GLI [BBS + M2] Fair Value Analysis - Regression

17 Jun

GLI [BBS + M2] Fair Value Analysis – Regression Forecast
This indicator provides a regression-based fair value model that forecasts asset prices using a custom-built Global Liquidity Index (GLI) derived from central bank balance sheets (BBS) and M2 money supply across major economies.

🔍 Core Concept
The indicator performs a linear regression between:

• Today's GLI (independent variable)
  
• Asset price "n" days later (dependent variable)
  
• This leads to a forecasted fair value, along with ±1, ±2, and ±3 standard deviation bands to visualize potential overbought/oversold conditions or market dislocations.
  

🧮 GLI Composition
GLI is computed from:

• 🇺🇸 US, 🇯🇵 Japan, 🇨🇳 China, 🇪🇺 Eurozone, 🇬🇧 UK central bank balance sheets
  
• M2 Money Supply from the same regions
  
• Reverse repo (RRP) and the US Treasury General Account (WT)
  

⚙️ Customizable Inputs

• Lead (Days Offset): Defines how far forward the regression predicts asset prices
  
• Lookback: Determines the number of historical data points used in the regression calculation
  
• Optional Settings : Lead = 7, Lookback = 47
  

📈 Output

• Fair Value Line (Forecast)
  
• ±1 to ±3 Standard Deviation Bands
  
• Visual fill zones for clearer market deviation context
  

📌 How to Use

• Use the forecasted value as a fair value anchor to assess over/undervaluation.
  
• SD bands serve as a probabilistic range
  
• Especially useful in macro-driven markets and mid-long term strategic positioning.
  

⚠️ Note
This model is tailored for macro-aware traders and investors. Interpret with market context in mind, as liquidity signals are leading but not always precise in timing.

17 Jun

Catatan Rilis

GLI [BBS + M2] Fair Value Analysis – Regression Forecast
This indicator provides a regression-based fair value model that forecasts asset prices using a custom-built Global Liquidity Index (GLI) derived from central bank balance sheets (BBS) and M2 money supply across major economies.

🔍 Core Concept
The indicator performs a linear regression between:

• Today's GLI (independent variable)
  
• Asset price "n" days later (dependent variable)
  
• This leads to a forecasted fair value, along with ±1, ±2, and ±3 standard deviation bands to visualize potential overbought/oversold conditions or market dislocations.
  

🧮 GLI Composition
GLI is computed from:

• 🇺🇸 US, 🇯🇵 Japan, 🇨🇳 China, 🇪🇺 Eurozone, 🇬🇧 UK central bank balance sheets
  
• M2 Money Supply from the same regions
  
• Reverse repo (RRP) and the US Treasury General Account (WT)
  

⚙️ Customizable Inputs

• Lead (Days Offset): Defines how far forward the regression predicts asset prices
  
• Lookback: Determines the number of historical data points used in the regression calculation
  

📈 Output

• Fair Value Line (Forecast)
  
• ±1 to ±3 Standard Deviation Bands
  
• Visual fill zones for clearer market deviation context
  

📌 How to Use

• Use the forecasted value as a fair value anchor to assess over/undervaluation.
  
• SD bands serve as a probabilistic range
  
• Especially useful in macro-driven markets and mid-long term strategic positioning.
  

⚠️ Note
This model is tailored for macro-aware traders and investors. Interpret with market context in mind, as liquidity signals are leading but not always precise in timing.

17 Jun

Catatan Rilis

Deleted

17 Jun

Catatan Rilis

Updated back again
Mess up with the notes cause this is my first published indicator

25 Jul

Catatan Rilis

Updated the visual and the display panel

25 Jul

Catatan Rilis

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