Mastering Python for Finance: Implement advanced state-of-the-art financial statistical applications using Python, Edition 2

• Explore advanced financial models used by the industry and ways of solving them using Python
• Build state-of-the-art infrastructure for modeling, visualization, trading, and more
• Empower your financial applications by applying machine learning and deep learning

• Solve linear and nonlinear models representing various financial problems
• Perform principal component analysis on the DOW index and its components
• Analyze, predict, and forecast stationary and non-stationary time series processes
• Create an event-driven backtesting tool and measure your strategies
• Build a high-frequency algorithmic trading platform with Python
• Replicate the CBOT VIX index with SPX options for studying VIX-based strategies
• Perform regression-based and classification-based machine learning tasks for prediction
• Use TensorFlow and Keras in deep learning neural network architecture

If you are a financial or data analyst or a software developer in the financial industry who is interested in using advanced Python techniques for quantitative methods in finance, this is the book you need! You will also find this book useful if you want to extend the functionalities of your existing financial applications by using smart machine learning techniques. Prior experience in Python is required.