Python in Capital Markets

Learning Outcomes

Unlocking the secrets of coding and data science.

Discourse

Whilst there are a myriad of Python courses available, what many of them fail to do is spend time on the fundamental building blocks and use cases within finance. This course targets exactly what you need to know to be able to add value in situations faced by those working in Capital Markets. Our hard-hitting approach enables you to move from zero to hero, ensuring that you can produce robust code that works. We cover the fundamentals of programming in Python by building a simple bond pricer and moving towards a machine learning model that can predict bond prices based upon changing market conditions. We can also tailor the course to meet any specific models or use cases required. Our sessions are lively and engaging, ensuring that the content is not only extremely well delivered, but received and understood well by participants.

Program Overview

Python Fundamentals – Getting started and learning to code

Introduction to Python
Python environment – IDE, Package manager
Jupyter notebooks
Fundamentals of programming with Python

Python Practical programming – Building a simple bond pricer

Why Python is suited for data analysis?
Introduction to module – Numpy, Matplotlib
Building a bond pricer and scenario manager in Python

Python Data Analysis – Getting to the heart and soul of Python

Importing data from Excel and CSV files
Data analysis with Pandas
Pandas Essentials – Pandas Data Structures, Hierarchical Indexing, Handling Missing Data, Useful Methods and Operations
Data visualization using Pandas

Python Data Science & Machine Learning – Building an application to ‘predict’ the market

Descriptive Analysis with data
Data analysis using scikit-learn
Plotting data using various plotting methods
Using various statistical tools for analysis