibility – Attend in central London or join online, with the freedom to switch week by week to fit around your professional commitments.
• Extensive digital learning resources – Access high-quality materials and supporting content throughout the programme to deepen and consolidate your understanding.
• Recognised university certification – Earn a City St George’s, University of London certificate and digital LinkedIn badge to formally recognise your achievement and enhance your professional profile.

This course delivers an advanced, practice-led exploration of derivatives pricing and interest rate modelling, combining rigorous quantitative frameworks with hands-on implementation in Python and C++. You will develop both the theoretical understanding and the coding capability required to build and apply models used in modern financial institutions.

Derivatives Pricing Foundations

You will begin with the core frameworks underpinning modern option pricing, including:

• Binomial and trinomial models, including the Cox–Ross–Rubinstein approach
• Black–Scholes methodology
• Explicit and implicit PDE methods
• Monte Carlo simulation and variance reduction techniques
• Pricing error analysis and calculation of Greek parameters
• Hedging and replication strategies

You will apply these techniques to price European, Digital and Spread options, before extending to more complex structures including Barrier options and Double-No-Touch products.

American and Path-Dependent Optionality

The course explores early-exercise features and advanced numerical techniques, including:

• American options using tree-based methods
• The Longstaff–Schwartz methodology for Monte Carlo exercise decisions
• Asian options (geometric and arithmetic)
• Basket and path-dependent options

You will also analyse hedging replication strategies for European and structured products.

Interest Rate Modelling and Swaption Pricing

A significant focus of the programme is modern interest rate modelling, including:

• Short-rate models: Merton, Vasicek and one-factor Hull–White
• Multi-factor Hull–White models
• Yield curve shape and calibration
• Bond pricing and caplet pricing as options on bonds
• Swaption pricing, including Jamshidian’s trick
• Bermudan options pricing, forward volatility products pricing, convexity adjustments, model implementation and the SABR model

You will also study the Libor Market Model, including drift equations, dynamics (lognormal, CEV, displaced diffusion), evolution of Libors, and PCA-based rank reduction.

There is no formal examination for this course. Instead, learning is reinforced through weekly exercises and applied projects, including practical implementation in Python or C++.

Upon successful completion, you will receive a City St George’s, University of London certificate and digital LinkedIn badge, formally recognising your advanced training in financial engineering for interest rates and foreign exchange.

Teaching

Sessions combine expert-led lectures with hands-on exercises designed to apply the concepts covered each week. You can participate in London or online, with the course delivered in a flexible hybrid format to fit around your professional commitments. The emphasis is on practical understanding and real-world implementation, ensuring you leave with both theoretical insight and applied technical capability.

• Prior knowledge: A foundation in financial engineering and strong mathematical skills are required to succeed on this course
• Programming skills: You should be comfortable with basic object-oriented programming concepts in Python or C++.

English requirements

English proficiency: Fluent spoken and written English is required for enrolment.

Books that cover the course well from the theory and coding perspective include:

• John Hull, Options, Futures and Other Derivatives, Prentice Hall 2006.
• Steve Shreve, Stochastic Calculus for Finance II, Springer 2004.
• Martin Baxter and Andrew Rennie, Financial Calculus: An Introduction to Derivative Pricing, Chapter 5, (CUP 1996).
• Mark Joshi, C++ Design Patterns and Derivative Pricing, (Cambridge University Press, 2004).