- Rust core: typical_price.rs ((H+L+C)/3), median_price.rs ((H+L)/2), weighted_close.rs ((H+L+2C)/4) — stateless per-bar OHLC transforms — and linreg.rs (LinearRegression — endpoint of a rolling ordinary-least-squares fit) and linreg_slope.rs (LinRegSlope — slope of that fit). Each with a full Indicator impl, runnable doctest and reference / property / warmup / reset / batch==streaming tests. - Python: PyTypicalPrice / PyMedianPrice / PyWeightedClose / PyLinearRegression / PyLinRegSlope PyO3 classes + module registration + .pyi stubs. - Node: explicit TypicalPriceNode / MedianPriceNode / WeightedCloseNode / LinearRegressionNode / LinRegSlopeNode; index.d.ts and index.js updated. - WASM: explicit WasmTypicalPrice / WasmMedianPrice / WasmWeightedClose; WasmLinearRegression / WasmLinRegSlope via the scalar macro. - Wiki: a new indicators/statistics/ folder with five Indicator-*.md pages, a new "Statistics" family in Indicators-Overview.md and Home.md. cargo fmt + clippy (core/wickra/data/wasm/node) clean; 454 core tests, 25 data tests and 66 doctests green.
3.4 KiB
WeightedClose
Weighted Close — the bar's
(high + low + 2·close) / 4, a per-bar price that gives the close double weight.
Quick reference
| Field | Value |
|---|---|
| Family | Statistics |
| Sub-category | Price transforms |
| Input type | Candle (uses high, low, close) |
| Output type | f64 |
| Output range | unbounded (price scale) |
| Default parameters | none (no parameters) |
| Warmup period | 1 |
| Interpretation | A representative per-bar price that leans on the close. |
Formula
WeightedClose = (high + low + 2·close) / 4
Like the TypicalPrice, the weighted close
collapses an OHLC bar to one number — but it counts the close twice, so the
result sits closer to where the bar settled than to its range. Reach for it
when the closing print carries more signal than the extremes.
Parameters
WeightedClose takes no parameters — WeightedClose::new() in Rust,
wickra.WeightedClose() in Python, new ta.WeightedClose() in Node.
Inputs / Outputs
From crates/wickra-core/src/indicators/weighted_close.rs:
impl Indicator for WeightedClose {
type Input = Candle;
type Output = f64;
// update(&mut self, input: Candle) -> Option<f64>
}
WeightedClose is a candle-input indicator that reads high, low and
close. In Python the streaming update accepts a 6-tuple or a dict; the
batch helper takes high, low, close numpy arrays. Node and WASM expose
update(high, low, close) and the matching batch.
Warmup
WeightedClose::new().warmup_period() == 1. It is a stateless per-bar
transform — it emits a value from the very first candle.
Edge cases
- No warmup. Every candle produces a value immediately.
- Reset.
wc.reset()only clears theis_readyflag; there is no rolling state to discard.
Examples
Rust
use wickra::{Candle, Indicator, WeightedClose};
fn main() -> Result<(), Box<dyn std::error::Error>> {
let mut wc = WeightedClose::new();
let v = wc.update(Candle::new(10.0, 12.0, 8.0, 11.0, 1.0, 0)?);
println!("{:?}", v);
Ok(())
}
Output:
Some(10.5)
(12 + 8 + 2·11) / 4 = 42 / 4 = 10.5. This matches the reference_value
test in crates/wickra-core/src/indicators/weighted_close.rs.
Python
import numpy as np
import wickra as ta
wc = ta.WeightedClose()
print(wc.batch(np.array([12.0]), np.array([8.0]), np.array([11.0])))
Output:
[10.5]
Node
const ta = require('wickra');
const wc = new ta.WeightedClose();
console.log(wc.batch([12], [8], [11]));
Output:
[ 10.5 ]
Interpretation
The weighted close sits on the spectrum between the raw close and the
TypicalPrice: closer to the close, but still
nudged by the bar's range. Use it as a drop-in close replacement when you want
the settlement to dominate without ignoring the extremes entirely.
Common pitfalls
- Feeding it scalar prices. It needs the full
high/low/closebar.
References
The Weighted Close; the (H + L + 2C) / 4 definition is standard (TA-Lib's
WCLPRICE).
See also
- Indicator-TypicalPrice.md —
(H + L + C) / 3. - Indicator-MedianPrice.md —
(H + L) / 2. - Indicators-Overview.md — the full taxonomy.