Algorithmic Trading in Python Thomas Wiecki @twiecki 

About me 

About me 

Rise of the machines 84% of all stock trades are done by computers vs Rationality Speed Capacity Intuition Understanding Speech - Cognitively biased / emotional - Human - Limited + 50 years of experience + Knows how the market works + Native speaker + Purely analytical + 1 TFLOP + Big Data - None - Depends on programming - “I'll be back” 

Pythonic Algorithmic Trading Pipeline Data Analysis Generate ideas Tools: ● Pandas ● Matplotlib ● (Seaborn) ● IPython Backtesting Test on historical data whether idea can be exploited. Tools: ● Zipline ● Quantopian ● PyAlgoTrader Forward testing Paper-trade on real-time market data. Tools: ● Quantopian Live trading Trade with real money. Tools: ● Quantopian (soon) optimize 

Algorithmic Trading: Backtesting Historical stock data ● datetime ● Price ● Volume Trading Algorithm ● Applies transforms (e.g. mavg) ● Makes trading decision ● Places orders ● Transaction costs ● Slippage ● Order delay Performance and Risk analysis 

Zipline ● Trading simulator/backtester written in Python ● Open-Source (Apache 2.0) ● Stream-based (prevents look-ahead bias) ● Batteries included – Moving average, Sharpe, alpha, beta... ● Used in production on Quantopian.com – Contribute back to community – Linus' law: "given enough eyeballs, all bugs are shallow" ● http://zipline.io 

Interoperability 

Architecture Source Moving Average VWAP Regression User Algorithm Transaction Simulator Transform layer places orders executes orders Emits price and volume info 

Go to: http://bit.ly/1cx0Gj7 

Conclusions ● Zipline gives you full control over you backtest. ● Copy & paste your Zipline algorithm to Quantopian: – Share it, get feedback. – Test it on minute data. – Forward test it. – Go live (soon!) 

Come hack Wall Street. Questions? @twiecki @quantopian