The retail financial industry is saturated with methods sold as infallible and dissociated from evidence. Academic literature is clear about an uncomfortable reality: on average, systematically outperforming benchmark indices is statistically difficult, and most publicly disclosed strategies fail to preserve their performance outside of the sample in which they were designed.

Technical analysis, applied in isolation and mechanically, does not constitute a robust system. Patterns and levels used without context rarely survive an honest statistical test over long horizons, and the returns promised on social media seldom hold up outside of cherry-picked examples. This does not invalidate technical analysis as a timing tool — it invalidates it as a complete methodology.

The approach I apply does not seek to refute the Efficient Market Hypothesis; it explores inefficiencies documented in specific windows and regimes. It is a hybrid model, inspired by institutional practices and adapted to retail execution, integrating technical, fundamental and macroeconomic analysis. The priority is risk management and capital preservation across complete market cycles — return is a consequence, not a promise.