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wickra/crates/wickra-core/src/indicators/adl.rs
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//! Accumulation/Distribution Line.
use crate::ohlcv::Candle;
use crate::traits::Indicator;
/// Accumulation/Distribution Line — Marc Chaikin's cumulative volume-flow
/// indicator.
///
/// Each bar contributes a *money-flow volume*: the bar's volume weighted by
/// where the close fell within the bar's range.
///
/// ```text
/// MFM_t = ((close low) (high close)) / (high low) (the money-flow multiplier, 1..+1)
/// MFV_t = MFM_t · volume_t
/// ADL_t = ADL_{t1} + MFV_t
/// ```
///
/// A close near the high makes the multiplier near `+1` (accumulation), near
/// the low near `1` (distribution). The running total is unbounded and drifts
/// with cumulative volume — what matters is its slope and its divergence from
/// price. A bar with `high == low` contributes `0`.
///
/// # Example
///
/// ```
/// use wickra_core::{Candle, Indicator, Adl};
///
/// let mut indicator = Adl::new();
/// let mut last = None;
/// for i in 0..80 {
/// let base = 100.0 + f64::from(i);
/// let candle =
/// Candle::new(base, base + 2.0, base - 2.0, base + 1.0, 10.0, i64::from(i)).unwrap();
/// last = indicator.update(candle);
/// }
/// assert!(last.is_some());
/// ```
#[derive(Debug, Clone, Default)]
pub struct Adl {
total: f64,
has_emitted: bool,
}
impl Adl {
/// Construct a new Accumulation/Distribution Line starting at zero.
pub const fn new() -> Self {
Self {
total: 0.0,
has_emitted: false,
}
}
/// Current cumulative value if at least one candle has been ingested.
pub const fn value(&self) -> Option<f64> {
if self.has_emitted {
Some(self.total)
} else {
None
}
}
}
impl Indicator for Adl {
type Input = Candle;
type Output = f64;
fn update(&mut self, candle: Candle) -> Option<f64> {
let range = candle.high - candle.low;
let mfv = if range == 0.0 {
// A zero-range bar carries no positional information.
0.0
} else {
let mfm = ((candle.close - candle.low) - (candle.high - candle.close)) / range;
mfm * candle.volume
};
self.total += mfv;
self.has_emitted = true;
Some(self.total)
}
fn reset(&mut self) {
self.total = 0.0;
self.has_emitted = false;
}
fn warmup_period(&self) -> usize {
1
}
fn is_ready(&self) -> bool {
self.has_emitted
}
fn name(&self) -> &'static str {
"ADL"
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::traits::BatchExt;
use approx::assert_relative_eq;
fn candle(open: f64, high: f64, low: f64, close: f64, volume: f64, ts: i64) -> Candle {
Candle::new(open, high, low, close, volume, ts).unwrap()
}
#[test]
fn reference_values() {
// bar 1: close at high -> MFM = +1 -> MFV = +100; ADL = 100.
// bar 2: h=12 l=8 c=9 -> MFM = ((9-8)-(12-9))/4 = -0.5 -> MFV = -100;
// ADL = 100 - 100 = 0.
let mut adl = Adl::new();
let out = adl.batch(&[
candle(8.0, 10.0, 8.0, 10.0, 100.0, 0),
candle(10.0, 12.0, 8.0, 9.0, 200.0, 1),
]);
assert_relative_eq!(out[0].unwrap(), 100.0, epsilon = 1e-12);
assert_relative_eq!(out[1].unwrap(), 0.0, epsilon = 1e-12);
}
#[test]
fn emits_from_first_candle() {
let mut adl = Adl::new();
assert_eq!(adl.warmup_period(), 1);
assert!(adl.update(candle(8.0, 10.0, 8.0, 9.0, 50.0, 0)).is_some());
}
#[test]
fn close_at_high_accumulates_full_volume() {
// Every bar closes at its high: MFM = +1, so ADL grows by `volume`.
let mut adl = Adl::new();
let mut expected = 0.0;
for i in 0..10 {
let c = candle(8.0, 10.0, 8.0, 10.0, 25.0, i);
expected += 25.0;
assert_relative_eq!(adl.update(c).unwrap(), expected, epsilon = 1e-9);
}
}
#[test]
fn zero_range_bar_contributes_nothing() {
let mut adl = Adl::new();
adl.update(candle(8.0, 10.0, 8.0, 10.0, 100.0, 0));
let before = adl.value().unwrap();
// A flat candle (high == low) adds zero.
let after = adl.update(candle(9.0, 9.0, 9.0, 9.0, 999.0, 1)).unwrap();
assert_relative_eq!(after, before, epsilon = 1e-12);
}
#[test]
fn reset_clears_state() {
let mut adl = Adl::new();
adl.batch(&[
candle(8.0, 10.0, 8.0, 9.0, 100.0, 0),
candle(9.0, 11.0, 9.0, 10.0, 100.0, 1),
]);
assert!(adl.is_ready());
adl.reset();
assert!(!adl.is_ready());
assert_eq!(adl.value(), None);
}
#[test]
fn batch_equals_streaming() {
let candles: Vec<Candle> = (0..60)
.map(|i| {
let mid = 100.0 + (i as f64 * 0.3).sin() * 8.0;
candle(
mid,
mid + 2.0,
mid - 2.0,
mid + 0.5,
10.0 + (i % 5) as f64,
i,
)
})
.collect();
let batch = Adl::new().batch(&candles);
let mut b = Adl::new();
let streamed: Vec<_> = candles.iter().map(|c| b.update(*c)).collect();
assert_eq!(batch, streamed);
}
}