Ming Wang

Mastering Financial Pattern Recognition - Finding and Back-Testing Candlestick

Description: 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

Price: 110 AUD

Location: Hillsdale, NSW

End Time: 2025-02-12T20:35:20.000Z

Shipping Cost: 30.98 AUD

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Mastering Financial Pattern Recognition - Finding and Back-Testing CandlestickMastering Financial Pattern Recognition - Finding and Back-Testing CandlestickMastering Financial Pattern Recognition - Finding and Back-Testing CandlestickMastering Financial Pattern Recognition - Finding and Back-Testing Candlestick

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Return shipping will be paid by: Buyer

Returns Accepted: Returns Accepted

Item must be returned within: 60 Days

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EAN: 9781098120474

UPC: 9781098120474

ISBN: 9781098120474

MPN: N/A

Format: Paperback, 288 pages

Author: Kaabar, Sofien

Book Title: Mastering Financial Pattern Recognition - Finding

Item Height: 1.6 cm

Item Length: 23.3 cm

Item Weight: 0.38 kg

Item Width: 17.8 cm

Language: Eng

Publisher: O'Reilly Media

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