Sigma Channel [JOAT]JOAT Sigma Channel
Introduction
JOAT Sigma Channel is an open-source regression-based channel overlay built to identify the best-fit directional corridor across a search range of candidate windows.
It is designed to show whether price is traveling normally inside a fitted corridor, stretching away from it, reclaiming it, or moving into stress territory.
The problem it solves is model selection.
A fixed-length regression channel can look excellent in one regime and poor in the next.
If the market accelerates, slows down, or shifts its dominant drift horizon, a static window becomes less useful.
Sigma Channel solves that by searching a range of possible windows and selecting the strongest available fit.
That fit becomes the active corridor.
Around it the script builds multiple sigma tiers.
These tiers create a richer price-state map than a single upper and lower band.
The result is a more useful framework for reading acceptance, stretch, reclaim, and exhaustion.
Core Concepts
1. Multi-Window OLS Search
The script evaluates multiple candidate regression windows and scores them by fit quality.
for len = minWindow to maxWindow by stepWindow
= f_model(len)
2. Sigma-Tier Envelope Stack
The fitted centerline is surrounded by inner, core, outer, and stress layers.
3. Slope and Quality Diagnostics
The chosen model exposes both slope and fit quality.
4. Reclaim and Acceptance States
The script identifies when price reclaims or accepts back inside the corridor after extension.
5. Stress-State Shading
The most extreme statistical layer is visually emphasized.
6. Forward Projection
The active model projects forward to keep the corridor useful at the right edge.
7. Residual Awareness
Residual behavior helps judge whether the active model remains representative.
8. Gradient Candle Context
Bar coloring transitions with the current statistical state.
Features
Adaptive regression search: scans multiple windows instead of using one fixed length
Inner, core, outer, and stress bands: multiple sigma tiers for normal and abnormal travel
Slope-aware corridor logic: distinguishes positive and negative drift
Reclaim and acceptance events: return-to-channel behavior is identified
Stress shading: abnormal statistical extension is highlighted
Forward projection: the active corridor extends to the chart edge
Gradient candle tinting: bar color reflects the current z-state
Dashboard: slope, quality, window, and deviation state are summarized
Input Parameters
Model Search:
Minimum Window
Maximum Window
Window Step
Minimum R-Squared
Projection Bars
Deviation Envelope:
Inner Sigma
Core Sigma
Outer Sigma
Stress Sigma
Filter Stack / Visual System:
Bias EMA
ATR Length
Momentum RSI
Use EMA Bias Gate
Use RSI Gate
Use Volume Gate
Tint Bars
Show Projection
Show Dashboard
How to Use This Indicator
Step 1: Check the active slope and whether the corridor is upward, downward, or balanced.
Step 2: Check fit quality before trusting the active statistical path.
Step 3: Read whether price is inside the core corridor, at the outer layer, or in stress territory.
Step 4: Watch reclaims back into the channel after extension.
Step 5: Use the projection to organize the near-future chart space.
Indicator Limitations
The selected best-fit window can change as the market evolves
Linear regression becomes less representative in strongly nonlinear markets
Statistical extension does not guarantee immediate reversal
The indicator measures deviation from a model, not directional certainty
Originality Statement
This script is original in the way it combines adaptive regression selection, multi-tier sigma structure, reclaim logic, stress-state shading, and forward projection into one corridor framework.
The goal is not just to draw a regression channel.
The goal is to keep the active model responsive while preserving statistical context.
Disclaimer
This indicator is provided for educational and informational purposes only.
It is not financial advice.
Regression fit and statistical deviation do not predict future price with certainty.
Markets can remain extended or break away from the active fit entirely.
Best Use Cases
Reading whether price is behaving normally inside a fitted directional corridor
Identifying statistical stretch and stress states
Watching for reclaim behavior after extension
Combining statistical deviation with separate structure or liquidity analysis
Interpretation Notes
The channel should be trusted more when fit quality is stronger and the slope is clear.
Core travel is generally more normal than outer-band travel.
Stress states are especially useful when they coincide with separate structural or participation warnings.
The projection should be read as a continuation of the current best-fit model, not as a forecast guarantee.
Publication Notes
This script is intended to be published with a clean chart where the corridor, the active slope, and at least one reclaim or extension state are obvious.
The example chart should help the viewer understand how the band hierarchy works.
Avoid combining it with unrelated overlays in the publication image.
-Made with passion by jackofalltrades
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