Want to know more about open source applications and how easy they are to use? Join this months Full Stack Quants meetup to learn more!
Excel has proved to be the tool of choice for (tens of?) thousands of traders and market analysts who have been doing data science -- finding relationships between assets and economic metrics -- since times before the category 'data scientist' even existed. But as the data sets get bigger and the patterns get harder to find, Excel performs substantially less well than the modern data scientist's toolkit. Now might be the time to wean yourself off Excel and get familiar with the new tools.
This presentation show how easy it is to install and use the open source applications you need. Robert Hardy will show how the same kind of data cleaning and analysis is done with Python.
The presentation will keep technical details to a minimum. If you have ever worked with Excel then you should be able to follow along.
Robert Hardy is a full stack quant, with over 12 years of experience in the front office teams of major financial institutions. He has built professional portfolio management systems entirely from open source components. He experienced an epiphany when he was introduced to TDD, pair programming and Agile methods. Robert talks and blogs on topics related to software and mathematics, and with his diploma in painting and ceramics in hand he claims to even have some level of expertise in the Fine Arts.
Guest presenter Kirill Egorov will walk us through an example of using R for clustering analysis on equity data from Quandl.
Kirill has been working on data management and analytics in financial services for the last 8 years. He started out in the Treasury team of a large Russian bank, where he was building data pipelines and models for liquidity management and middle office reporting. After moving to London he joined a fixed income brokerage startup, where he has been building out their data analytics platform, leveraging multiple open source technologies.