Top 7 Python Libraries Popular In The FinTech Sector

According to PricewaterhouseCoopers, over $150 billion will be invested in FinTech companies over the next 3 to 5 years. FinTech has its reach in domains like insurance, lending, regulations, trading, e-banking and other payment services, and thus has a wide scope.

The rise in popularity of Python as a programming language can be verified with the increase in the number of FinTech startups employing Python and its frameworks. Investment banking and hedge fund industries are also using Python to solve quantitative problems for pricing, trade management, and risk management platforms.

“Everyone at JP Morgan now needs to know Python and there are around 5,000 developers using it at Bank of America. There are close to 10 million lines of Python code in Quartz and we got close to 3,000 commits a day,” Kirat Singh, former MD of Bank of America told anewsportal.

Citi group is also encouraging their analysts to pick up Python coding skills and the list continues. Python is even more popular with startups because of its simplicity and the ease with which the product can be taken to the market.

Choosing a language or a framework is important for a young company as factors like talent access, ease of validation and how quickly the product can be built has a greater impact on its life cycle.

Here are some of the top open-source Python libraries assisting the FinTech industry:

PyAlgoTrade is an event-driven algorithmic trading Python library which supports back-testing, live-feed paper trading and real-time trading on Bitstamp. PyAlgoTradeis developed and tested using Python 2.7/3.7 and dependencies include NumPy and SciPy,pytz, matplotlib for plotting support,tornadofor Bitstamp support and tweepy for Twitter support.

Here we see how data series abstractions can be made using PyAlgoTrade:

It primarily deals with the risk analytics and performance related financial portfolios. This was developed and is maintained byQuantopianandwas open-sourced in 2015.It works well with the Zipline open source backtesting library.Pyfolio library can be used to model tear sheets based on returns,Bayesiananalysis and other transactions. Other features include plotting tear sheets withpyfolio.plottingandpyfolio.timeseriesfor calling individual statistical functions.

Zipline is an open-source algorithmic trading simulator written in Python. It is used to simulaterealistic slippage, transaction costs and order delays. Process each event individually and avoids look-ahead bias. Zipline too is maintained by Quantopian which updates zipline round-the-clock.

The quantecon python library consists of modules like game theory,Markovchains, random generation utilities (random), a collection of tools (tools), and other utilities (util) which are mainly used by developers internal to the package.