Trade management in Python - a story of throughput
Ciprian Miclaus
Python is used more and more in finance and in investment banking nowadays as the language and platform of choice to solve various problems that were previously solved in other languages: Java, C++ or VBA.
This presentation offers a gentle introduction to the world of trading and investment banking, the kind of problems encountered and solved and how Python fits in the picture. While there are many use cases for using Python in investment banking, this story focuses on the trade management and trade capture use cases.
It decomposes the trade capture scenario and shows how throughput (measured generally in trades/second) can be measured and increased. It then goes to describe a real world custom solution based on multiprocessing in Python.
At the end of the presentation, the participants will hopefully gain an idea of what types of problems developers working for investment banks have to deal with on a day to day basis and how Python is put to good use to solve those problems.