kingchenc
6643f7a81d
Second half of the eight indicators that fill out the new family taxonomy. - Rust core: true_range.rs (TrueRange — the raw single-bar volatility ATR averages), chaikin_volatility.rs (ChaikinVolatility — rate of change of a smoothed high-low spread), z_score.rs (ZScore — price normalised against its rolling mean and standard deviation) and linreg_angle.rs (LinRegAngle — the rolling regression slope as a degree angle). Each with a full Indicator impl, runnable doctest and reference / property / warmup / reset / batch==streaming tests. - Python / Node / WASM: classes wired through all three bindings (ZScore and LinRegAngle ride the scalar macros where possible) plus .pyi stubs and __init__.py / __all__ entries. - Wiki: four new Indicator-*.md pages. The eight-family taxonomy restructure (Overview / Home / README / folder layout) lands next in F13c. cargo fmt + clippy (core/wickra/data/wasm/node) clean; 508 core tests, 25 data tests and 74 doctests green.
155 lines
4.3 KiB
Markdown
155 lines
4.3 KiB
Markdown
# ChaikinVolatility
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> Chaikin Volatility — the rate of change of a smoothed high-low spread;
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> is the trading range widening or narrowing?
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## Quick reference
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| Field | Value |
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|-------|-------|
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| Family | Volatility & Bands |
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| Input type | `Candle` (uses `high`, `low`) |
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| Output type | `f64` |
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| Output range | unbounded around zero (percent) |
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| Default parameters | `ema_period = 10`, `roc_period = 10` (Python) |
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| Warmup period | `ema_period + roc_period` |
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| Interpretation | Positive = ranges expanding, negative = ranges contracting. |
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## Formula
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```
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spread_t = high_t − low_t
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smoothed_t = EMA(spread, ema_period)_t
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ChaikinVol = 100 · (smoothed_t − smoothed_{t−roc_period}) / smoothed_{t−roc_period}
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```
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Marc Chaikin's volatility measure tracks not the *level* of the trading range
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but how fast it is *widening or narrowing*. The bar's high-low spread is
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EMA-smoothed, then run through a rate-of-change: a rising value means ranges
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are expanding (often near a market top, as fear spikes), a falling value means
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they are contracting (a quiet, complacent market). The classic configuration
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smooths the spread with a `10`-period EMA and takes its `10`-period rate of
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change.
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## Parameters
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- `ema_period` — the EMA that smooths the high-low spread (`10`).
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- `roc_period` — the rate-of-change lookback over the smoothed spread (`10`).
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`ChaikinVolatility::classic()` returns the `(10, 10)` configuration.
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## Inputs / Outputs
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From `crates/wickra-core/src/indicators/chaikin_volatility.rs`:
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```rust
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impl Indicator for ChaikinVolatility {
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type Input = Candle;
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type Output = f64;
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// update(&mut self, input: Candle) -> Option<f64>
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}
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```
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`ChaikinVolatility` is a **candle-input** indicator that reads `high` and
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`low`. Python's streaming `update` accepts a 6-tuple or a dict; the batch
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helper takes `high`, `low` numpy arrays. Node and WASM expose
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`update(high, low)` and the matching `batch`.
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## Warmup
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`ChaikinVolatility::classic().warmup_period() == 20`. The EMA emits at candle
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`ema_period`; the rate-of-change then needs `roc_period` more smoothed values.
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## Edge cases
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- **Constant range.** A constant high-low spread smooths to a constant EMA,
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whose rate of change is `0`.
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- **Expanding range.** A monotonically widening range reads positive.
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- **Reset.** `cv.reset()` clears the inner EMA and ROC.
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## Examples
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### Rust
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```rust
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use wickra::{BatchExt, Candle, Indicator, ChaikinVolatility};
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fn main() -> Result<(), Box<dyn std::error::Error>> {
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let mut cv = ChaikinVolatility::new(10, 10)?;
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// A constant 2-wide range -> constant EMA -> zero rate of change.
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let candles: Vec<Candle> = (0..40)
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.map(|i| {
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let base = 100.0 + f64::from(i);
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Candle::new(base, base + 1.0, base - 1.0, base, 1.0, i).unwrap()
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})
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.collect();
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println!("{:?}", cv.batch(&candles).last().unwrap());
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Ok(())
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}
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```
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Output:
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```
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Some(0.0)
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```
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### Python
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```python
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import numpy as np
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import wickra as ta
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cv = ta.ChaikinVolatility(10, 10)
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n = 40
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base = np.arange(n, dtype=float) + 100.0
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print(cv.batch(base + 1.0, base - 1.0)[-1])
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```
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Output:
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```
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0.0
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```
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### Node
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```javascript
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const ta = require('wickra');
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const cv = new ta.ChaikinVolatility(10, 10);
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const base = Array.from({ length: 40 }, (_, i) => 100 + i);
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const out = cv.batch(base.map((b) => b + 1), base.map((b) => b - 1));
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console.log(out[out.length - 1]);
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```
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Output:
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```
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0
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```
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## Interpretation
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A rising Chaikin Volatility warns that ranges are expanding fast — Chaikin
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associated sharp rises with market tops, where panic widens bars. A low or
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falling reading is the calm, range-contracting market that often precedes a
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move. It complements [`Atr`](Indicator-Atr.md): ATR gives the level of
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volatility, Chaikin Volatility gives its momentum.
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## Common pitfalls
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- **Reading it as a volatility level.** It is a *rate of change* — zero means
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steady ranges, not zero volatility.
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- **Feeding it scalar prices.** It needs the `high`/`low` bar.
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## References
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Marc Chaikin's Chaikin Volatility; the EMA-of-spread rate-of-change definition
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here is the standard one.
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## See also
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- [Indicator-Atr.md](Indicator-Atr.md) — the level of per-bar volatility.
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- [Indicator-TrueRange.md](Indicator-TrueRange.md) — raw single-bar range.
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- [Indicators-Overview.md](../../Indicators-Overview.md) — the full taxonomy.
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