This is a high-level quantitative finance short course. You’ll develop your knowledge of the most widely used models in the banking industry, particularly in relation to the interest rate and FX markets.
Learn from a highly experienced banking practitioner to prepare for the next steps in your finance career and develop your knowledge of the C++ programming language.
You’ll learn the most important concepts in financial engineering from an expert with over 12 years of experience in the banking industry. A solid grounding in quantitative finance and the ability to use C++ will allow you to take the next steps in your banking career.
The course is taught once a week on weekday evenings, allowing you to fit your learning in around other commitments.
Who is it for?
You’ll need some knowledge of financial engineering to join this course. Strong mathematical skills are a must. It’s the ideal way into roles such as quantitative analyst, market risk manager or market risk model methodology manager.
The goal of this two-day workshop is to provide a detailed overview of machine learning techniques applied for finance. We offer insights into the latest techniques for modelling financial markets and focus on option pricing and calibration.
We not only tackle the theory but give practical guidance and live demonstrations of the computational methods involved. After introducing the subject we cover Gaussian Process Regression and Artificial Neural Networks and show how such methods can be applied to solve option pricing problems, speed up the calculation of xVAs or apply them for hedging.
We further show how to use existing pricing libraries to interact with machine learning environments often set up in Python.
We explain how to set up the methods mainly in Python using Keras, Tensorflow or SciKit Learn. We give many examples which are directly related to financial mathematics and can be explored further after the course. All the material is available as Jupyther notebooks. For Gaussian Processes we use Matlab and Python examples.
This workshop covers the fundamentals and it illustrates the application of state-of-the-art machine learning applications for application to Mathematical Finance.
The workshop is designed as a 2-day event.