Mastering Financial Pattern Recognition: Finding and Back-Testing Candlestick Patterns with Python
Language: English
Published by O'Reilly Media, 2022
- Softcover
- Used
Condition: Used - Very good
US$ 54.75
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Complete and clean. All pages present and readable, binding intact. Highlighting or writing is absent or limited to a handful of pages. No water damage. Cover and spine may show light shelf wear, edge bumping, or minor creasing. May have a remainder mark, stickers or sticker residue, or a previous owner's name. Access codes, CDs, DVDs, and other bundled supplements may not be included and should be assumed used or missing unless the listing explicitly states otherwise.
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- Title
- Mastering Financial Pattern Recognition: Finding and Back-Testing Candlestick Patterns with Python
- Author
- Kaabar, Sofien
- Publisher
- O'Reilly Media
- Publication year
- 2022
- Condition
- Very Good
- Binding
- paperback
- Language
- English
- ISBN 10
- 1098120477
- ISBN 13
- 9781098120474
- Item weight
- 37 ounces
- Dimensions
- 7x0x9
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
"Synopsis" may belong to another edition of this title.
About the Author
Having elaborated many successful trading algorithms, Sofien is now sharing back the knowledge he has acquired over the years to make it accessible to everyone.
"About the title" may belong to another edition of this title.
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