ChaikinMoneyFlow
Chaikin Money Flow (CMF) — the ratio of money-flow volume to total volume over a rolling window, bounded to
[−1, +1].
Quick reference
| Field | Value |
|---|---|
| Family | Volume |
| Input type | Candle (uses high, low, close, volume) |
| Output type | f64 |
| Output range | [−1, +1] |
| Default parameters | period = 20 (Python) |
| Warmup period | period |
| Interpretation | Window accumulation/distribution balance; sign and magnitude both matter. |
Formula
MFM_t = ((close − low) − (high − close)) / (high − low) (money-flow multiplier, −1..+1)
MFV_t = MFM_t · volume_t (money-flow volume)
CMF_t = Σ(MFV, period) / Σ(volume, period)CMF is the Adl increment averaged the way RSI averages gains: rather than a running total, it divides the summed money-flow volume of the last period bars by the summed volume of those bars. The result is volume-normalised, so it lives in [−1, +1] regardless of how heavily the instrument trades. A bar with high == low carries no positional information and contributes a money-flow volume of 0.
Parameters
period — the lookback window. The Python binding defaults it to 20; the Rust and Node constructors require it explicitly.
Inputs / Outputs
From crates/wickra-core/src/indicators/cmf.rs:
use wickra::{Indicator, ChaikinMoneyFlow, Candle};
// ChaikinMoneyFlow: Input = Candle, Output = f64
const _: fn(&mut ChaikinMoneyFlow, Candle) -> Option<f64> = <ChaikinMoneyFlow as Indicator>::update;ChaikinMoneyFlow is a candle-input indicator: it reads high, low, close and volume. In Python the streaming update accepts a 6-tuple or a dict; the batch helper takes high, low, close, volume numpy arrays. Node and WASM expose update(high, low, close, volume) and the matching batch.
Warmup
ChaikinMoneyFlow::new(20).warmup_period() == 20. The first value lands once the window holds a full period bars — on input index period − 1.
Edge cases
- Zero-range bar. A bar with
high == lowcontributesMFV = 0. - Empty-volume window. If the whole window traded zero volume, the
0/0ratio is defined as0.0(zero_volume_window_yields_zeropins this). - Saturated flow. Every bar closing on its high gives
MFM = +1, so CMF saturates at+1(closes_at_high_yield_cmf_onepins this). - Reset.
cmf.reset()clears the window and both running sums.
Examples
Rust
use wickra::{BatchExt, Candle, Indicator, ChaikinMoneyFlow};
fn main() -> Result<(), Box<dyn std::error::Error>> {
let mut cmf = ChaikinMoneyFlow::new(2)?;
let out = cmf.batch(&[
Candle::new(8.0, 10.0, 8.0, 10.0, 100.0, 0)?, // close at high -> MFV +100
Candle::new(10.0, 12.0, 8.0, 10.0, 100.0, 1)?, // close mid-range -> MFV 0
]);
println!("{:?}", out);
Ok(())
}Output:
[None, Some(0.5)]Bar 1 closes at its high (MFM = +1, MFV = +100); bar 2 closes mid-range (MFM = 0, MFV = 0). CMF(2) = (100 + 0) / (100 + 100) = 0.5. This matches the reference_values test in crates/wickra-core/src/indicators/cmf.rs.
Python
import numpy as np
import wickra as ta
cmf = ta.ChaikinMoneyFlow(2)
high = np.array([10.0, 12.0])
low = np.array([8.0, 8.0])
close = np.array([10.0, 10.0])
volume = np.array([100.0, 100.0])
print(cmf.batch(high, low, close, volume))Output:
[nan 0.5]Node
const ta = require('wickra');
const cmf = new ta.ChaikinMoneyFlow(2);
console.log(cmf.batch([10, 12], [8, 8], [10, 10], [100, 100]));Output:
[ NaN, 0.5 ]Interpretation
CMF reads as a balance: sustained positive values mean closes are clustering near bar highs on real volume (accumulation), sustained negative values mean the opposite (distribution). Crosses of the zero line are the textbook signal; the ±0.05 band is often treated as a neutral zone. Because CMF is volume-normalised it is comparable across instruments — unlike the raw Adl, whose level is arbitrary.
Common pitfalls
- Confusing it with the ADL. CMF is a bounded ratio; the ADL is an unbounded running total. They share the money-flow multiplier and nothing else.
- Feeding it scalar prices. It needs the full OHLCV bar.
References
Marc Chaikin's Chaikin Money Flow; the money-flow-multiplier formulation here matches the standard definition (StockCharts).
See also
- Indicator-Adl — the cumulative line CMF is built on.
- Indicator-ChaikinOscillator — the EMA-difference oscillator on the ADL.
- Indicators-Overview — the full taxonomy.