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Mastering Financial Pattern Recognition Finding And Backtesting Candlestick Patterns With Python 1st Edition Sofien Kaabar

  • SKU: BELL-54588162
Mastering Financial Pattern Recognition Finding And Backtesting Candlestick Patterns With Python 1st Edition Sofien Kaabar
$ 31.00 $ 45.00 (-31%)

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Mastering Financial Pattern Recognition Finding And Backtesting Candlestick Patterns With Python 1st Edition Sofien Kaabar instant download after payment.

Publisher: O'Reilly Media
File Extension: PDF
File size: 6.42 MB
Pages: 291
Author: Sofien Kaabar
ISBN: 9781098120474, 1098120477
Language: English
Year: 2022
Edition: 1

Product desciption

Mastering Financial Pattern Recognition Finding And Backtesting Candlestick Patterns With Python 1st Edition Sofien Kaabar by Sofien Kaabar 9781098120474, 1098120477 instant download after payment.

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 backtest 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 guide, 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 backtesting 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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