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Autor(en): 
  • Hilpisch Yves
  • Python for Algorithmic Trading: From Idea to Cloud Deployment 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 2-7 Tagen versandfertig
    Veröffentlichung:  November 2020  
    Genre:  EDV / Informatik 
     
    Accounting software / Algorithms & data structures / algorithms and data structures / BUSINESS & ECONOMICS / E-Commerce / Online Trading / COMPUTERS / Computer Science / COMPUTERS / Information Technology / COMPUTERS / Languages / Python / COMPUTERS / Programming / Algorithms
    ISBN:  9781492053354 
    EAN-Code: 
    9781492053354 
    Verlag:  O'Reilly 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 233 mm / B 178 mm / D 20 mm 
    Gewicht:  654 gr 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and indivisual traders using online platforms. The tool of choice for many traders today is Python and its ecosystems 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. Ny 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 trading platforms.

      



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