diff --git a/Indicators/MyIndicators/VIDYA_MTF_Pro.md b/Indicators/MyIndicators/VIDYA_MTF_Pro.md index 4b3ac5e..36c7f18 100644 --- a/Indicators/MyIndicators/VIDYA_MTF_Pro.md +++ b/Indicators/MyIndicators/VIDYA_MTF_Pro.md @@ -2,63 +2,37 @@ ## 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. +The `VIDYA_MTF_Pro` is a multi-timeframe (MTF) version of Tushar Chande's adaptive moving average. It projects the VIDYA from a **higher, user-selected timeframe** onto the current 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 VIDYA adapts its speed based on the market's volatility (measured by the Chande Momentum Oscillator - CMO), making it an excellent tool for identifying the "true" trend of the higher timeframe. -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 -## 2. Mathematical Foundations and Calculation Logic +The calculation combines an EMA with a volatility index: -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) - -1. **Fetch Higher Timeframe Data:** The indicator first retrieves the OHLC price data for the user-selected higher timeframe. -2. **Calculate the Chande Momentum Oscillator (CMO):** The CMO is calculated on the higher timeframe's price data over a period `M`. - $\text{CMO}_{htf} = \frac{\text{Sum Up}_{htf} - \text{Sum Down}_{htf}}{\text{Sum Up}_{htf} + \text{Sum Down}_{htf}}$ -3. **Calculate the VIDYA on the Higher Timeframe:** The VIDYA is calculated recursively using the higher timeframe data. - * $\alpha = \frac{2}{N + 1}$ - * $\text{VIDYA}_{htf_i} = (P_{htf_i} \times \alpha \times \text{Abs}(\text{CMO}_{htf_i})) + (\text{VIDYA}_{htf_{i-1}} \times (1 - \alpha \times \text{Abs}(\text{CMO}_{htf_i})))$ -4. **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. +1. **CMO:** Calculated on the higher timeframe to measure momentum/volatility. +2. **Alpha:** The smoothing factor is dynamically adjusted: $\alpha = \frac{2}{N+1} \times |CMO|$. +3. **VIDYA:** The recursive formula is applied to the higher timeframe data. ## 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. +* **Self-Contained:** Uses direct `Copy...` functions; no external dependencies. +* **Modular Engine (`VIDYA_Calculator.mqh`):** Reuses the standard VIDYA logic. -* **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. - -* **Optimized Incremental Calculation:** - Unlike basic MTF indicators that download and recalculate the entire higher-timeframe history on every tick, this indicator employs a sophisticated incremental algorithm. - * **HTF State Tracking:** It tracks the calculation state of the higher timeframe separately (`htf_prev_calculated`). - * **Persistent Buffers:** The internal buffer for the higher timeframe (`BufferVIDYA_HTF_Internal`) is maintained globally, preserving the recursive state of the VIDYA algorithm between ticks. - * **Efficient Mapping:** The projection loop only updates the bars corresponding to the new data, drastically reducing CPU usage. - * This results in **O(1) complexity** per tick, ensuring the indicator remains lightweight even when running on multiple charts simultaneously. - -* **Dual-Mode Logic:** The `OnCalculate` function contains a smart branching logic. - * If a higher timeframe is selected, it performs the optimized 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. +* **Optimized Incremental Calculation (O(1)):** + * **HTF State Tracking:** Tracks `htf_prev_calculated` to process only new bars on the higher timeframe. + * **Persistent State:** The internal VIDYA buffer preserves the recursive value from the previous calculation step. + * **Smart Mapping:** Projects the values to the current chart efficiently, handling the index alignment between timeframes correctly. ## 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. +* **Upper Timeframe (`InpUpperTimeframe`):** The calculation timeframe. +* **CMO Period (`InpPeriodCMO`):** Lookback for volatility measurement (Default: `9`). +* **EMA Period (`InpPeriodEMA`):** Base smoothing period (Default: `12`). +* **Applied Price (`InpSourcePrice`):** Standard or Heikin Ashi. ## 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. +* **Trend Filter:** Price above MTF VIDYA = Bullish bias; Price below = Bearish bias. +* **Flat Line:** A flat MTF VIDYA indicates low volatility and consolidation on the higher timeframe. +* **Support/Resistance:** Due to its adaptive nature, the MTF VIDYA often hugs price action closely during trends, providing accurate dynamic support levels.