Elliott Wave Theory in Finance

Elliott Wave Theory in Finance: From Subjective Interpretation to Testable Models with Python examines how far a traditionally discretionary approach can be expressed as explicit, testable rules. Sofien Kaabar, CFA, develops a Python framework for identifying swings, evaluating impulse and corrective counts, preserving alternate interpretations, and recording when each decision became possible. Worked market charts connect theory to prospective forecasts, while empirical tests across stocks and foreign exchange compare wave-based strategies with matched random entries and account for trading costs. The book offers readers a way to investigate Elliott Wave claims rigorously; it does not present a ready-made profitable trading system. Features Explains Elliott Wave structure, Fibonacci projections, confirmation delays and invalidation in accessible language. Provides Python examples and charting tools for readers who want to implement and test the rules themselves. Includes a companion GitHub repository and reports backtests with trading costs and random-entry controls.