Pythons, Pandas and more – The Big Data Zoo for Stock Markets

Many of the world’s largest hedge funds employ some of the most talented data scientists, quants and computer engineers; often exceeding the supposed intellectual capabilities of firms such as Google or Apple. These engineers, scientists and quants spend their days seeking new ways to create alpha. Often in the pursuit of building these new trading algorithms a suite of tools are necessary for analysis, backtesting, integration of external data (such as alternative market data), and even implementation (the trading phase of the strategy).

While highly secretive, rightfully so, regarding their actual strategies; many of these firms are embracing the open source movement and making some of their tooling available for entities outside the walls of their funds. One example of this open sourcing of powerful software for use in quantitative strategies is “pandas” which provides effective time series analysis and was kick-started by members of the AQR team. In a recent International Business Times article, Data Investment Made Easy by Outsourcing – Saad Amen the CEO of Cuemacro highlights the changes that have occurred in the last 10-15 years:

“If I think back maybe 10 or 15 years ago, there simply weren’t as many tools out there if you wanted to do analysis of markets. Say for example you wanted to produce really nice charts to visualize your output, it was a lot more difficult to do that from a programmatic perspective — of course, you have things like Excel. But these days there are so many different possibilities for visualization that it means that I don’t have to spend a lot of time actually coding that stuff up. It’s already made my life a lot quicker and easier. So to some extent, it’s helping to level the playing field”  – Saad Amen CEO of Cuemacro

Python a powerful programming language is another crucial tool in the toolbox for quants. This language gives firms a way to integrate external data such as fundamental market data, pricing data, and even data such as big data sentiment analysis with other tools to backtest a variety of alpha generating strategies. Quantopian has built an extensive suite of back testing capability from python. Their tool set is enabling individuals throughout the globe to create bespoke trading algorithms.

The tight control of the specific signals and implementation details of each hedge fund’s alpha driving strategies is critical to their success. And there is great benefit to enabling access to an algorithmic analysis tool set in the quest for finding or creating talented new practitioners, integrating innovative data sets and continued evolution of alpha generating trading strategies.

“For obvious reasons, particular trading signals from hedge funds and similar organizations remain proprietary because part of their edge is in how they compute that. But at the same time, I have observed that hedge funds have actually started to open source some parts of their software. Not the signal bit; kind of more the infrastructure-related parts to it.” – Saad Amen CEO of Cuemacro

At RelateTheNews we embrace these tools while also ensuring we create effective proprietary alpha generating signals for capital markets participants globally. As we continue our growth our goals are to also contribute to this growing suite of open source tools which enable effective trading strategy creation, evaluation and implementation.