EMA Hybrid: A Hybrid Technical Indicator for Market Trend Detection

This paper introduces the EMA Hybrid, a novel hybrid technical indicator designed for robust market trend detection in dynamic trading environments. The indicator integrates quantitative market microstructure data with qualitative sentiment and regime factors through a two-layer adaptive architecture. 

The quantitative base layer employs an enhanced exponential moving average recursion with context-weighted price inputs and adaptive smoothing coefficients. This layer incorporates volume ratios, volatility scaling, buy-sell pressure, VWAP deviations, and order book imbalances to model market conviction dynamics. 

The qualitative overlay layer modulates the quantitative base through a powered multiplier aggregating social media sentiment, fear \& greed indices, geopolitical risk metrics, and cross-asset correlation regimes. This layer adjusts indicator responsiveness according to broader market psychology and external risk factors.

Hybrid integration dynamically adapts reversal thresholds and trend classification based on the qualitative context, requiring stronger quantitative confirmation during contradictory regimes while lowering barriers in high-conviction environments. The system includes a low-energy filter to suppress signals during low-volume, low-volatility periods.