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Python for algorithmic trading : from idea to cloud deployment / Yves J. Hilpisch
Sebastopol, CA : O'Reilly, 2021
379 pages. : illustrations ; cm.
Ký hiệu phân loại (DDC): 332.64
Financial trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM platforms
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Python for finance : mastering data-driven finance / Yves J. Hilpisch
Sebastopol, CA : O'Reilly Media, 2019
714 pages. : illustrations ; 24 cm.
Ký hiệu phân loại (DDC): 332.0285
Python has become the programming language of choice for data-driven and AI-first finance. Some of the largest investment banks and hedge funds now use Python and its ecosystem for building core trading and risk management systems. In the second edition of this guide, Yves Hilpisch shows developers and quantitative analysts how to use Python packages and tools for financial data science, algorithmic trading, and computational finance
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The time-discrete method of lines for options and bonds : a PDE approach / Gunter H. Meyer
New Jersey : World Scientific, 2015
xv, 269 pages. : illustrations ; 25 cm.
Ký hiệu phân loại (DDC): 332.632
Few financial mathematical books have discussed mathematically acceptable boundary conditions for the degenerate diffusion equations in finance. In The Time-Discrete Method of Lines for Options and Bonds, Gunter H. Meyer examines PDE models for financial derivatives and shows where the Fichera theory requires the pricing equation at degenerate boundary points, and what modifications of it lead to acceptable tangential boundary conditions at non-degenerate points on computational boundaries when no financial data are available. Extensive numerical simulations are carried out with the method of lines to examine the influence of the finite computational domain and of the chosen boundary conditions on option and bond prices in one and two dimensions, reflecting multiple assets, stochastic volatility, jump diffusion and uncertain parameters. Special emphasis is given to early exercise boundaries, prices and their derivatives near expiration. Detailed graphs and tables are included which may serve as benchmark data for solutions found with competing numerical methods
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