OPEN-SOURCE SCRIPT
Fair Value Strategy Ultimate

This is a strategy using an index's (SPX, NDX, RUT) Fair Value derived from Net Liquidity.
Net Liquidity function is simply: Fed Balance Sheet - Treasury General Account - Reverse Repo Balance
Formula for calculating the fair value of and Index using Net Liquidity looks like this: net_liquidity/1000000000/scalar - subtractor
The Index Fair Value is then subtracted from the Index value which creates an oscillating diff value.
When diff is greater than the overbought threshold, Index is considered overbought and we go short/sell.
When diff is less than the oversold signal, Index is considered oversold and we cover/buy.
The net liquidity values I calculate outside of TradingView. If you'd like the strategy to work for future dates, you'll need to update the reference to my NetLiquidityLibrary, which I update daily.
Parameters:
Index: SPX, NDX, RUT
Strategy: Short Only, Long Only, Long/Short
Inverse (bool): check if using an inverse ETF to go long instead of short.
Scalar (float)
Subtractor (int)
Overbought Threshold (int)
Oversold Threshold (int)
Start After Date: When the strategy should start trading
Close Date: Day to close open trades. I just like it to get complete results rather than the strategy ending with open trades.
Optimal Parameters:
I've optimized the parameters for each index using the python backtesting library and they are as follows =>
SPX
Scalar: 1.1
Subtractor: 1425
OB Threshold: 0
OS Threshold: -175
NDX
Scalar: 0.5
Subtractor: 250
OB Threshold: 0
OS Threshold: -25
RUT
Scalar: 3.2
Subtractor: 50
OB Threshold: 25
OS Threshold: -25
Net Liquidity function is simply: Fed Balance Sheet - Treasury General Account - Reverse Repo Balance
Formula for calculating the fair value of and Index using Net Liquidity looks like this: net_liquidity/1000000000/scalar - subtractor
The Index Fair Value is then subtracted from the Index value which creates an oscillating diff value.
When diff is greater than the overbought threshold, Index is considered overbought and we go short/sell.
When diff is less than the oversold signal, Index is considered oversold and we cover/buy.
The net liquidity values I calculate outside of TradingView. If you'd like the strategy to work for future dates, you'll need to update the reference to my NetLiquidityLibrary, which I update daily.
Parameters:
Index: SPX, NDX, RUT
Strategy: Short Only, Long Only, Long/Short
Inverse (bool): check if using an inverse ETF to go long instead of short.
Scalar (float)
Subtractor (int)
Overbought Threshold (int)
Oversold Threshold (int)
Start After Date: When the strategy should start trading
Close Date: Day to close open trades. I just like it to get complete results rather than the strategy ending with open trades.
Optimal Parameters:
I've optimized the parameters for each index using the python backtesting library and they are as follows =>
SPX
Scalar: 1.1
Subtractor: 1425
OB Threshold: 0
OS Threshold: -175
NDX
Scalar: 0.5
Subtractor: 250
OB Threshold: 0
OS Threshold: -25
RUT
Scalar: 3.2
Subtractor: 50
OB Threshold: 25
OS Threshold: -25
開源腳本
秉持TradingView一貫精神,這個腳本的創作者將其設為開源,以便交易者檢視並驗證其功能。向作者致敬!您可以免費使用此腳本,但請注意,重新發佈代碼需遵守我們的社群規範。
免責聲明
這些資訊和出版物並非旨在提供,也不構成TradingView提供或認可的任何形式的財務、投資、交易或其他類型的建議或推薦。請閱讀使用條款以了解更多資訊。
開源腳本
秉持TradingView一貫精神,這個腳本的創作者將其設為開源,以便交易者檢視並驗證其功能。向作者致敬!您可以免費使用此腳本,但請注意,重新發佈代碼需遵守我們的社群規範。
免責聲明
這些資訊和出版物並非旨在提供,也不構成TradingView提供或認可的任何形式的財務、投資、交易或其他類型的建議或推薦。請閱讀使用條款以了解更多資訊。