Composite Market Momentum Index (CMM)***

The Composite Market Momentum Index (CMMI), developed by Alcides Davila, a Miami-based Business Consultant, functions as a specialized momentum oscillator within sophisticated technical frameworks such as the Composite Predictive Index (CPI-IGv5)***. Davila's background in volatile sectors informs CMMI's design, emphasizing resilient, multi-layered analysis to navigate market uncertainties. At its essence, CMMI synthesizes momentum from RSI and momentum indicators, serving as a key input to CPI-(IGv5's)*** probability engine for directional forecasts.
The primary purpose of CMMI is to assess market strength and potential shifts, helping traders identify high-probability opportunities while mitigating risks from isolated metrics. Integrated into CPI-IGv5, it bolsters the "probUp" metric—a probabilistic estimate of upward price action—by fusing complementary factors, yielding a claimed 68-80% trend-prediction accuracy in backtests. Productivity is moderate to high under trending conditions, where multi-indicator redundancy reduces false positives. Still, it may underperform in ranging or highly volatile markets, necessitating user-led backtesting to assess real-world efficacy.
Mathematically, CMMI originates from a 9-period momentum applied to a 14-period RSI, enhanced by a 3-period smoothed short RSI to create the base composite. It undergoes Z-score standardization over a 50-bar window for normalization, followed by a linear weighted sum with other elements (e.g., 0.10 allocation to momentum). Logical enhancements include using the hyperbolic tangent (tanh) for value bounding and cumulative distribution function (CDF) or logistic mappings to derive probabilities, ensuring outputs are statistically rigorous. Threshold logic governs signals: overbought alerts trigger on crossovers above 75 (normalized scale), oversold below 25, with strict pro filters at 0.55 (buy) and 0.45 (sell) on a 0-1 basis, often requiring confirmations from EMA slopes, POC crossovers, or volume deltas. This gated approach adds precision by filtering signals through base, strong, and ultra categories based on probUp thresholds, such as>0.68 for medium-term entries.
Versatility is evident in CMMI's multitimeframe adaptability, supporting modes from scalping (1-minute resolution, short multipliers) to long-term (daily, extended lookbacks up to 500 bars), dynamically adjusting via secure data requests to incorporate live and historical momentum. It accommodates diverse assets, including commodities—Davila's focus—equities, and forex, with customizable weights and manual inputs ([-1,1] scale) for external variables like news impact (elevated to 0.20 for emphasis) or industry segments (0.05), allowing fine-tuning for macroeconomic or sector-specific contexts. Efficiency is achieved through real-time rolling sums, Z-windows, and resource optimizations (e.g., max 500 bars/lines/labels), minimizing computational overhead while enabling cooldowns to mitigate alert fatigue in high-frequency setups.
For enhanced application, pair with confirmatory indicators such as MACD ratios or VWAP, and use strategy modes to backtest signal viability across horizons. Target investors include day traders and scalpers seeking quick, data-driven entries, institutions focused on commodity analysis, and technically adept retail users, all of whom benefit from its probabilistic framework over rigid rules. While versatile, CMMI's closed-source aspects in Pine Script limit full transparency, underscoring the need for empirical testing.