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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.
Machines can perform pattern recognition and detection better than humans because of their objectivity. Therefore, I have dedicated the first chapters of the book to creating the structure of a candlestick pattern recognition algorithm before moving on to dig deep into patterns and strategies in the later chapters. This means that the first skill you will learn is how to automate the data import process in Python.
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
Target Audience:
This book is suited for aspiring students, academics, curious minds, and finance practitioners who are interested in candlestick pattern recognition and its applications in finance using Python but also in developing strategies and technical indicators. The book makes the assumption that the reader has a basic background knowledge in both Python programming (professional Python users will find the code very straightforward) and in financial trading. I take a detailed and simple approach that focuses on the key concepts so that you understand the purpose and the know-how of every idea