diff --git a/crates/aura-engine/tests/stage1_meanrev_e2e.rs b/crates/aura-engine/tests/stage1_meanrev_e2e.rs new file mode 100644 index 0000000..ee1c8ce --- /dev/null +++ b/crates/aura-engine/tests/stage1_meanrev_e2e.rs @@ -0,0 +1,88 @@ +//! Mean-reversion signal composition: price -> {Ema mean, Sub dev} -> Mul sq -> +//! Ema var -> Sqrt sigma -> LinComb(k) band -> {Add upper, Sub lower} -> +//! {Gt, Gt} -> {Latch, Latch} -> Sub = bias in {-1,0,+1}. Tests the FADE +//! direction (price above mean+k*sigma -> short -1; below mean-k*sigma -> long +//! +1), the latched hold, and that no fade fires on a flat series. Built +//! straight from aura-std nodes (no CLI dependency); mirrors stage1_breakout_e2e. + +use aura_core::{Scalar, Timestamp}; +use aura_engine::{GraphBuilder, Harness, Source, VecSource}; +use aura_std::{Add, Ema, Gt, Latch, LinComb, Mul, Recorder, Sqrt, Sub}; +use std::sync::mpsc; + +// Feed `closes` into the Bollinger-fade signal subgraph (window n, band width k) +// and tap the exposure (bias) through a Recorder. Returns the emitted bias values +// in cycle order. +fn run_meanrev_bias(closes: &[f64], n: i64, k: f64) -> Vec { + let (tx, rx) = mpsc::channel(); + let mut g = GraphBuilder::new("meanrev_sig"); + let mean = g.add(Ema::builder().bind("length", Scalar::i64(n))); + let dev = g.add(Sub::builder()); // price - mean + let sq = g.add(Mul::builder()); // dev * dev + let var = g.add(Ema::builder().bind("length", Scalar::i64(n))); // EWMA variance + let sigma = g.add(Sqrt::builder()); + let band = g.add(LinComb::builder(1).bind("weights[0]", Scalar::f64(k))); // k*sigma + let upper = g.add(Add::builder()); // mean + k*sigma + let lower = g.add(Sub::builder()); // mean - k*sigma + let gt_hi = g.add(Gt::builder()); // price > upper + let gt_lo = g.add(Gt::builder()); // lower > price + let short_latch = g.add(Latch::builder()); + let long_latch = g.add(Latch::builder()); + let bias = g.add(Sub::builder()); // long_latch - short_latch + let rec = g.add(Recorder::builder(vec![aura_core::ScalarKind::F64], aura_core::Firing::Any, tx)); + let price = g.source_role("price", aura_core::ScalarKind::F64); + g.feed(price, [mean.input("series"), dev.input("lhs"), gt_hi.input("a"), gt_lo.input("b")]); + g.connect(mean.output("value"), dev.input("rhs")); + g.connect(dev.output("value"), sq.input("lhs")); + g.connect(dev.output("value"), sq.input("rhs")); + g.connect(sq.output("value"), var.input("series")); + g.connect(var.output("value"), sigma.input("value")); + g.connect(sigma.output("value"), band.input("term[0]")); + g.connect(mean.output("value"), upper.input("lhs")); + g.connect(band.output("value"), upper.input("rhs")); + g.connect(mean.output("value"), lower.input("lhs")); + g.connect(band.output("value"), lower.input("rhs")); + g.connect(upper.output("value"), gt_hi.input("b")); + g.connect(lower.output("value"), gt_lo.input("a")); + g.connect(gt_hi.output("value"), short_latch.input("set")); + g.connect(gt_lo.output("value"), short_latch.input("reset")); + g.connect(gt_lo.output("value"), long_latch.input("set")); + g.connect(gt_hi.output("value"), long_latch.input("reset")); + g.connect(long_latch.output("value"), bias.input("lhs")); + g.connect(short_latch.output("value"), bias.input("rhs")); + g.connect(bias.output("value"), rec.input("col[0]")); + let flat = g.build().expect("meanrev signal wiring resolves").compile_with_params(&[]).expect("compiles"); + let mut h = Harness::bootstrap(flat).expect("bootstraps"); + let prices: Vec<(Timestamp, Scalar)> = + closes.iter().enumerate().map(|(i, &c)| (Timestamp(i as i64), Scalar::f64(c))).collect(); + let src: Vec> = vec![Box::new(VecSource::new(prices))]; + h.run(src); + rx.try_iter().map(|(_, row): (Timestamp, Vec)| row[0].as_f64()).collect() +} + +#[test] +fn meanrev_fades_against_the_move_and_holds_the_latch() { + // k = 0 makes the band collapse to the mean (upper = lower = mean), so the + // fade fires on ANY deviation from the lagging EWMA mean -- isolating the + // direction + latch from the sigma threshold (the k>0 band is exercised by + // the real-data CLI screen). n = 3 -> alpha = 0.5, so the mean lags the level + // clearly. A long calm, then a sustained jump UP, then a sustained drop DOWN. + // calm (price == mean -> no break) | up (price > mean -> SHORT) | down (price < mean -> LONG) + let closes = [100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 130.0, 130.0, 130.0, 70.0, 70.0, 70.0]; + let bias = run_meanrev_bias(&closes, 3, 0.0); + assert!(!bias.is_empty(), "the signal must emit once warmed up"); + assert_eq!(*bias.first().unwrap(), 0.0, "calm bars (price == mean) must not fade; got {bias:?}"); + let first_short = bias.iter().position(|&b| b == -1.0).expect("an up-move must fade SHORT (-1)"); + let first_long = bias.iter().position(|&b| b == 1.0).expect("a down-move must fade LONG (+1)"); + assert!(first_short < first_long, "short (up-fade) must precede long (down-fade); got {bias:?}"); + assert_eq!(*bias.last().unwrap(), 1.0, "the down-fade long must hold to the end; got {bias:?}"); +} + +#[test] +fn meanrev_flat_series_never_fades() { + // A perfectly flat series: dev == 0, sigma == 0, band == mean, so price is + // never strictly beyond the band -> no break ever -> bias pinned at 0. + let bias = run_meanrev_bias(&[100.0; 10], 3, 2.0); + assert!(!bias.is_empty(), "the signal must emit once warmed up"); + assert!(bias.iter().all(|&b| b == 0.0), "a flat series must never fade; got {bias:?}"); +}