Chaos theory's application in financial markets offers a distinct perspective beyond conventional models, focusing on non-linear and complex dynamics. Key concepts include attractors, fractals, and the butterfly effect. Attractors represent recurring patterns or levels toward which markets gravitate. Fractals show consistent patterns across different timeframes, relevant to technical analysis. The butterfly effect highlights sensitivity to initial conditions, complicating long-term forecasts.

Chaos theory aids in volatility analysis, with models like phase space reconstruction providing insights into market behavior. The Lyapunov exponent measures chaos, indicating a system's sensitivity to change. Positive values show unpredictability, while negative values suggest stability. Implementing the Lyapunov exponent in MQL5 can enhance trading strategies,...
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