Mastering Financial Pattern Recognition: Finding and Back-Testing Candlestick Patterns with Python

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

蠟燭圖已成為金融交易平台和圖表程式的重要組成部分。透過這些圖表，交易員可以學習解讀價格行動歷史和預測的基本模式。這本A-Z指南向投資組合經理、量化交易員、策略師和分析師展示如何使用Python來識別、掃描、交易和回測蠟燭圖模式的盈利能力。

金融作家、交易顧問和機構市場策略師Sofien Kaabar向您展示如何創建蠟燭圖掃描器和指標，以便您可以比較這些模式的盈利能力。通過這本實用指南，您還將探索一種類似蠟燭圖的新型圖表系統，以及從未呈現過的新模式。

這本書將幫助您：
- 創建並了解經典和現代蠟燭圖模式所需的條件
- 學習背後的市場心理學
- 使用框架學習如何進行回測交易策略
- 探索不同的圖表系統並了解其限制
- 在Python中以不同的時間框架導入OHLC歷史外匯數據
- 使用算法掃描和重現模式
- 通過評估盈利能力和可預測性來了解模式的潛力