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wickra/docs/wiki/indicators/volatility/Indicator-Keltner.md
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2026-05-22 16:18:04 +02:00
# Keltner Channels
> A pure composition of [EMA](../trend/Indicator-Ema.md) on typical price plus
> ATR-scaled envelopes. The middle line is the trend filter, the bands are
> the volatility cone.
## Quick reference
| Item | Value |
|---------------------|------------------------------------------------------------------------------------|
| Family | Volatility |
| Sub-category | envelope (composed: EMA + ATR) |
| Input type | `Candle` (uses `high`, `low`, `close`) |
| Output type | `KeltnerOutput { upper: f64, middle: f64, lower: f64 }` |
| Output range | unbounded; `lower ≤ middle ≤ upper` |
| Default parameters | `ema_period = 20`, `atr_period = 10`, `multiplier = 2.0` |
| Warmup period | `max(ema_period, atr_period)` (`20` for defaults) — see Warmup notes |
| Interpretation | trend-following envelope; tags signal momentum, not exhaustion |
## Formula
```
middle_t = EMA_{ema_period}( typical_price_t ) // tp = (H+L+C)/3
upper_t = middle_t + multiplier * ATR_{atr_period}_t
lower_t = middle_t - multiplier * ATR_{atr_period}_t
```
The middle line is an EMA of **typical price**, not of close
(`crates/wickra-core/src/indicators/keltner.rs:62`,
`candle.typical_price()`).
## Parameters
| Name | Type | Default | Constraint | Source |
|--------------|---------|---------|-------------------------|----------------------------------------------|
| `ema_period` | `usize` | `20` | `> 0` | `Keltner::new` (`keltner.rs:33`) |
| `atr_period` | `usize` | `10` | `> 0` | `Keltner::new` (`keltner.rs:33`) |
| `multiplier` | `f64` | `2.0` | finite and `> 0.0` | `Keltner::new` (`keltner.rs:34-36`) |
Python defaults from
`#[pyo3(signature = (ema_period=20, atr_period=10, multiplier=2.0))]` in
`bindings/python/src/lib.rs`. `Keltner::classic()` returns the same
configuration.
## Inputs / Outputs
```rust
impl Indicator for Keltner {
type Input = Candle;
type Output = KeltnerOutput;
fn update(&mut self, candle: Candle) -> Option<KeltnerOutput>;
}
pub struct KeltnerOutput { pub upper: f64, pub middle: f64, pub lower: f64 }
```
- **Python streaming.** Returns `(upper, middle, lower)` tuple or `None`.
- **Python batch.** `Keltner.batch(high, low, close)` returns a 2-D
`np.ndarray` of shape `(n, 3)` with columns `[upper, middle, lower]`;
warmup rows are `NaN` across all three columns.
- **Node streaming.** Returns a `{ upper, middle, lower }` object or
`null`.
- **Node batch.** `keltner.batch(high, low, close)` returns a flat
`Array<number>` of length `n * 3` interleaved per row:
`[u0, m0, l0, u1, m1, l1, …]`.
## Warmup
`warmup_period()` reports `max(ema_period, atr_period)` — for the
default `(20, 10, 2.0)` that is `20`.
**Important caveat verified empirically.** Because `Keltner::update`
calls `self.ema.update(...)?` *before* `self.atr.update(...)?`, the ATR
sub-indicator only receives an input on candles where the EMA already
has a value. The actual first emission therefore occurs after roughly
`ema_period + atr_period - 1` candles, not `max(ema_period, atr_period)`.
With the classic `(20, 10, 2.0)` configuration the first non-`None`
output is the 29th candle (index `28`), not the 20th. Code reference:
`keltner.rs:61-69`. Plan your data prefix accordingly.
## Edge cases
- **Flat market.** A constant-OHLC series produces `upper == middle == lower`
because ATR collapses to `0`. The pinned test
`flat_market_collapses_bands` covers this.
- **Trending market.** When ATR rises, both bands widen symmetrically
around the EMA centerline.
- **Reset.** `reset()` resets both the underlying EMA and ATR; the
configured periods/multiplier are preserved.
- **NaN / infinity.** `Candle::new` rejects non-finite OHLC values up
front; the indicator never receives them.
- **Invalid params.** `ema_period == 0`, `atr_period == 0`, or non-positive
`multiplier` returns an error from `Keltner::new`.
## Examples
### Rust
```rust
use wickra::{BatchExt, Candle, Indicator, Keltner};
fn main() -> Result<(), Box<dyn std::error::Error>> {
let candles = vec![
Candle::new(10.0, 11.0, 9.0, 10.5, 1.0, 0)?,
Candle::new(10.5, 12.0, 10.0, 11.5, 1.0, 0)?,
Candle::new(11.5, 13.0, 11.0, 12.5, 1.0, 0)?,
Candle::new(12.5, 14.0, 12.0, 13.5, 1.0, 0)?,
Candle::new(13.5, 15.0, 13.0, 14.5, 1.0, 0)?,
];
let mut k = Keltner::new(3, 3, 2.0)?;
for (i, v) in k.batch(&candles).into_iter().enumerate() {
println!("i={i} -> {:?}", v);
}
Ok(())
}
```
Output:
```
i=0 -> None
i=1 -> None
i=2 -> None
i=3 -> None
i=4 -> Some(KeltnerOutput { upper: 17.166666666666664, middle: 13.166666666666666, lower: 9.166666666666666 })
```
Notice the first emission is at `i = 4` (the 5th candle), not `i = 2`,
even though `max(ema=3, atr=3) = 3`. This is the EMA-gates-ATR effect
documented under **Warmup**.
### Python
```python
import numpy as np
import wickra as ta
k = ta.Keltner(3, 3, 2.0)
h = np.array([11.0, 12.0, 13.0, 14.0, 15.0])
l = np.array([ 9.0, 10.0, 11.0, 12.0, 13.0])
c = np.array([10.5, 11.5, 12.5, 13.5, 14.5])
print(k.batch(h, l, c))
```
Output:
```
[[ nan nan nan]
[ nan nan nan]
[ nan nan nan]
[ nan nan nan]
[17.16666667 13.16666667 9.16666667]]
```
### Node
```js
const w = require('wickra');
const k = new w.Keltner(3, 3, 2.0);
const flat = k.batch(
[11, 12, 13, 14, 15],
[ 9, 10, 11, 12, 13],
[10.5, 11.5, 12.5, 13.5, 14.5],
);
console.log('length:', flat.length);
console.log('row 4 [upper, middle, lower]:', flat.slice(12, 15));
```
Output:
```
length: 15
row 4 [upper, middle, lower]: [ 17.166666666666664, 13.166666666666666, 9.166666666666666 ]
```
## Interpretation
- **Trend filter.** Persistent closes above the upper band signal
trend continuation, much like Bollinger's "walking the band" pattern;
Keltner is generally tighter than Bollinger on noisy series because
ATR responds more smoothly than a rolling stddev.
- **Squeeze cross-over.** A common "squeeze" setup compares Bollinger
bandwidth to Keltner channel width: when Bollinger fits *inside*
Keltner, a volatility expansion is statistically more likely.
- **Pullback entries.** In a defined uptrend, pullbacks to the middle
EMA line are a classic continuation entry; the lower band acts as
the disaster stop.
## Common pitfalls
- **Reported warmup understates the true warmup.** `warmup_period()`
reports `max(ema_period, atr_period)`, but because the EMA is
evaluated first and short-circuits the ATR update via `?`, the
indicator only emits after roughly `ema_period + atr_period - 1`
candles. For the classic `(20, 10, 2.0)` you need 29 candles, not
20, before the first valid `KeltnerOutput`. Inspecting
`is_ready()` is the safest gate.
- **Typical price ≠ close.** The middle EMA runs on
`(H + L + C) / 3`, not on close. A pre-computed "EMA of close"
panel will not equal the Keltner middle line and trying to align
them at floating-point precision will fail.
## References
- Chester W. Keltner, *How to Make Money in Commodities*, 1960. The
original construction used a 10-day SMA of typical price with an
envelope sized by the 10-day average range. The modern variant
(EMA centerline + ATR envelope) is the form Wickra implements.
- Linda Bradford Raschke popularised the EMA + ATR rephrasing in the
1990s; this is the version most TA libraries ship today.
## See also
- [EMA](../trend/Indicator-Ema.md) — the centerline component.
- [ATR](Indicator-Atr.md) — the envelope width component.
- [Bollinger Bands](Indicator-BollingerBands.md) — envelope using stddev
rather than ATR; useful side-by-side comparison.
- [Donchian Channels](Indicator-Donchian.md) — envelope using rolling
extrema with no smoothing.