Agenda

Agenda

Python for Financial Markets

08:3009:00

Registration and refreshments

08:30 - 09:00

09:0010:30

Introduction to Python I

09:00 - 10:30

  • The basics of Python
  • What are the basic types
  • Data structures
  • Control flow syntax
  • Recursion vs. iteration

10:3010:45

Morning break

10:30 - 10:45

10:4512:00

Introduction to Python II

10:45 - 12:00

  • Objects and classes
  • PEP8 coding conventions
  • Python standard libraries
  • Tutorial

12:0013:00

Lunch

12:00 - 13:00

13:0014:30

Data analysis in Python I

13:00 - 14:30

  • What is SciPy?
  • NumPy: linear algebra library
  • Pandas: time series library

14:3014:45

Afternoon break

14:30 - 14:45

14:4516:15

Data analysis in Python II

14:45 - 16:15

  • Visualisation libraries: Matplotlib, Plotly etc.
  • Scikit-learn and machine learning
  • Tutorial

08:3009:00

Refreshments

08:30 - 09:00

09:0010:30

Analysis of financial data I

09:00 - 10:30

  • What type of financial data is available?
  • How to download data from Bloomberg, Quandl, FRED etc.
  • Market drivers
  • Creating a trading strategy: approaches and introduction to FX markets
  • How to backtest a trading strategy in Python

10:3010:45

Morning break

10:30 - 10:45

10:4512:00

Analysis of financial data II

10:45 - 12:00

  • Tutorial

12:0013:00

Lunch

12:00 - 13:00

13:0014:30

Financial market case studies using Python I

13:00 - 14:30

  • Understanding the behaviour of FX around major data events
  • Creating a web app to do volatility calculation of FX with Dash
  • xlwings: using Python in Excel

14:3014:45

Afternoon break

14:30 - 14:45

14:4516:15

Financial market case studies using Python II

14:45 - 16:15

  • Comparing unemployment data across different US states
  • Tutorial