Harness the power of Python libraries to transform freely available financial market data into algorithmic trading strategies and deploy them into a live trading environment Key Features Follow practical Python recipes to acquire, visualize, and store market data for market research Design, backtest, and evaluate the performance of trading strategies using professional techniques Deploy trading strategies built in Python to a live trading environment with API connectivity Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDiscover how Python has made algorithmic trading accessible to non-professionals with unparalleled expertise and practical insights from Jason Strimpel, founder of PyQuant News and a seasoned professional with global experience in trading and risk management. This book guides you through from the basics of quantitative finance and data acquisition to advanced stages of backtesting and live trading. Detailed recipes will help you leverage
