Variable Index Dynamic Average (VIDYA) Professional Family

1. Summary (Introduction)

The Variable Index Dynamic Average (VIDYA), developed by Tushar Chande, is a sophisticated adaptive moving average that automatically adjusts its speed based on market momentum. It uses the Chande Momentum Oscillator (CMO) to dynamically alter its smoothing factor. When momentum is high, VIDYA becomes more sensitive and follows prices closely. When momentum wanes in a consolidating market, it slows down and smooths out price action.

Our professional implementation is an indicator family consisting of two versions, both powered by a single, universal calculation engine:

VIDYA_Pro: The classic, single-color implementation that acts as a pure adaptive trend line.
VIDYA_Color_Pro: An enhanced version that changes color based on the direction of the underlying momentum (CMO positive or negative), providing an additional layer of visual information.

Both indicators support calculations based on either standard or Heikin Ashi price data.

2. Mathematical Foundations and Calculation Logic

VIDYA is a modified Exponential Moving Average where the smoothing factor is multiplied by the absolute value of the Chande Momentum Oscillator (CMO).

Required Components

EMA Period (N): The base period for the EMA smoothing calculation.
CMO Period (M): The lookback period for the Chande Momentum Oscillator.
Source Price (P): The price series used for the calculation.

Calculation Steps (Algorithm)

Calculate the Chande Momentum Oscillator (CMO): The CMO measures momentum over a period M, oscillating between -100 and +100.
- \text{Sum Up}_i = \text{Sum of positive price changes over M periods}
- \text{Sum Down}_i = \text{Sum of absolute negative price changes over M periods}
- \text{CMO}_i = 100 \times \frac{\text{Sum Up}_i - \text{Sum Down}_i}{\text{Sum Up}_i + \text{Sum Down}_i}
Calculate the VIDYA: The VIDYA is calculated recursively.
- First, define the standard EMA smoothing factor, alpha: \alpha = \frac{2}{N + 1}
- Then, calculate the VIDYA for each bar. Note that the formula uses the absolute value of the CMO (normalized to a 0-1 range) to adjust the speed, not the direction. \text{VIDYA}_i = (P_i \times \alpha \times \text{Abs}(\frac{\text{CMO}_i}{100})) + (\text{VIDYA}_{i-1} \times (1 - \alpha \times \text{Abs}(\frac{\text{CMO}_i}{100})))

3. MQL5 Implementation Details

Our MQL5 implementation is built on a highly efficient and reusable object-oriented architecture.

Universal Calculation Engine (VIDYA_Calculator.mqh): A single, powerful engine file contains all the core calculation logic. This eliminates code duplication and ensures that both VIDYA_Pro and VIDYA_Color_Pro produce identical average values.
Composition with CMO Engine: The VIDYA calculator does not re-implement the CMO logic. Instead, it internally instantiates our robust CMO_Calculator class. This ensures that the momentum measurement is mathematically identical to the standalone CMO indicator.
Optimized Incremental Calculation: Unlike basic implementations that recalculate the entire history on every tick, this indicator employs an intelligent incremental algorithm.
- It utilizes the prev_calculated state to determine the exact starting point for updates.
- Persistent State: The internal buffers (m_price, m_cmo_buffer) persist their state between ticks. This allows the recursive VIDYA calculation to continue seamlessly from the last known value without re-processing the entire history.
- This results in O(1) complexity per tick, ensuring instant updates and zero lag.
Method Overloading: The CVIDYACalculator class features two versions of the Calculate method:
1. Calculate(..., double &vidya_buffer[]): A version that accepts a single output buffer. This is automatically called by VIDYA_Pro.
2. Calculate(..., double &vidya_up_buffer[], double &vidya_down_buffer[]): A version that accepts two output buffers. This is automatically called by VIDYA_Color_Pro.
Object-Oriented Design (Inheritance): The engine uses a CVIDYACalculator base class and a CVIDYACalculator_HA derived class. The child class only overrides the PreparePriceSeries method to supply Heikin Ashi data, inheriting the entire complex calculation logic from its parent.

4. Parameters (`VIDYA_Pro` & `VIDYA_Color_Pro`)

The input parameters are identical for both indicators.

CMO Period (InpPeriodCMO): The lookback period for the Chande Momentum Oscillator. Default is 9.
EMA Period (InpPeriodEMA): The base period for the EMA smoothing. Default is 12.
Applied Price (InpSourcePrice): The source price for the calculation. This unified dropdown menu allows you to select from all standard and Heikin Ashi price types.

5. Usage and Interpretation

`VIDYA_Pro` (Single Color)

Adaptive Trend Line: Use it as a more intelligent, responsive trend line. It hugs the price during strong trends and flattens out during consolidation, helping to reduce whipsaws.
Trend Filter: A flat or sideways VIDYA line is a strong indication of a ranging market, suggesting that trend-following strategies should be paused.
Dynamic Support/Resistance: In a trending market, the VIDYA line can act as a dynamic level of support (in an uptrend) or resistance (in a downtrend).

`VIDYA_Color_Pro` (Multi-Color)

This version includes all the benefits of the standard VIDYA_Pro but adds an immediate visual cue for momentum direction.

Trend Direction at a Glance:
- Green Line: Indicates that the underlying momentum is bullish (CMO > 0).
- Red Line: Indicates that the underlying momentum is bearish (CMO < 0).
Confirmation of Trend Change: A color change from red to green can act as an early confirmation that bullish momentum is taking over, and vice-versa. This can be particularly useful for timing entries after a pullback. For example, in a larger uptrend, a brief switch to red followed by a return to green can signal a good entry point.

6.1 KiB Raw Blame History