This strategy calculates normalized price or on-balance volume differentials across a user-defined timeframe and passes them through an activation function such as Swish, Step, or LeakyReLU.
1Copy the scriptPress Copy script above. It reads the file straight from GitHub.
2Open the Pine EditorOpen a TradingView chart and choose Pine Editor at the bottom of the screen.
3Paste over the templateCreate a new strategy, select all of the template text and paste. Press Save and give it a name.
4Add it to the chartPress Add to chart. The trades and results appear in the Strategy Tester tab; adjust the settings with the gear icon.
Source Code
The code stays on GitHub. The author has not published this script under an open licence, so ForexR does not show its code. Copy script reads the file straight from GitHub into your clipboard, so you can still try it on your own chart. Ask the author before reusing the code anywhere else.
Overview
Scaled Normalized Vector Strategy opens long positions when the activated vector crosses above a positive threshold and short positions when it crosses below a negative threshold. It also plots a scaled Karobein Oscillator in a separate pane. The strategy has no stop loss or take profit, and enabling the legacy mode introduces lookahead bias and repainting via historical higher-timeframe data.
Minimax normalization with customizable lookback
Selectable activation functions including Swish, Step, and LeakyReLU
Higher-timeframe vector difference calculation with optional OBV input
Secondary Karobein Oscillator plotted in the indicator pane
The inputs you can change from the gear icon on the chart. Defaults are the author's.
Setting
Type
Default
Variable
Price Data
source
close
price
Timeframe
int
18
tf
Threshold
input
14.
thresh
Divisor
int
1000000
div
Minimax Lookback
int
233
mmx
Volume
bool
false
showVol
Use Old System
bool
true
useold
Activation
string
Swish
method
Karobein Osc Lookback
int
8
per
Third-party code. ForexR did not write, test or endorse this script, and the summary above was generated automatically from its code and README. Indicators describe the past, and a strategy's backtest can look better than live trading, especially when a script repaints. Check it in the Strategy Tester and on a demo account before you rely on it.
Donald - AI Futures 5M 15M Timeframe is an overlay trading strategy designed for intraday futures trading. It utilizes rational quadratic kernel regression to construct dynamic momentum zones and smoothed price boundaries on the main price chart. The strategy
This overlay strategy combines a machine-learning distance model with a MACD oscillator to open trades on the price chart. It compares recent history using cosine similarity or Euclidean and Lorentzian distance, then filters direction with selectable moving-av
Donald - AI Futures is a price-chart strategy that estimates inner and outer high-low zones and a smoothed close with rational quadratic kernel regression. It builds bullish and bearish momentum signals, optionally compares volume with a volume-weighted moving
Calculates MACD line and signal line differences, passing current and previous deltas through a two-layer neural network model with ReLU activation functions. User-configurable weights, biases, and threshold values determine output classification signals. The
MACD + Divergences [Alorse] is a momentum strategy that calculates the MACD oscillator and identifies regular and hidden divergences using pivot high and low points. It filters trade signals with dual Exponential Moving Averages (EMA 150 and 600) to ensure tra
This strategy combines the ATR-banded Q-Trend indicator with the Klinger Volume Oscillator (KVO) to execute confluence trades. It enters long when a Q-Trend buy trigger aligns with a positive KVO value and a bullish candle confirmation, taking short trades und