Multi-Asset Cross Timeframe Divergence Ind. (MACDI) // AlgoFyre

The Multi-Asset Cross Timeframe Divergence Indicator (MACDI) introduces a unique approach to detecting divergences in momentum across multiple assets and timeframes simulatenously. It goes beyond traditional divergence indicators by calculating divergences not on a single asset or timeframe, but on multiple assets on multiple timeframes. It visually highlights lagging correlated asset momentum divergences, helping traders identify inefficiencies and capitalize on potential opportunities in the secondary asset.

The integration of smoothed aggregated momentum trendlines, real-time visual alerts, and divergence-based labels on price charts provides a clearer and more actionable understanding of market movements.

The MACDI serves as a comprehensive divergence detection tool that tracks momentum shifts across multiple assets and timeframes. It detects change of momentum and direction of the primary (leading) asset while the secondary (following) asset still has not changed it's momentum in it's current trend. The current momentum function used is RSI(). Future iterations of the indicator might add more momentum options such as MACD. Let's get into the details:

🔸Composite Momentum Gradient

The indicator calculates and smooths the momentum trend across multiple assets and timeframes, offering a comprehensive perspective on market momentum direction. In the initial step, the indicator computes the aggregated momentum of the selected assets and timeframes, averaging them to produce a unified measure of market momentum. A generalized formula would be:

𝑆(RSIₐᵗᶠ) = 𝒮(RSIₐᵗᶠ, Length, Method)

This means, the indicator calculates two smoothed momentum values for each asset (HTF and LTF):

1. Leading Assset Highter Timeframe Momentum Value
   
2. Following Assset Highter Timeframe Momentum Value
   
3. Leading Assset Lower Timeframe Momentum Value
   
4. Following Assset Lower Timeframe Momentum Value
   

Each of these values is smoothed based on user-defined settings, allowing for various smoothing techniques such as SMA and customizable lengths.

Subsequently, the composite gradient of both assets’ momentum for each timeframe is calculated, resulting in two series values: one for the higher timeframe (HTF) and one for the lower timeframe (LTF). These series represent the aggregated average momentum trend across both assets.

Pine Script®

🔸Real-time Divergence Indications and Alert Table

After calculating the Composite Momentum Gradient, which serves as the foundation for trend analysis, the next objective is to identify and calculate both bullish and bearish divergences. These divergences are displayed historically and in real time, providing valuable insights for trading decisions and analysis. The divergence lookback period, denoted as "i", represents the number of bars in the past to which the current bar is compared.

Let's look at the four divergences:

1. Bullish Divergence (LTF)
   
   A bullish divergence occurs on the lower timeframe (LTF) when:
   🔸The smoothed RSI of Asset1 on the LTF is greater than its value on the previous i-bars, while
   🔸The smoothed RSI of Asset2 on the LTF is less than its value on the previous i-bar.
   
   Formula:
   𝑆(RSIₐ₁ˡᵗᶠ) > 𝑆(RSIₐ₁ˡᵗᶠ⁽ⁱ⁾) ∧ 𝑆(RSIₐ₂ˡᵗᶠ) < 𝑆(RSIₐ₂ˡᵗᶠ⁽ⁱ⁾)
   
   
2. Bearish Divergence (LTF)
   
   A bearish divergence occurs on the lower timeframe (LTF) when:
   🔸The smoothed RSI of Asset1 on the LTF is less than its value on the previous i-bars, while
   🔸The smoothed RSI of Asset2 on the LTF is greater than its value on the previous i-bars.
   
   Formula:
   𝑆(RSIₐ₁ˡᵗᶠ) < 𝑆(RSIₐ₁ˡᵗᶠ⁽ⁱ⁾) ∧ 𝑆(RSIₐ₂ˡᵗᶠ) > 𝑆(RSIₐ₂ˡᵗᶠ⁽ⁱ⁾)
   
   
3. Bullish Divergence (HTF)
   
   A bullish divergence occurs on the higher timeframe (HTF) when:
   🔸The smoothed RSI of Asset1 on the HTF is greater than its value on the previous i-bars, while
   🔸The smoothed RSI of Asset2 on the HTF is less than its value on the previous i-bars.
   
   Formula:
   𝑆(RSIₐ₁ʰᵗᶠ) > 𝑆(RSIₐ₁ʰᵗᶠ⁽ⁱ⁾) ∧ 𝑆(RSIₐ₂ʰᵗᶠ) < 𝑆(RSIₐ₂ʰᵗᶠ⁽ⁱ⁾)
   
   
4. Bearish Divergence (HTF)
   
   A bearish divergence occurs on the higher timeframe (HTF) when:
   🔸The smoothed RSI of Asset1 on the HTF is less than its value on the previous i-bars, while
   🔸The smoothed RSI of Asset2 on the HTF is greater than its value on the previous i-bars.
   
   Formula:
   RSIₐ₁ʰᵗᶠ < RSIₐ₁ʰᵗᶠ⁽ⁱ⁾ ∧ RSIₐ₂ʰᵗᶠ > RSIₐ₂ʰᵗᶠ⁽ⁱ⁾
   

How to Use the Multi-Asset Cross Timeframe Divergence Indicator (MACDI)

1. Identify Divergence Clusters
   Look for clusters of divergences occurring across both lower and higher timeframes. A higher concentration of divergences suggests an increased probability of a trend reversal, applicable to both bullish and bearish divergences.
   
   
2. Spot Low Probability Divergences
   Assess the Composite Gradient to gauge the likelihood of a reversal. For bullish reversals, a low value or oversold condition is favorable, while a high value or an oversold condition suggests a potential bearish reversal with higher propability.
   
   
3. Customize Your Settings
   
   🔸Leading Asset & Following Asset
   Select the assets for which divergences will be analyzed.
   
   🔸Higher & Lower Timeframes
   Set the preferred timeframes for the analysis.
   
   🔸RSI Settings
   Adjust the RSI divergence visibility, calculation length, source data, smoothing method and divergence offset (i) to suit your strategy.