feat: add 19 indicators for external feature-extractor coverage (377 -> 396) (#175)

Adds 19 streaming indicators so an external trading-bot feature extractor can replace its hand-built features with native, batch/streaming-equivalent ones. Each is a real gap (verified against the existing catalogue), production-only, with full Python/Node/WASM bindings, fuzz drivers, and tests. Five commits, one per family group; counter 377 -> 396.

## What's added

**Price Statistics (6)** — `LogReturn`, `RealizedVolatility` (raw quadratic variation, the un-annualised counterpart to `HistoricalVolatility`), `RollingQuantile`, `RollingIqr`, `RollingPercentileRank`, `SpreadAr1Coefficient` (pairwise AR(1) rho of the spread; complements `OuHalfLife`).

**Price Action (4)** — `CloseVsOpen`, `BodySizePct`, `WickRatio`, `HighLowRange` (stateless per-bar OHLC transforms).

**Regime / Trend / Jump labels (3)** — `TrendLabel` (sign of the rolling OLS slope), `JumpIndicator` (return outliers vs trailing volatility, measured as deviation from the trailing mean so steady drift is not flagged), `RegimeLabel` (volatility-quantile regime split).

**Risk / Performance (2)** — `WinRate`, `Expectancy` (R-multiple).

**Microstructure (4)** — `OrderFlowImbalance` (Cont-Kukanov-Stoikov OFI), `Vpin`, `AmihudIlliquidity`, `RollMeasure`. These reuse the existing `OrderBook` / `Trade` inputs (no new input type).

## Intentionally NOT added (already present, would be duplicates)

- **Population skew / kurtosis** — `skewness.rs` / `kurtosis.rs` are already population moments (divisor n).
- **Hurst R/S** — `hurst_exponent.rs` already uses rescaled-range (R/S) analysis.
- **Queue Imbalance** — exactly `OrderBookImbalanceTop1` ((bidSize - askSize) / (bidSize + askSize)).

## Verification

`cargo test -p wickra-core` (lib 3187 + doc 354), `cargo clippy --workspace --all-targets --all-features -D warnings` clean, node `npm run build && npm test` (471), python `pytest` (784). Counter consistent across `mod.rs`, lib block, README, and docs/README at 396.

fuzz/fuzz_targets/indicator_update.rs

@@ -14,9 +14,7 @@
 //! `Ema(20)`. This target now covers every scalar indicator in the catalogue.
 
 use libfuzzer_sys::fuzz_target;
-use wickra_core::{
-AdaptiveCycle, Alma, AnchoredRsi, Apo, Autocorrelation, AverageDrawdown, BatchExt, Beta, BollingerBands, CalmarRatio, CenterOfGravity, Cfo, Cmo, CoefficientOfVariation, ConditionalValueAtRisk, ConnorsRsi, Coppock, CyberneticCycle, Decycler, DecyclerOscillator, Dema, DetrendedStdDev, DoubleBollinger, Dpo, DrawdownDuration, EhlersStochastic, ElderImpulse, Ema, EmpiricalModeDecomposition, Fama, FisherTransform, Frama, GainLossRatio, HilbertDominantCycle, HistoricalVolatility, Hma, HtDcPhase, HtPhasor, HtTrendMode, HurstExponent, Indicator, InstantaneousTrendline, InverseFisherTransform, Jma, Kama, KellyCriterion, Kst, Kurtosis, LaguerreRsi, LinRegAngle, LinRegChannel, LinRegIntercept, LinRegSlope, LinearRegression, MaEnvelope, MaType, MacdExt, MacdFix, MacdIndicator, Mama, MaxDrawdown, McGinleyDynamic, MedianAbsoluteDeviation, MidPoint, Mom, OmegaRatio, PainIndex, PearsonCorrelation, PercentageTrailingStop, Pmo, Ppo, ProfitFactor, RSquared, RecoveryFactor, RenkoTrailingStop, Roc, Rocp, Rocr, Rocr100, RoofingFilter, Rsi, RviVolatility, SharpeRatio, SineWave, Skewness, Sma, Smma, SortinoRatio, SpearmanCorrelation, StandardError, StandardErrorBands, Stc, StdDev, StepTrailingStop, StochRsi, SuperSmoother, Tema, Tii, Trima, Trix, Tsf, Tsi, UlcerIndex, ValueAtRisk, Variance, VerticalHorizontalFilter, Vidya, Wma, ZScore, ZeroLagMacd, Zlema, T3
-};
+use wickra_core::{AdaptiveCycle, Alma, AnchoredRsi, Apo, Autocorrelation, AverageDrawdown, BatchExt, Beta, BollingerBands, CalmarRatio, CenterOfGravity, Cfo, Cmo, CoefficientOfVariation, ConditionalValueAtRisk, ConnorsRsi, Coppock, CyberneticCycle, Decycler, DecyclerOscillator, Dema, DetrendedStdDev, DoubleBollinger, Dpo, DrawdownDuration, EhlersStochastic, ElderImpulse, Ema, EmpiricalModeDecomposition, Expectancy, Fama, FisherTransform, Frama, GainLossRatio, HilbertDominantCycle, HistoricalVolatility, Hma, HtDcPhase, HtPhasor, HtTrendMode, HurstExponent, Indicator, InstantaneousTrendline, InverseFisherTransform, Jma, JumpIndicator, Kama, KellyCriterion, Kst, Kurtosis, LaguerreRsi, LinRegAngle, LinRegChannel, LinRegIntercept, LinRegSlope, LinearRegression, LogReturn, MaEnvelope, MaType, MacdExt, MacdFix, MacdIndicator, Mama, MaxDrawdown, McGinleyDynamic, MedianAbsoluteDeviation, MidPoint, Mom, OmegaRatio, PainIndex, PearsonCorrelation, PercentageTrailingStop, Pmo, Ppo, ProfitFactor, RSquared, RealizedVolatility, RecoveryFactor, RegimeLabel, RenkoTrailingStop, Roc, Rocp, Rocr, Rocr100, RollingIqr, RollingPercentileRank, RollingQuantile, RoofingFilter, Rsi, RviVolatility, SharpeRatio, SineWave, Skewness, Sma, Smma, SortinoRatio, SpearmanCorrelation, StandardError, StandardErrorBands, Stc, StdDev, StepTrailingStop, StochRsi, SuperSmoother, Tema, Tii, TrendLabel, Trima, Trix, Tsf, Tsi, UlcerIndex, ValueAtRisk, Variance, VerticalHorizontalFilter, Vidya, WinRate, Wma, ZScore, ZeroLagMacd, Zlema, T3};
 
 /// Drive a single streaming + batch run through one scalar indicator. Marked
 /// `#[inline(never)]` so a panic backtrace pin-points the specific indicator.
@@ -96,6 +94,14 @@ fuzz_target!(|data: Vec<f64>| {
     // HurstExponent needs `period >= 2 * chunks`; 16/4 is the cheapest fit
     // that still exercises every code path.
     drive(|| HurstExponent::new(16, 4).unwrap(), &data);
+    drive(|| LogReturn::new(1).unwrap(), &data);
+    drive(|| RealizedVolatility::new(20).unwrap(), &data);
+    drive(|| RollingQuantile::new(20, 0.5).unwrap(), &data);
+    drive(|| RollingIqr::new(14).unwrap(), &data);
+    drive(|| RollingPercentileRank::new(14).unwrap(), &data);
+    drive(|| TrendLabel::new(14).unwrap(), &data);
+    drive(|| JumpIndicator::new(20, 3.0).unwrap(), &data);
+    drive(|| RegimeLabel::new(5, 20).unwrap(), &data);
     drive(|| RviVolatility::new(10).unwrap(), &data);
     drive(|| LaguerreRsi::new(0.5).unwrap(), &data);
     drive(|| ConnorsRsi::classic(), &data);
@@ -157,6 +163,8 @@ fuzz_target!(|data: Vec<f64>| {
     drive(|| ProfitFactor::new(20).unwrap(), &data);
     drive(|| GainLossRatio::new(20).unwrap(), &data);
     drive(|| KellyCriterion::new(20).unwrap(), &data);
+    drive(|| WinRate::new(20).unwrap(), &data);
+    drive(|| Expectancy::new(20).unwrap(), &data);
 
     // RecoveryFactor and DrawdownDuration produce non-`f64` outputs / have
     // no `period` knob, so they cannot use the `drive` helper directly.