mql5/Indicators/MyIndicators/VIDYA_TrendActivity_Pro.md

VIDYA Trend Activity Professional

1. Summary (Introduction)

The VIDYA Trend Activity is a custom-built "meta-indicator" designed to measure the directional strength and activity of the Variable Index Dynamic Average (VIDYA). While the VIDYA line itself shows the trend, this oscillator quantifies how trendy the market is according to the VIDYA's behavior.

Its primary purpose is to act as a trend filter. It generates high values when the VIDYA is moving decisively and low values when the VIDYA line flattens out.

Our VIDYA_TrendActivity_Pro implementation is a unified, professional version that allows all underlying calculations (both VIDYA and ATR) to be based on either standard or Heikin Ashi data.

2. Mathematical Foundations and Calculation Logic

This indicator analyzes the behavior of two underlying indicators, VIDYA and ATR, to produce a final, normalized oscillator.

Required Components

• VIDYA: The underlying adaptive moving average. Its slope is the primary input.
• ATR (Average True Range): Used as a normalization factor.
• Smoothing Period: A final smoothing period for the oscillator output.

Calculation Steps (Algorithm)

1. Calculate VIDYA: First, the standard VIDYA is calculated.
2. Calculate ATR: Separately, the standard Wilder's ATR is calculated.
3. Calculate Raw Activity: For each bar, the indicator measures the rate of change of the VIDYA line and normalizes it by the market's current volatility (ATR). \text{Raw Activity}_i = \frac{\text{Abs}(\text{VIDYA}_i - \text{VIDYA}_{i-1})}{\text{ATR}_i}
4. Normalize with Arctan: The Raw Activity value is passed through the inverse tangent (Arctan) function and scaled to a consistent 0..1 range. \text{Scaled Activity}_i = \frac{\text{Arctan}(\text{Raw Activity}_i)}{\pi/2}
5. Final Smoothing: The Scaled Activity values are smoothed with a Simple Moving Average (SMA). \text{Final Activity}_i = \text{SMA}(\text{Scaled Activity}, \text{Smoothing Period})_i

3. MQL5 Implementation Details

Our MQL5 implementation follows a modern, component-based, object-oriented design.

• Component-Based Design: The VIDYA_TrendActivity_Calculator reuses our existing, standalone VIDYA_Calculator.mqh and ATR_Calculator.mqh modules. This eliminates code duplication and ensures consistency.

• Object-Oriented Logic:

  • The CVIDYATrendActivityCalculator base class contains pointers to the VIDYA and ATR calculator objects.
  • The Heikin Ashi version (CVIDYATrendActivityCalculator_HA) is achieved simply by instantiating the Heikin Ashi version of the VIDYA module (CVIDYACalculator_HA). The ATR calculator type is chosen dynamically based on user input.

• Stability via Full Recalculation: We employ a "brute-force" full recalculation within OnCalculate for maximum stability.

4. Parameters

• VIDYA Settings:
  • InpPeriodCMO: The period for the underlying Chande Momentum Oscillator.
  • InpPeriodEMA: The base period for the underlying VIDYA.
  • InpSourcePrice: The source price for the underlying VIDYA. This unified dropdown allows you to select from all standard and Heikin Ashi price types.
• Activity Calculation Settings:
  • InpAtrPeriod: The period for the ATR used in normalization.
  • InpAtrSource: Determines the source for the ATR calculation (Standard or Heikin Ashi).
  • InpSmoothingPeriod: The period for the final SMA smoothing of the oscillator.

5. Usage and Interpretation

• Trend Filter: This is the indicator's primary function. A trader can establish a threshold (e.g., 0.1 or 0.2).
  • Activity > Threshold: The market is considered to be in a trending phase.
  • Activity < Threshold: The market is considered to be in a ranging or consolidating phase.
• Identifying Trend Exhaustion: A sharp decline in the activity histogram after a strong trend can signal that momentum is waning.
• Confirming Breakouts: A spike in the activity histogram accompanying a price breakout can provide strong confirmation that the breakout has momentum.