The low learning curve Python programming language has grown in popularity over the past decade. Data Scientists, algorithmic developers, quantitative financial professionals, and market enthusiasts have helped this become a strong tool for algorithmic research, development, and trading. Python for the trading industry comes with tools including:

  • Jupyter notebooks
  • NumPy for High-Speed Numerical Processing
  • Pandas for Efficient Data Analysis and Time Series Analysis Techniques
  • Matplotlib for Data Visualization
  • TA-Lib for Technical Analysis
  • Tensor flow


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Conversations: What we wish we knew when we started AlgoTrading

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CloudQuant's portfolio managers and quantitative algo traders look back on their starts in Algorithmic Trading. This candid overview allows everyone to see the "Things We Wish We Knew When We Started AlgoTrading".  This is a short collection of the interviews with some of our amazing coders here in the office

CloudQuant presentation for the Students of the University of Chicago Financial Program

A video introduction to the CloudQuant Trading Strategy Incubator by data scientist, Nicolaus Schmandt
Backtest Homepage showing P&L and Sharpe

CloudQuant rolls out Upgrades to Free Stock Market Backtesting System

CloudQuant, the trading strategy incubator, announces upgrades to our free stock market backtesting system. The web application allows any market enthusiasts to develop a trading strategy using easy to learn Python programming. Anyone who has ever written a spreadsheet macro or a simple program can easily use the system.
Trevor Trinkino Quantitative Trader

FXCM Machine Learning with Trevor Trinkino

On February 8th Trevor Trinkino presented Machine Learning with FXCM in a webinar. During this presentation, he promised to make available his machine learning Python Notebook and the supporting data file. These are available on our Google drive at:
Trading Strategy Scorecard from CloudQuant

One Minute Trader Podcast with Tayloe Draughon of CloudQuant

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One Minute Trader with Matt Davio recently interviewed Tayloe Draughon to discuss Crowd Sourced Trading Ideas using our trading strategy incubator.
Young women getting started in technology

Young Women: Programming Helps!

The first book I got was “Hello World”. The book intimidated me, because I saw programming as a superpower, something only my dad was capable enough to do. I tried to learn it, but I just got bored very quickly. My dad, still persistent, decided it was time to try programming something we loved.
Backtest Research Life Cycle for Trading Strategies

Backtesting Trading Strategies

If you knew your trading strategy would work 50% of the time, would you commit your scarce savings to trade it? What if it worked 75% of the time? Backtesting gives one the confidence to know that your trading strategy will work.
Three Inside Up Technical Pattern shown on $IBM Jan 2, 2018

TA-LIB Three Inside Up Buy Signal - $IBM

IBM, the 100-year-old company, is wedging into a tight trade, but it looks like the Bulls are gearing to press a move higher. Just before year-end, the stock set a Three Inside Up Japanese candlestick pattern setting the stage for a rally. Source code using TA-LIB and Python included.
Harami Sell Signal on Google Dec 20, 2017

Harami Sell Signal with Three Inside Down Demonstrated on $GOOG

December 19, 2017 Monday Google pressed new highs, but Tuesday closed out the day with a Harami Sell signal. Watch out for today. A negative close today boosts the negative outlook with the emergence of a Three Inside Down pattern. In this event, it will most likely mean that there will be a “little coal in Google stockholders stockings for Christmas”.

Technical Analysis Library (TA-LIB) for Python Backtesting

Anyone who has ever worked on developing a trading strategy from scratch knows the huge amount of difficulty that is required to get your logic right. ... TA-LIB Turbo-Charges Your Research Loop: TA-Lib is widely used by quantitative researchers and software engineers developing automated trading systems and charts. This freely available tool allows you to gather information on over 200 stock market indicators.