Python for Finance: Mastering Data-Driven Finance

The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics.

Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full fledged framework for Monte Carlo simulation based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.

• Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging (The Wiley Finance Series)
• Mastering Python for Finance: Implement advanced state-of-the-art financial statistical applications using Python, 2nd Edition
• What Hedge Funds Really Do: An Introduction to Portfolio Management
• Algorithmic Trading with Interactive Brokers (Python and C++)
• Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
• Machine Learning (McGraw-Hill International Editions Computer Science Series)
• Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
• Trading Evolved: Anyone can Build Killer Trading Strategies in Python
• Advances in Financial Machine Learning
• Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python