Variable Index Dynamic Average (VIDYA) MTF Professional

1. Summary (Introduction)

The Variable Index Dynamic Average (VIDYA) MTF Pro is a multi-timeframe (MTF) version of the classic adaptive moving average developed by Tushar Chande. This indicator calculates the VIDYA on a higher, user-selected timeframe and projects it onto the current, lower-timeframe chart.

This allows traders to visualize the underlying trend from a broader perspective, using the higher-timeframe VIDYA as a dynamic benchmark for support, resistance, and overall market direction, all without leaving their primary trading chart.

The indicator is highly versatile: if the user selects the current chart's timeframe, it functions identically to the standard VIDYA_Pro indicator. It also fully supports both standard and Heikin Ashi price data.

2. Mathematical Foundations and Calculation Logic

The underlying calculation is identical to the standard VIDYA. It 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 from the higher timeframe used for the calculation.

Calculation Steps (Algorithm)

Fetch Higher Timeframe Data: The indicator first retrieves the OHLC price data for the user-selected higher timeframe.
Calculate the Chande Momentum Oscillator (CMO): The CMO is calculated on the higher timeframe's price data over a period M. \text{CMO}_{htf} = \frac{\text{Sum Up}_{htf} - \text{Sum Down}_{htf}}{\text{Sum Up}_{htf} + \text{Sum Down}_{htf}}
Calculate the VIDYA on the Higher Timeframe: The VIDYA is calculated recursively using the higher timeframe data.
- \alpha = \frac{2}{N + 1}
- \text{VIDYA}_{htf_i} = (P_{htf_i} \times \alpha \times \text{Abs}(\text{CMO}_{htf_i})) + (\text{VIDYA}_{htf_{i-1}} \times (1 - \alpha \times \text{Abs}(\text{CMO}_{htf_i})))
Project to Current Chart: The calculated higher-timeframe VIDYA values are then mapped to the current chart, creating a "step-like" line where each value from the higher timeframe is held constant for the duration of its corresponding bars on the lower timeframe.

3. MQL5 Implementation Details

Self-Contained and Robust: This indicator is fully self-contained and does not depend on any external indicator files (iCustom). It directly fetches the required higher-timeframe price data using built-in Copy... functions for maximum stability.
Modular Calculation Engine (VIDYA_Calculator.mqh): The indicator reuses the exact same, proven calculation engine as the standard VIDYA_Pro. This ensures mathematical consistency and leverages our modular design principles.
Dual-Mode Logic: The OnCalculate function contains a smart branching logic.
- If a higher timeframe is selected, it performs the full MTF data fetching and projection process.
- If the current timeframe is selected, it bypasses the MTF logic and functions identically to the standard VIDYA_Pro, calculating directly on the current chart's data for maximum efficiency.
Stability via Full Recalculation: We employ a full recalculation for both modes, which is the most reliable method for a recursive indicator like VIDYA.

4. Parameters

Upper Timeframe (InpUpperTimeframe): The higher timeframe on which the VIDYA will be calculated. If set to PERIOD_CURRENT, the indicator will run on the current chart's timeframe.
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

The MTF version of VIDYA opens up new strategic possibilities beyond simple trend following.

Dynamic Support and Resistance: The primary use of the MTF VIDYA is as a dynamic, high-level area of support and resistance. When the price on the lower timeframe pulls back to the higher-timeframe VIDYA line, it can present a high-probability entry point in the direction of the larger trend.
Major Trend Filter: The slope and position of the MTF VIDYA line provide a clear, smoothed-out view of the dominant trend.
- If the price is consistently above a rising MTF VIDYA, the market is in a strong uptrend. Traders should focus on buying opportunities.
- If the price is consistently below a falling MTF VIDYA, the market is in a strong downtrend. Traders should focus on selling opportunities.
Confirmation of Breakouts: A breakout on the lower timeframe that is also supported by the direction of the MTF VIDYA line is a much stronger signal.
Range Detection: A flat MTF VIDYA line indicates that the higher timeframe is consolidating, signaling that range-bound strategies might be more appropriate on the lower timeframe.

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