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Miha Kralj
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# ABBER: Aberration Bands
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | Source (close) |
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| **Parameters** | `period`, `multiplier` (default 2.0) |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | `period` bars |
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### TL;DR
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- ABBER measures price deviation from a central moving average using mean absolute deviation rather than standard deviation, producing dynamic bands ...
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- Parameterized by `period`, `multiplier` (default 2.0).
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- Output range: Tracks input.
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- Requires `period` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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ABBER measures price deviation from a central moving average using mean absolute deviation rather than standard deviation, producing dynamic bands that adapt to volatility while remaining robust against extreme outliers. Where Bollinger Bands amplify outliers through squaring (the $L^2$ norm), ABBER uses raw absolute differences (the $L^1$ norm), so bands respond to typical price behavior rather than the occasional spike that yanks everything sideways. For a 20-period window with a 2.0 multiplier, ABBER contains approximately 89% of normally-distributed price action, but its real advantage emerges with fat-tailed distributions where standard deviation overreacts to single-bar anomalies.
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## Historical Context
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# ACCBANDS: Acceleration Bands
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | OHLCV bar (TBar) |
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| **Parameters** | `period`, `factor` (default 4.0) |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | `period` bars |
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### TL;DR
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- Acceleration Bands construct a volatility envelope using the intra-bar high-low range rather than close-to-close standard deviation, creating chann...
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- Parameterized by `period`, `factor` (default 4.0).
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- Output range: Tracks input.
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- Requires `period` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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Acceleration Bands construct a volatility envelope using the intra-bar high-low range rather than close-to-close standard deviation, creating channels that accommodate the full price excursion of the underlying asset. Each bar's contribution to band width is normalized by price level ($w = (H-L)/(H+L)$), making the bands scale-invariant across instruments. Three independent Simple Moving Averages of the adjusted high, adjusted low, and close prices form the upper, lower, and middle bands respectively. Headley's original breakout rule declares a trend when price closes outside the bands for two consecutive bars.
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## Historical Context
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# APCHANNEL: Adaptive Price Channel
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | OHLCV bar (TBar) |
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| **Parameters** | None |
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| **Outputs** | Single series (Apchannel) |
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| **Output range** | Tracks input |
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| **Warmup** | 1 bar |
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### TL;DR
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- APCHANNEL applies exponential smoothing independently to price highs and lows, creating a dynamic envelope that "remembers" significant extremes wh...
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- No configurable parameters; computation is stateless per bar.
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- Output range: Tracks input.
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- Requires 1 bar of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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APCHANNEL applies exponential smoothing independently to price highs and lows, creating a dynamic envelope that "remembers" significant extremes while gradually fading their influence over time. Unlike rigid Donchian channels that drop price extremes abruptly when they exit the lookback window (the "cliff effect"), APCHANNEL decays them smoothly through leaky integration. The result is a channel with continuously sloping boundaries that responds to volatility without the discontinuous jumps that plague fixed-window approaches. The algorithm is $O(1)$ per bar with only two state variables and no buffers.
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## Historical Context
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# APZ: Adaptive Price Zone
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | OHLCV bar (TBar) |
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| **Parameters** | `period`, `multiplier` (default 2.0) |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | `period` bars |
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### TL;DR
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- APZ constructs a volatility-adaptive envelope using double-smoothed exponential moving averages with an aggressive smoothing factor derived from $\...
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- Parameterized by `period`, `multiplier` (default 2.0).
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- Output range: Tracks input.
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- Requires `period` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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APZ constructs a volatility-adaptive envelope using double-smoothed exponential moving averages with an aggressive smoothing factor derived from $\sqrt{\text{period}}$, making it significantly faster than standard EMA-based channels. The center line is a double-EMA of price; the band width is a double-EMA of the high-low range, scaled by a multiplier. Designed specifically for mean-reversion trading in non-trending markets, APZ identifies overbought/oversold extremes where price is likely to reverse rather than continue. A closing price outside the zone signals an immediate overshoot, not a breakout.
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## Historical Context
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# ATRBANDS: Average True Range Bands
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | OHLCV bar (TBar) |
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| **Parameters** | `period`, `multiplier` (default 2.0) |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | `period` bars |
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### TL;DR
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- ATR Bands create a volatility-adaptive envelope by projecting Wilder's Average True Range above and below a central Simple Moving Average.
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- Parameterized by `period`, `multiplier` (default 2.0).
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- Output range: Tracks input.
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- Requires `period` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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ATR Bands create a volatility-adaptive envelope by projecting Wilder's Average True Range above and below a central Simple Moving Average. Unlike fixed-percentage envelopes or standard-deviation bands, ATR Bands use True Range to measure volatility, making them robust for assets with gaps, pre-market moves, and 24/7 trading where the "hidden" volatility between bars is significant. The True Range captures the maximum of intra-bar range, gap-up distance, and gap-down distance, ensuring that overnight gaps contribute fully to band width even when the current bar's open-to-close range is narrow.
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## Historical Context
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# BBANDS: Bollinger Bands
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | Source (close) |
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| **Parameters** | `period` (default DefaultPeriod), `multiplier` (default DefaultMultiplier) |
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| **Outputs** | Multiple series (Middle, Upper, Lower, Width, PercentB) |
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| **Output range** | Tracks input |
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| **Warmup** | `period` bars |
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### TL;DR
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- Bollinger Bands construct a volatility-adaptive envelope around a Simple Moving Average using population standard deviation as the width measure.
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- Parameterized by `period` (default defaultperiod), `multiplier` (default defaultmultiplier).
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- Output range: Tracks input.
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- Requires `period` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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Bollinger Bands construct a volatility-adaptive envelope around a Simple Moving Average using population standard deviation as the width measure. The bands expand during high-volatility periods and contract during consolidation, dynamically adapting to changing market conditions. Under Gaussian assumptions, $\pm 2\sigma$ contains approximately 95.4% of price action, but financial returns exhibit fat tails and volatility clustering, so the bands function more as a volatility-normalized reference frame than a strict probability envelope. The derived metrics %B (price position as a fraction of band width) and BandWidth (normalized band spread) extend the raw bands into a complete analytical toolkit.
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## Historical Context
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# DCHANNEL: Donchian Channels
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | OHLCV bar (TBar) |
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| **Parameters** | `period` |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | `period` bars |
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### TL;DR
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- Donchian Channels track the highest high and lowest low over a fixed lookback period, defining the absolute price boundaries within which an asset ...
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- Parameterized by `period`.
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- Output range: Tracks input.
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- Requires `period` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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Donchian Channels track the highest high and lowest low over a fixed lookback period, defining the absolute price boundaries within which an asset has traded. Unlike volatility-based bands that compute statistical dispersion, Donchian Channels represent actual historical extremes — the literal "price box." The implementation uses monotonic deques for $O(1)$ amortized sliding-window max/min, ensuring that computing a 500-period channel costs no more than a 20-period one. The midpoint of the upper and lower bands serves as a simple trend bias indicator.
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## Historical Context
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# DECAYCHANNEL: Decay Min-Max Channel
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | OHLCV bar (TBar) |
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| **Parameters** | `period` |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | `period` bars |
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### TL;DR
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- Decay Channel combines the absolute price boundaries of Donchian Channels with exponential decay toward the midpoint, creating an envelope that exp...
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- Parameterized by `period`.
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- Output range: Tracks input.
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- Requires `period` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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Decay Channel combines the absolute price boundaries of Donchian Channels with exponential decay toward the midpoint, creating an envelope that expands instantly on new volatility but contracts smoothly during consolidation. While Donchian Channels hold their width until an extreme exits the lookback window, Decay Channel allows the bands to "forget" old extremes over time using a half-life model. The period parameter serves as the half-life: after that many bars without a new extreme, the band has decayed 50% of the distance back toward center. The decayed values are always clamped within Donchian bounds, ensuring they never extrapolate beyond actual price history.
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## Historical Context
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# FCB: Fractal Chaos Bands
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | OHLCV bar (TBar) |
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| **Parameters** | `period` (default 20) |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | `period + 2` bars |
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### TL;DR
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- Fractal Chaos Bands filter raw price action through Bill Williams' fractal detection logic, tracking the highest confirmed fractal high and lowest ...
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- Parameterized by `period` (default 20).
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- Output range: Tracks input.
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- Requires `period + 2` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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Fractal Chaos Bands filter raw price action through Bill Williams' fractal detection logic, tracking the highest confirmed fractal high and lowest confirmed fractal low over a lookback period. Unlike Donchian Channels which use every bar's high and low, FCB uses only structurally significant turning points — bars where the middle element of a 3-bar pattern is a local extremum. The result is a "cleaner" channel that ignores transient spikes and focuses on confirmed support and resistance levels. The bands tend to remain flat during trends and step discretely when new structural pivots form, making them useful for identifying genuine breakouts versus noise.
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## Historical Context
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# JBANDS: Jurik Adaptive Envelope Bands
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | Source (close) |
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| **Parameters** | `period`, `phase` (default 0) |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | 1 bar |
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### TL;DR
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- JBANDS expose the internal adaptive envelope mechanism of the Jurik Moving Average (JMA), producing asymmetric bands that snap instantly to new pri...
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- Parameterized by `period`, `phase` (default 0).
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- Output range: Tracks input.
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- Requires 1 bar of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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JBANDS expose the internal adaptive envelope mechanism of the Jurik Moving Average (JMA), producing asymmetric bands that snap instantly to new price extremes and decay exponentially during consolidation. Unlike standard volatility bands (Bollinger, Keltner) which maintain symmetric width around a center line, JBANDS feature "snap-and-decay" hysteresis: expansion is instantaneous (plasticity), contraction is gradual (elasticity). The decay rate is dynamically modulated by a two-stage volatility estimator — a 10-bar SMA feeding a 128-bar trimmed mean — making the bands tight during quiet markets and expansive during trends. The center line is the full JMA: a 2-pole IIR filter with phase control and adaptive alpha.
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## Historical Context
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# KCHANNEL: Keltner Channel
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | OHLCV bar (TBar) |
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| **Parameters** | `period` (default 20), `multiplier` (default 2.0) |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | `period * 2` bars |
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### TL;DR
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- Keltner Channel constructs a volatility-adaptive envelope by projecting Average True Range above and below an Exponential Moving Average center line.
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- Parameterized by `period` (default 20), `multiplier` (default 2.0).
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- Output range: Tracks input.
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- Requires `period * 2` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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Keltner Channel constructs a volatility-adaptive envelope by projecting Average True Range above and below an Exponential Moving Average center line. The channel differs from ATR Bands solely in the center line: Keltner uses EMA (faster, more responsive) while ATR Bands use SMA (more stable, more lag). The EMA center combined with ATR width creates a channel that both tracks trend and adapts to volatility, making it one of the most widely used channel indicators for trend-following and mean-reversion strategies. The implementation uses EMA with warmup compensation for accurate early values and Wilder's smoothing (RMA) for ATR.
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## Historical Context
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# MAENV: Moving Average Envelope
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | Source (close) |
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| **Parameters** | `period` (default 20), `percentage` (default 1.0), `maType` (default MaenvType.EMA) |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | `period` bars |
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### TL;DR
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- Moving Average Envelope (MA Envelope) constructs symmetric bands at a fixed percentage distance above and below a moving average center line.
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- Parameterized by `period` (default 20), `percentage` (default 1.0), `matype` (default maenvtype.ema).
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- Output range: Tracks input.
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- Requires `period` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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Moving Average Envelope (MA Envelope) constructs symmetric bands at a fixed percentage distance above and below a moving average center line. Unlike volatility-adaptive channels (Bollinger, Keltner, ATR Bands) where band width varies with market conditions, MA Envelope uses a constant percentage offset, creating bands whose absolute width scales only with price level. The indicator supports configurable moving average types (SMA, EMA, WMA) for the center line, allowing users to trade off between lag, smoothness, and responsiveness.
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## Historical Context
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# MMCHANNEL: Min-Max Channel
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | OHLCV bar (TBar) |
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| **Parameters** | `period` |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | `period` bars |
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### TL;DR
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- Min-Max Channel tracks the highest high and lowest low over a lookback period, creating a pure price envelope without any midpoint calculation.
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- Parameterized by `period`.
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- Output range: Tracks input.
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- Requires `period` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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Min-Max Channel tracks the highest high and lowest low over a lookback period, creating a pure price envelope without any midpoint calculation. Unlike Donchian Channels which include a middle band, MMCHANNEL delivers only the raw extremes. The implementation uses monotonic deques for O(1) amortized updates: each element enters the deque once and leaves at most once, so total work over $N$ bars is $O(N)$ regardless of period length.
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## Historical Context
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@@ -1,5 +1,22 @@
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# PCHANNEL: Price Channel
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | OHLCV bar (TBar) |
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| **Parameters** | `period` |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | `period` bars |
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### TL;DR
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- Price Channel tracks the highest high and lowest low over a lookback period with a midpoint average, creating a three-line price envelope that defi...
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- Parameterized by `period`.
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- Output range: Tracks input.
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- Requires `period` bars of warmup before first valid output (IsHot = true).
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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Price Channel tracks the highest high and lowest low over a lookback period with a midpoint average, creating a three-line price envelope that defines where the market has been. Functionally identical to Donchian Channels, the indicator uses actual price extremes rather than volatility estimates, producing bands that represent real support and resistance levels. This implementation uses monotonic deques for O(1) amortized updates instead of the naive O(n) rescan that most platforms use internally.
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## Historical Context
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@@ -1,5 +1,22 @@
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# REGCHANNEL: Linear Regression Channel
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| Property | Value |
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| ---------------- | -------------------------------- |
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| **Category** | Channel |
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| **Inputs** | Source (close) |
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| **Parameters** | `period` (default 20), `multiplier` (default 2.0) |
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| **Outputs** | Multiple series (Upper, Lower) |
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| **Output range** | Tracks input |
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| **Warmup** | `period` bars |
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### TL;DR
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- Linear Regression Channel plots a best-fit line through price data over a specified period with parallel bands at a configurable standard deviation...
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- Parameterized by `period` (default 20), `multiplier` (default 2.0).
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- Output range: Tracks input.
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||||
- Requires `period` bars of warmup before first valid output (IsHot = true).
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||||
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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||||
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Linear Regression Channel plots a best-fit line through price data over a specified period with parallel bands at a configurable standard deviation of residuals. Unlike moving average envelopes that offset from a smoothed price, regression channels adapt their slope to the underlying trend and their width to actual dispersion around that trend. The algorithm uses ordinary least squares with precomputed index sums, requiring two passes per bar: one for the regression coefficients and one for the residual standard deviation.
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## Historical Context
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@@ -1,5 +1,22 @@
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# SDCHANNEL: Standard Deviation Channel
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| Property | Value |
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||||
| ---------------- | -------------------------------- |
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||||
| **Category** | Channel |
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||||
| **Inputs** | Source (close) |
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||||
| **Parameters** | `period` (default 20), `multiplier` (default 2.0) |
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||||
| **Outputs** | Multiple series (Upper, Lower) |
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||||
| **Output range** | Tracks input |
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||||
| **Warmup** | `period` bars |
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||||
|
||||
### TL;DR
|
||||
|
||||
- Standard Deviation Channel plots a linear regression line through price data with parallel bands at a specified number of standard deviations of re...
|
||||
- Parameterized by `period` (default 20), `multiplier` (default 2.0).
|
||||
- Output range: Tracks input.
|
||||
- Requires `period` bars of warmup before first valid output (IsHot = true).
|
||||
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
|
||||
|
||||
Standard Deviation Channel plots a linear regression line through price data with parallel bands at a specified number of standard deviations of residuals above and below. Unlike Bollinger Bands which measure deviation from a moving average, SDCHANNEL measures deviation from the best-fit trend line, capturing how much price wanders from its underlying trajectory rather than from its simple average. The algorithm is identical to REGCHANNEL; the distinction is purely a naming convention found across different platforms and literature.
|
||||
|
||||
## Historical Context
|
||||
|
||||
@@ -1,5 +1,22 @@
|
||||
# STARCHANNEL: Stoller Average Range Channel
|
||||
|
||||
| Property | Value |
|
||||
| ---------------- | -------------------------------- |
|
||||
| **Category** | Channel |
|
||||
| **Inputs** | OHLCV bar (TBar) |
|
||||
| **Parameters** | `period` (default 20), `multiplier` (default 2.0), `atrPeriod` (default 0) |
|
||||
| **Outputs** | Multiple series (Upper, Lower) |
|
||||
| **Output range** | Tracks input |
|
||||
| **Warmup** | `Math.Max(period, effectiveAtrPeriod)` bars |
|
||||
|
||||
### TL;DR
|
||||
|
||||
- Stoller Average Range Channel creates a volatility-adaptive price envelope using Average True Range (ATR) to determine band width around a simple m...
|
||||
- Parameterized by `period` (default 20), `multiplier` (default 2.0), `atrperiod` (default 0).
|
||||
- Output range: Tracks input.
|
||||
- Requires `Math.Max(period, effectiveAtrPeriod)` bars of warmup before first valid output (IsHot = true).
|
||||
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
|
||||
|
||||
Stoller Average Range Channel creates a volatility-adaptive price envelope using Average True Range (ATR) to determine band width around a simple moving average centerline. The bands automatically expand during volatile periods and contract during calmer markets. The implementation uses a circular buffer for the SMA running sum and Wilder's RMA with a warmup compensator for ATR, achieving O(1) streaming updates per bar.
|
||||
|
||||
## Historical Context
|
||||
|
||||
@@ -1,5 +1,22 @@
|
||||
# STBANDS: Super Trend Bands
|
||||
|
||||
| Property | Value |
|
||||
| ---------------- | -------------------------------- |
|
||||
| **Category** | Channel |
|
||||
| **Inputs** | OHLCV bar (TBar) |
|
||||
| **Parameters** | `period` (default DefaultPeriod), `multiplier` (default DefaultMultiplier) |
|
||||
| **Outputs** | Multiple series (Upper, Lower, Trend, Width) |
|
||||
| **Output range** | Tracks input |
|
||||
| **Warmup** | `period` bars |
|
||||
|
||||
### TL;DR
|
||||
|
||||
- Super Trend Bands provide ATR-based dynamic support and resistance levels with asymmetric ratchet logic: the upper band only tightens downward duri...
|
||||
- Parameterized by `period` (default defaultperiod), `multiplier` (default defaultmultiplier).
|
||||
- Output range: Tracks input.
|
||||
- Requires `period` bars of warmup before first valid output (IsHot = true).
|
||||
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
|
||||
|
||||
Super Trend Bands provide ATR-based dynamic support and resistance levels with asymmetric ratchet logic: the upper band only tightens downward during downtrends, and the lower band only tightens upward during uptrends. This creates natural trailing stop-loss levels that respect market momentum. A trend direction signal ($+1$ or $-1$) flips when price breaches the opposite band. The ATR is computed as a simple moving average of True Range via a ring buffer with running sum, providing O(1) streaming updates.
|
||||
|
||||
## Historical Context
|
||||
|
||||
@@ -1,5 +1,22 @@
|
||||
# TTM_LRC: TTM Linear Regression Channel
|
||||
|
||||
| Property | Value |
|
||||
| ---------------- | -------------------------------- |
|
||||
| **Category** | Channel |
|
||||
| **Inputs** | Source (close) |
|
||||
| **Parameters** | `period` (default 100) |
|
||||
| **Outputs** | Multiple series (Midline, Upper1, Lower1, Upper2, Lower2) |
|
||||
| **Output range** | Tracks input |
|
||||
| **Warmup** | `period` bars |
|
||||
|
||||
### TL;DR
|
||||
|
||||
- TTM Linear Regression Channel plots a least-squares regression line through price data with dual standard deviation bands at $\pm 1\sigma$ and $\pm...
|
||||
- Parameterized by `period` (default 100).
|
||||
- Output range: Tracks input.
|
||||
- Requires `period` bars of warmup before first valid output (IsHot = true).
|
||||
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
|
||||
|
||||
TTM Linear Regression Channel plots a least-squares regression line through price data with dual standard deviation bands at $\pm 1\sigma$ and $\pm 2\sigma$. Developed by John Carter as part of his TTM (Trade The Markets) indicator suite, it extends the standard regression channel by providing two band levels that create statistically meaningful trading zones. The algorithm is identical to REGCHANNEL/SDCHANNEL in its regression and residual computation, but uses a longer default period (100) and emits four bands instead of two.
|
||||
|
||||
## Historical Context
|
||||
|
||||
@@ -1,5 +1,22 @@
|
||||
# UBANDS: Ehlers Ultimate Bands
|
||||
|
||||
| Property | Value |
|
||||
| ---------------- | -------------------------------- |
|
||||
| **Category** | Channel |
|
||||
| **Inputs** | Source (close) |
|
||||
| **Parameters** | `period` (default DefaultPeriod), `multiplier` (default DefaultMultiplier) |
|
||||
| **Outputs** | Multiple series (Upper, Middle, Lower, Width) |
|
||||
| **Output range** | Tracks input |
|
||||
| **Warmup** | `period` bars |
|
||||
|
||||
### TL;DR
|
||||
|
||||
- Ehlers Ultimate Bands replace the conventional SMA foundation of Bollinger Bands with the Ultrasmooth Filter (USF), a 2-pole IIR filter with zero o...
|
||||
- Parameterized by `period` (default defaultperiod), `multiplier` (default defaultmultiplier).
|
||||
- Output range: Tracks input.
|
||||
- Requires `period` bars of warmup before first valid output (IsHot = true).
|
||||
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
|
||||
|
||||
Ehlers Ultimate Bands replace the conventional SMA foundation of Bollinger Bands with the Ultrasmooth Filter (USF), a 2-pole IIR filter with zero overshoot and minimal lag. Band width is determined by the RMS (Root Mean Square) of residuals between price and the smoothed centerline, providing a mathematically rigorous deviation measure that makes no assumptions about the distribution of returns. The USF is a recursive filter requiring O(1) computation per bar, while the RMS calculation scans the lookback window at O(n) per bar.
|
||||
|
||||
## Historical Context
|
||||
|
||||
@@ -1,5 +1,22 @@
|
||||
# UCHANNEL: Ehlers Ultimate Channel
|
||||
|
||||
| Property | Value |
|
||||
| ---------------- | -------------------------------- |
|
||||
| **Category** | Channel |
|
||||
| **Inputs** | OHLCV bar (TBar) |
|
||||
| **Parameters** | `strPeriod` (default DefaultStrPeriod), `centerPeriod` (default DefaultCenterPeriod), `multiplier` (default DefaultMultiplier) |
|
||||
| **Outputs** | Multiple series (Upper, Middle, Lower, STR) |
|
||||
| **Output range** | Tracks input |
|
||||
| **Warmup** | 1 bar |
|
||||
|
||||
### TL;DR
|
||||
|
||||
- Ehlers Ultimate Channel applies the Ultrasmooth Filter (USF) twice: once to the close price for the centerline and once to True Range for band widt...
|
||||
- Parameterized by `strperiod` (default defaultstrperiod), `centerperiod` (default defaultcenterperiod), `multiplier` (default defaultmultiplier).
|
||||
- Output range: Tracks input.
|
||||
- Requires 1 bar of warmup before first valid output (IsHot = true).
|
||||
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
|
||||
|
||||
Ehlers Ultimate Channel applies the Ultrasmooth Filter (USF) twice: once to the close price for the centerline and once to True Range for band width, creating a channel where both the trend estimate and the volatility measure share the same low-lag, zero-overshoot filter characteristics. Unlike UBANDS which uses RMS of price residuals, UCHANNEL uses Smoothed True Range (STR) for band width, making it responsive to gap-inclusive volatility. Separate period parameters allow independent tuning of centerline smoothness and band-width responsiveness.
|
||||
|
||||
## Historical Context
|
||||
|
||||
@@ -1,5 +1,22 @@
|
||||
# VWAPBANDS: VWAP with Dual Standard Deviation Bands
|
||||
|
||||
| Property | Value |
|
||||
| ---------------- | -------------------------------- |
|
||||
| **Category** | Channel |
|
||||
| **Inputs** | OHLCV bar (TBar) |
|
||||
| **Parameters** | `multiplier` (default DefaultMultiplier) |
|
||||
| **Outputs** | Multiple series (Upper1, Lower1, Upper2, Lower2, Vwap, StdDev, Width) |
|
||||
| **Output range** | Tracks input |
|
||||
| **Warmup** | `2` bars |
|
||||
|
||||
### TL;DR
|
||||
|
||||
- VWAP Bands extend the Volume Weighted Average Price with dual standard deviation bands at $\pm 1\sigma$ and $\pm 2\sigma$ levels, creating a five-l...
|
||||
- Parameterized by `multiplier` (default defaultmultiplier).
|
||||
- Output range: Tracks input.
|
||||
- Requires `2` bars of warmup before first valid output (IsHot = true).
|
||||
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
|
||||
|
||||
VWAP Bands extend the Volume Weighted Average Price with dual standard deviation bands at $\pm 1\sigma$ and $\pm 2\sigma$ levels, creating a five-line channel system anchored to volume-weighted fair value. Three running sums (cumulative price×volume, cumulative volume, cumulative price²×volume) enable O(1) streaming updates per bar. A session reset mechanism clears accumulations at configurable intervals, keeping the indicator anchored to current market structure.
|
||||
|
||||
## Historical Context
|
||||
|
||||
@@ -1,5 +1,22 @@
|
||||
# VWAPSD: VWAP with Standard Deviation Bands
|
||||
|
||||
| Property | Value |
|
||||
| ---------------- | -------------------------------- |
|
||||
| **Category** | Channel |
|
||||
| **Inputs** | OHLCV bar (TBar) |
|
||||
| **Parameters** | `numDevs` (default DefaultNumDevs) |
|
||||
| **Outputs** | Multiple series (Upper, Lower, Vwap, StdDev, Width) |
|
||||
| **Output range** | Tracks input |
|
||||
| **Warmup** | `2` bars |
|
||||
|
||||
### TL;DR
|
||||
|
||||
- VWAP with Standard Deviation Bands combines the Volume Weighted Average Price with a single configurable standard deviation band pair, providing a ...
|
||||
- Parameterized by `numdevs` (default defaultnumdevs).
|
||||
- Output range: Tracks input.
|
||||
- Requires `2` bars of warmup before first valid output (IsHot = true).
|
||||
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
|
||||
|
||||
VWAP with Standard Deviation Bands combines the Volume Weighted Average Price with a single configurable standard deviation band pair, providing a simpler alternative to VWAPBANDS (which uses dual $\pm 1\sigma$ and $\pm 2\sigma$ levels). Three running sums enable O(1) streaming updates. A session reset mechanism clears accumulations at configurable intervals, keeping the indicator anchored to current market structure. The configurable deviation parameter allows traders to select their desired confidence level ($1\sigma$ ≈ 68%, $2\sigma$ ≈ 95%, $3\sigma$ ≈ 99.7%).
|
||||
|
||||
## Historical Context
|
||||
|
||||
Reference in New Issue
Block a user