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Herausgeber: 
  • Danny Munrow
    Autor(en): 
  • James Preston
  • Algorithmic Trading Recipes in Python: Strategies for Stocks, Forex, and Crypto 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Juni 2026  
    Genre:  Wirtschaft / Recht 
     
    BUSINESS & ECONOMICS / E-Commerce / Online Trading / BUSINESS & ECONOMICS / Investments & Securities / Analysis & Trading Strategies
    ISBN:  9798183518139 
    EAN-Code: 
    9798183518139 
    Verlag:  Independently Published 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 229 mm / B 152 mm / D 24 mm 
    Gewicht:  450 gr 
    Seiten:  372 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Reactive Publishing

    Algorithmic Trading Recipes in Python delivers practical, ready-to-implement code examples for developing systematic trading strategies across major financial markets.

    This book provides a collection of Python recipes covering core techniques used in algorithmic trading. Readers will find working code examples for data handling, strategy implementation, backtesting, and execution workflows tailored to stocks, forex, and cryptocurrency markets.

    Whether you are an intermediate Python developer exploring quantitative trading or a trader looking to automate your approaches, these recipes offer concrete starting points and modular building blocks.

    What's Inside: - Reproducible Python code examples for common trading tasks
    - Strategy frameworks for trend following, mean reversion, momentum, and more
    - Data acquisition, cleaning, and feature engineering techniques
    - Backtesting and performance evaluation methods
    - Market-specific considerations for equities, forex, and crypto

    Important Note: Trading involves substantial risk of loss and is not suitable for everyone. The strategies and code in this book are for educational and illustrative purposes only. Past performance does not guarantee future results. Readers should conduct their own research and testing before applying any trading approach with real capital.

    Ideal for developers, quantitative enthusiasts, and traders interested in building and testing systematic strategies in Python.

      



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