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Autor(en): 
  • Sofien Kaabar
  • Mastering Financial Pattern Recognition: Finding and Back-Testing Candlestick Patterns with Python 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  November 2022  
    Genre:  Wirtschaft / Recht 
     
    Algorithms & data structures / algorithms and data structures / BUSINESS & ECONOMICS / Finance / General / Business & Economics / Investments & Securities / General / COMPUTERS / Data Science / Machine Learning / COMPUTERS / Interactive & Multimedia / COMPUTERS / Mathematical & Statistical Software / COMPUTERS / Programming / Algorithms
    ISBN:  9781098120474 
    EAN-Code: 
    9781098120474 
    Verlag:  O'Reilly 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 215 mm / B 175 mm / D 15 mm 
    Gewicht:  520 gr 
    Seiten:  464 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    Candlesticks have become a key component of platforms and charting programs for financial trading. With these charts, traders can learn underlying patterns for interpreting price action history and forecasts. This A-Z guide shows portfolio managers, quants, strategists, and analysts how to use Python to recognize, scan, trade, and back-test the profitability of candlestick patterns.

    Financial author, trading consultant, and institutional market strategist Sofien Kaabar shows you how to create a candlestick scanner and indicator so you can compare the profitability of these patterns. With this hands-on book, you'll also explore a new type of charting system similar to candlesticks, as well as new patterns that have never been presented before.

    With this book, you will:

    • Create and understand the conditions required for classic and modern candlestick patterns
    • Learn the market psychology behind them
    • Use a framework to learn how back-testing trading strategies are conducted
    • Explore different charting systems and understand their limitations
    • Import OHLC historical FX data in Python in different time frames
    • Use algorithms to scan for and reproduce patterns
    • Learn a pattern's potential by evaluating its profitability and predictability

      



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