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Indicator · Pine Script v6 · On the chart
Kalman Filter (KALMAN)
This indicator applies a one-dimensional Kalman filter to a chosen price source and plots the filtered series on the price chart.
GitHub stars99on the repository
Pine versionv6current
Lines of code40
Settings3inputs
LicenceApache-2.0
Last update4 weeks ago27 Sep 2026
Add It to Your TradingView Chart
- 1Copy the scriptPress Copy script above, or the copy button on the code below.
- 2Open the Pine EditorOpen a TradingView chart and choose Pine Editor at the bottom of the screen.
- 3Paste over the templateCreate a new indicator, select all of the template text and paste. Press Save and give it a name.
- 4Add it to the chartPress Add to chart, then adjust the settings with the gear icon next to its name.
Source Code
40 lines of Pine Script v6 from lib/filters/kalman/kalman.pine, published under Apache-2.0. Keep the author's credit and licence lines when you reuse it.
// Licensed under the Apache License, Version 2.0
// © mihakralj
//@version=6
indicator("Kalman Filter (KALMAN)", "KALMAN", overlay=true)
//@function Applies a Kalman Filter to the input series
//@param src Input series (measurement)
//@param q Process noise covariance
//@param r Measurement noise covariance
//@returns Filtered series
//@optimized Uses Kalman filter with O(1) complexity per bar
kalman(series float src, simple float q, simple float r) =>
if q <= 0.0 or r <= 0.0
runtime.error("Process noise covariance (q) and measurement noise covariance (r) must be positive")
var float x = na
var float p = na
float measurement = nz(src, 0.0)
if bar_index == 0 or na(x)
x := measurement
p := 1.0
float x_pred = x
float p_pred = p + q
float denom = p_pred + r
float k_gain = denom == 0.0 ? 0.0 : p_pred / denom
x := x_pred + k_gain * (measurement - x_pred)
p := (1.0 - k_gain) * p_pred
x
// ---------- Main loop ----------
// Inputs
i_source = input.source(close, "Source")
i_q = input.float(0.01, "Process Noise (Q)", minval=1e-9, step=0.01)
i_r = input.float(0.1, "Measurement Noise (R)", minval=1e-9, step=0.1)
// Calculation
kf_val = kalman(i_source, i_q, i_r)
// Plot
plot(kf_val, "KF", color=color.yellow, linewidth=2)
Overview
Process noise and measurement noise set how quickly the estimate follows new data versus how much it trusts the measurement. The function keeps a running state estimate and error covariance and updates both on every bar in constant time. It draws a single yellow line and does not generate trade signals or exits.
- Kalman filter of a price source
- Process noise and measurement noise inputs
- Constant-time state update each bar
- Yellow overlay of the filtered series
- Positive noise validation
Details
Published by
mihakralj on GitHub
Type
Indicator, Pine Script v6
Draws
On the price chart
Category
Trend
Markets
Any symbol
Timeframes
Any timeframe
Risk Notes
No repainting, lookahead or stacked entries were found in its code or README. That says nothing about how well it works: test it first.
Topics
algorithmic-tradingcsharpdotnetpinescriptpythonquantitative-financesimdta-libtechnical-analysistechnical-indicators
Settings
The inputs you can change from the gear icon on the chart. Defaults are the author's.
| Setting | Type | Default | Variable |
|---|---|---|---|
| Source | source | close | i_source |
| Process Noise (Q) | float | 0.01 | i_q |
| Measurement Noise (R) | float | 0.1 | i_r |
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.
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