Enhanced ML-FRAMA with HTF

Core Concept

FRAMA (Fractal Adaptive Moving Average) is an adaptive moving average that automatically adjusts its sensitivity based on market volatility using fractal geometry. This indicator enhances it with Machine Learning predictions and multi-timeframe analysis.

Key Components:

1. ML-Enhanced FRAMA

ML Enhancement: Uses machine learning to adjust FRAMA's sensitivity

Dynamic Adaptation: ML predictions modify the smoothing constant based on market conditions


2. Machine Learning System

Three ML Models Combined:

K-Nearest Neighbors (KNN): Finds similar historical patterns

Trend Model: Uses EMA crossovers for trend detection

Momentum Model: Combines RSI, ROC, and volume for momentum

Features Used:

RSI, MACD, ATR, Rate of Change

Volume ratio and momentum

VWAP deviation

Higher timeframe RSI

Daily EMA trend

3. Higher Timeframe Integration

HTF1: 1-hour timeframe

HTF2: 4-hour timeframe

Confluence Trading: Requires agreement across multiple timeframes

4. Visual Features

Support/Resistance Circles: Dynamic levels based on ATR volatility

Color Coding:

Green: Bullish signals

Red: Bearish signals

Purple/Orange: HTF indicators

Trend Detection: Colors change based on direction


Requirements for Bullish Signal:

Price crosses above ML-FRAMA

ML prediction > 60% bullish

High confidence (>30%)

Volume 20% above average

Both HTF timeframes bullish

Performance Tracking:

Adaptive Weights: Automatically adjusts model weights based on recent accuracy

Dynamic K: Adjusts KNN neighbors based on market volatility

Outlier Detection: Filters unusual bars from training data

Trading Philosophy:
Multi-Timeframe Confirmation

Avoids false signals by requiring HTF agreement

Reduces noise by focusing on higher probability setups

Volume Confirmation

Requires above-average volume for valid signals

Volume momentum adds conviction

Machine Learning Edge

Learns from historical patterns

Adapts to changing market conditions

Combines multiple analysis techniques

Use Cases:

Trend Following: ML-FRAMA as dynamic support/resistance

Breakout Trading: Price crosses with volume and HTF confirmation

Mean Reversion: Support/resistance circles as reversal zones

Swing Trading: HTF confluence for higher probability setups

Strengths:

Adaptive: Adjusts to market volatility

Multi-timeframe: Reduces false signals

Volume-confirmed: Adds conviction

ML-enhanced: Learns from market behavior

Visual: Clear support/resistance levels

Ideal For:

Swing traders looking for high-probability entries

Trend followers wanting adaptive moving averages

Technical analysts who value multi-timeframe confirmation

Traders who want machine learning without complexity

The indicator essentially creates a "smart" adaptive moving average that learns from the market and only provides signals when multiple timeframes and technical factors align.