* feat(rvi): add Relative Vigor Index
Dorsey's RVI = SMA(close - open, period) / SMA(high - low, period) over
a rolling window of period candles. Candle input, single parameter
period (default 10). Positive on average-bullish windows, negative on
average-bearish. Holds the previous value if the entire window has
zero range (denominator undefined).
Reference: Donald Dorsey, also pandas-ta rvi.
Touchpoints: rvi.rs + mod.rs + lib.rs re-export, PyRvi + __init__.py
+ test_new_indicators CANDLE_SCALAR + test_known_values reference,
RviNode (4-column OHLC batch) + index.d.ts/index.js + indicators.test
.js factory + reference, WasmRvi + make_candle_ohlc helper, candle-fuzz
target + criterion bench, README + CHANGELOG.
* feat(pgo): add Pretty Good Oscillator
Mark Johnson's PGO = (close - SMA(close, period)) / EMA(TR, period).
Counts roughly how many ATR-equivalents the close sits from its
period-bar mean. Candle input, single parameter period (default 14).
Johnson's heuristic uses +3/-3 crossings as entry signals.
Touchpoints: pgo.rs + mod.rs + lib.rs re-export, PyPgo + __init__.py
+ test_new_indicators CANDLE_SCALAR + test_known_values flat-close
reference, PgoNode (h/l/c) + index.d.ts/index.js + indicators.test.js
factory + reference, WasmPgo, candle-fuzz target + bench, README +
CHANGELOG.
* feat(kst): add Know Sure Thing (Pring)
Pring's long-horizon momentum oscillator: weighted sum of four
SMA-smoothed ROC series with fixed weights 1, 2, 3, 4, plus an SMA
signal line. Nine parameters (four ROC periods, four SMA periods, one
signal period); classic() applies Pring's recommended defaults.
Multi-output indicator emitting KstOutput { kst, signal }.
Touchpoints: kst.rs + mod.rs + lib.rs re-export, PyKst + __init__.py
+ test_new_indicators MULTI + test_known_values flat-input reference,
KstNode + KstValue + index.d.ts/index.js + indicators.test.js multi
factory + reference, WasmKst (manual JsValue object), scalar-fuzz
target (handled outside the f64-output drive helper), README +
CHANGELOG.
* feat(smi): add Stochastic Momentum Index (Blau)
Blau's doubly-EMA-smoothed bounded oscillator: measures the close's
displacement from the centre of the recent high-low range, scaled by
the smoothed range. Candle input, three parameters (period, d_period,
d2_period) with defaults 5 / 3 / 3.
Internally feeds both the displacement-EMA stack and the range-EMA
stack on every candle so they warm up in parallel (gating either
behind the other starves the second by one input).
Touchpoints: smi.rs + mod.rs + lib.rs re-export, PySmi + __init__.py
+ test_new_indicators CANDLE_SCALAR + test_known_values flat-input
reference, SmiNode + index.d.ts/index.js + indicators.test.js factory
+ reference, WasmSmi, candle-fuzz target, README + CHANGELOG.
* feat(laguerre-rsi): add Ehlers Laguerre RSI
Four-stage Laguerre polynomial filter wrapped in an RSI-style up/down
accumulator. Single gamma in [0, 1] (default 0.5) trades lag for
smoothness. State is seeded by setting all four L_i to the first input
so a constant series stays at the neutral 50. Output clamped to
[0, 100] to absorb floating-point rounding.
Reference: Ehlers, Time Warp - Without Space Travel, 2002.
Touchpoints: laguerre_rsi.rs + mod.rs + lib.rs re-export, PyLaguerreRsi
+ __init__.py + test_new_indicators SCALAR + test_known_values neutral
reference, LaguerreRsiNode + index.d.ts/index.js + indicators.test.js
factory + reference, WasmLaguerreRsi via scalar macro, scalar-fuzz
target, README + CHANGELOG.
* feat(connors-rsi): add Connors RSI (CRSI)
Larry Connors' 3-component aggregate: RSI(close), RSI(streak), and
PercentRank of the 1-period return over the last period_rank returns.
Each component is bounded in [0, 100] so the aggregate is too.
Three parameters (period_rsi, period_streak, period_rank) with
defaults 3 / 2 / 100. Streak tracks consecutive up/down runs (resets
to 0 on unchanged close).
Touchpoints: connors_rsi.rs + mod.rs + lib.rs re-export, PyConnorsRsi
+ __init__.py + test_new_indicators SCALAR + test_known_values bounded
reference, ConnorsRsiNode + index.d.ts/index.js + indicators.test.js
factory + reference, WasmConnorsRsi via scalar macro, scalar-fuzz
target, README + CHANGELOG.
* feat(inertia): add Dorsey Inertia (RVI + LinReg)
Donald Dorsey's Inertia — a LinearRegression smoothing of the RVI
series. Endpoint of an n-bar least-squares fit of RVI is the indicator
reading. Preserves trend direction while damping the ratio. Candle
input, two parameters (rvi_period, linreg_period) with defaults 14 / 20.
Touchpoints: inertia.rs + mod.rs + lib.rs re-export, PyInertia +
__init__.py + test_new_indicators CANDLE_SCALAR + test_known_values
constant reference, InertiaNode (4-column OHLC batch) + index.d.ts /
index.js + indicators.test.js factory + reference, WasmInertia,
candle-fuzz target, README + CHANGELOG.
* test(kst): Move KST out of MULTI dict (it is scalar-input)
KST sits in the MULTI dict (candle-input, multi-output) but its
update() takes a single f64, not a candle tuple. The shared streaming
loop in test_multi_streaming_matches_batch fed the OHLCV tuple in,
which crashed with `TypeError: argument 'value': must be real number,
not tuple` on every Python matrix entry.
Split into a new MULTI_SCALAR_INPUT dict with its own test function
that feeds the close-price stream as floats. KST is currently the
only such indicator; structure is ready for future scalar-input
multi-output additions (e.g. some MACD-shaped indicators).
* test(coverage): Cover SMI zero-range and ConnorsRsi zero-prev cold paths
codecov/patch on PR 40 flagged two uncovered defensive branches:
- SMI returns self.current early when the smoothed range collapses to
zero (`r2 <= 0.0`) so the formula stays defined. Exercised by feeding
bars where high == low.
- ConnorsRsi skips the ROC ring-buffer update when the previous price
is exactly zero so the divide-by-zero in `(input - prev) / prev` is
impossible. Exercised by seeding the first bar at 0.0.
218 lines
6.4 KiB
Rust
218 lines
6.4 KiB
Rust
//! Relative Vigor Index (RVI).
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use std::collections::VecDeque;
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use crate::error::{Error, Result};
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use crate::ohlcv::Candle;
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use crate::traits::Indicator;
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/// Relative Vigor Index — Donald Dorsey's ratio of intra-bar drive (close − open)
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/// to intra-bar range (high − low), averaged over a `period`-bar window.
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///
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/// The reading is `SMA(close − open, period) / SMA(high − low, period)`. A
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/// positive value means the average bar in the window closed above where it
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/// opened (bullish "vigor"); a negative value means the average closed below.
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/// The denominator's rolling-window SMA can fall to zero on a perfectly flat
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/// stretch, in which case the recurrence is undefined and the indicator holds
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/// its previous value.
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///
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/// # Example
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///
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/// ```
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/// use wickra_core::{Candle, Indicator, Rvi};
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///
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/// let mut rvi = Rvi::new(10).unwrap();
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/// let mut last = None;
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/// for i in 0..40 {
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/// let o = 100.0 + f64::from(i);
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/// let c = o + 0.5;
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/// let candle = Candle::new(o, c + 0.2, o - 0.2, c, 1.0, i64::from(i)).unwrap();
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/// last = rvi.update(candle);
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/// }
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/// assert!(last.is_some());
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/// ```
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#[derive(Debug, Clone)]
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pub struct Rvi {
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period: usize,
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window: VecDeque<(f64, f64)>,
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sum_num: f64,
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sum_den: f64,
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current: Option<f64>,
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}
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impl Rvi {
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/// # Errors
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/// Returns [`Error::PeriodZero`] if `period == 0`.
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pub fn new(period: usize) -> Result<Self> {
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if period == 0 {
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return Err(Error::PeriodZero);
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}
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Ok(Self {
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period,
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window: VecDeque::with_capacity(period),
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sum_num: 0.0,
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sum_den: 0.0,
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current: None,
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})
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}
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/// Configured period.
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pub const fn period(&self) -> usize {
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self.period
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}
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/// Current value if available.
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pub const fn value(&self) -> Option<f64> {
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self.current
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}
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}
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impl Indicator for Rvi {
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type Input = Candle;
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type Output = f64;
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fn update(&mut self, candle: Candle) -> Option<f64> {
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let num = candle.close - candle.open;
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let den = candle.high - candle.low;
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if self.window.len() == self.period {
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let (old_n, old_d) = self.window.pop_front().expect("window is non-empty");
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self.sum_num -= old_n;
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self.sum_den -= old_d;
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}
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self.window.push_back((num, den));
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self.sum_num += num;
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self.sum_den += den;
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if self.window.len() < self.period {
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return None;
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}
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if self.sum_den <= 0.0 {
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// Window of perfectly flat (zero-range) bars: ratio undefined.
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// Hold the previous value rather than emitting NaN / inf.
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return self.current;
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}
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let value = self.sum_num / self.sum_den;
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self.current = Some(value);
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Some(value)
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}
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fn reset(&mut self) {
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self.window.clear();
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self.sum_num = 0.0;
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self.sum_den = 0.0;
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self.current = None;
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}
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fn warmup_period(&self) -> usize {
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self.period
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}
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fn is_ready(&self) -> bool {
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self.current.is_some()
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}
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fn name(&self) -> &'static str {
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"RVI"
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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use crate::traits::BatchExt;
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use approx::assert_relative_eq;
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fn candle(open: f64, high: f64, low: f64, close: f64, ts: i64) -> Candle {
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Candle::new(open, high, low, close, 1.0, ts).unwrap()
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}
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#[test]
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fn rejects_zero_period() {
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assert!(matches!(Rvi::new(0), Err(Error::PeriodZero)));
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}
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#[test]
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fn accessors_and_metadata() {
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let mut r = Rvi::new(10).unwrap();
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assert_eq!(r.period(), 10);
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assert_eq!(r.warmup_period(), 10);
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assert_eq!(r.name(), "RVI");
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assert_eq!(r.value(), None);
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for i in 0..10 {
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r.update(candle(10.0, 11.0, 9.0, 10.5, i));
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}
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assert!(r.value().is_some());
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}
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#[test]
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fn reference_value_period_2() {
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// Two bars with (open, high, low, close) = (10, 11, 9, 10.5) and
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// (10.5, 11.5, 10, 11). Per bar:
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// num1 = 0.5, num2 = 0.5; sum = 1.0
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// den1 = 2.0, den2 = 1.5; sum = 3.5
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// RVI = 1.0 / 3.5 ≈ 0.2857142857
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let mut r = Rvi::new(2).unwrap();
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assert_eq!(r.update(candle(10.0, 11.0, 9.0, 10.5, 0)), None);
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let v = r.update(candle(10.5, 11.5, 10.0, 11.0, 1)).unwrap();
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assert_relative_eq!(v, 1.0 / 3.5, epsilon = 1e-12);
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}
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#[test]
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fn warmup_emits_first_value_at_period() {
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let mut r = Rvi::new(3).unwrap();
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for i in 0..2 {
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assert_eq!(r.update(candle(10.0, 11.0, 9.0, 10.5, i)), None);
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}
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assert!(r.update(candle(10.5, 11.5, 10.0, 11.0, 2)).is_some());
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}
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#[test]
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fn pure_uptrend_is_positive() {
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// Every bar closes above its open and has a non-zero range: RVI > 0.
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let mut r = Rvi::new(5).unwrap();
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for i in 0..10 {
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let o = 10.0 + f64::from(i);
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let c = o + 0.5;
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r.update(candle(o, c + 0.2, o - 0.2, c, i64::from(i)));
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}
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let v = r.value().unwrap();
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assert!(v > 0.0, "uptrend RVI should be positive: {v}");
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}
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#[test]
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fn zero_range_window_holds_value() {
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// Window of perfectly flat bars (high == low): ratio undefined,
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// indicator holds.
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let mut r = Rvi::new(3).unwrap();
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r.update(candle(10.0, 10.0, 10.0, 10.0, 0));
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r.update(candle(10.0, 10.0, 10.0, 10.0, 1));
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assert_eq!(r.update(candle(10.0, 10.0, 10.0, 10.0, 2)), None);
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}
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#[test]
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fn batch_equals_streaming() {
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let candles: Vec<Candle> = (0..40_i64)
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.map(|i| {
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let o = 100.0 + (i as f64 * 0.3).sin() * 5.0;
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let c = o + (i as f64 * 0.1).cos();
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candle(o, o.max(c) + 0.5, o.min(c) - 0.5, c, i)
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})
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.collect();
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let batch = Rvi::new(10).unwrap().batch(&candles);
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let mut b = Rvi::new(10).unwrap();
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let streamed: Vec<_> = candles.iter().map(|c| b.update(*c)).collect();
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assert_eq!(batch, streamed);
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}
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#[test]
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fn reset_clears_state() {
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let mut r = Rvi::new(5).unwrap();
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for i in 0..10 {
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r.update(candle(10.0, 11.0, 9.0, 10.5, i));
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}
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assert!(r.is_ready());
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r.reset();
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assert!(!r.is_ready());
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assert_eq!(r.update(candle(10.0, 11.0, 9.0, 10.5, 0)), None);
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}
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}
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