STC

Doug Schaff's Trend Cycle — a doubly-Stochastic-smoothed MACD that produces a bounded [0, 100] reading reacting faster than MACD itself.

Quick reference

Field	Value
Family	Price Oscillators
Input type	f64 (single close)
Output type	f64
Output range	[0, 100] (clamped)
Default parameters	fast = 23, slow = 50, schaff_period = 10, factor = 0.5
Warmup period	slow + 2 · (schaff_period − 1) (68 for defaults)
Interpretation	Cross above 25 = bullish entry; cross below 75 = bearish exit.

Formula

macd_t  = EMA(close, fast)_t − EMA(close, slow)_t
%K_t    = 100 · (macd − LL(macd, schaff_period)) / (HH(macd, schaff_period) − LL(macd, schaff_period))
%D_t    = %D_{t-1} + factor · (%K_t − %D_{t-1})       // half-EMA when factor = 0.5
%K2_t   = 100 · (%D − LL(%D, schaff_period)) / (HH(%D, schaff_period) − LL(%D, schaff_period))
STC_t   = STC_{t-1} + factor · (%K2_t − STC_{t-1})

STC runs a stochastic over the MACD, smooths it (%D), runs a second stochastic over that, and smooths again — two min/max normalisations plus two half-EMA passes. The output is clamped to [0, 100] to absorb floating-point rounding. Each stochastic stage returns 0 when its rolling range collapses (flat input or a strictly monotone trend where the MACD settles into a constant lag), so degenerate series produce a deterministic 0 rather than NaN / ±inf.

Parameters

Name	Type	Default	Constraint	Source
fast	usize	23	>= 1, < slow	Stc::new (stc.rs:56)
slow	usize	50	>= 1, > fast	stc.rs:56
schaff_period	usize	10	>= 1	stc.rs:56
factor	f64	0.5	finite, (0, 1]	stc.rs:65

Any zero period returns [Error::PeriodZero]; fast >= slow or a factor outside (0, 1] returns [Error::InvalidPeriod]. Stc::classic() returns (23, 50, 10, 0.5). Python defaults come from the pyo3 signature; the Node constructor takes all four arguments explicitly. The public class is STC in both bindings.

Inputs / Outputs

use wickra::{Indicator, Stc};
// Stc: Input = f64, Output = f64
const _: fn(&mut Stc, f64) -> Option<f64> = <Stc as Indicator>::update;

A single f64 close in, an Option<f64> out in [0, 100]. Python maps this to float | None / a float64 np.ndarray with NaN warmup; Node to number | null / Array<number>.

Warmup

warmup_period() returns slow + 2 · (schaff_period − 1). The slow EMA emits at slow inputs; the first stochastic's window then needs schaff_period − 1 more inputs to fill, and the second stochastic's window another schaff_period − 1 after that. For the defaults that is 50 + 2·9 = 68. Pinned by warmup_emits_first_value_at_warmup_period ((2, 4, 3, 0.5) → warmup 8: inputs 1–7 return None, input 8 emits).

Edge cases

• Constant / monotone series. Both stochastic ranges collapse, so STC settles deterministically at 0 (test constant_series_yields_zero).
• Bounded output. STC is always within [0, 100] regardless of input (test output_is_bounded).
• Full-range cycling. A sufficiently strong oscillation drives STC across the whole [0, 100] band (test oscillating_series_visits_full_range).
• Reset. reset() clears both EMAs, both rolling windows, and the two smoothing accumulators.

Examples

Rust

use wickra::{BatchExt, Indicator, Stc};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let prices: Vec<f64> = (0..400)
        .map(|i| 100.0 + (f64::from(i) * 0.15).sin() * 30.0)
        .collect();
    let mut stc = Stc::classic(); // (23, 50, 10, 0.5)
    for v in stc.batch(&prices).into_iter().flatten() {
        assert!((0.0..=100.0).contains(&v));
    }
    Ok(())
}

Python

import numpy as np
import wickra as ta

stc = ta.STC(23, 50, 10, 0.5)
out = stc.batch(prices)  # 1-D series in [0, 100], NaN for the first 67 rows

Node

const ta = require('wickra');
const stc = new ta.STC(23, 50, 10, 0.5);
const v = stc.update(101.5); // null during warmup, else a value in [0, 100]

Interpretation

STC is a faster, bounded reinterpretation of MACD:

1. Overbought / oversold. Like a stochastic, readings near 100 are overbought, near 0 oversold. Schaff's signal lines are 25 and 75.
2. Cycle turns. A cross up through 25 flags a new up-cycle (bullish entry); a cross down through 75 flags a down-cycle (bearish exit/entry). Because of the double smoothing, STC turns earlier than raw MACD while filtering more of its whipsaw.

Common pitfalls

• Reading the long warmup wrong. Two stochastic windows stack on top of the slow EMA, so STC needs slow + 2·(schaff_period − 1) bars — much longer than the slow period alone.
• Expecting MACD-like unbounded values. STC is normalised to [0, 100]; its magnitude reflects cycle position, not momentum size.

References

• Doug Schaff, Schaff Trend Cycle (late 1990s, FX Studies). Widely described in Technical Analysis of Stocks & Commodities coverage of the indicator.

See also

• MacdIndicator — the unsmoothed source signal.
• Stochastic — the normalisation STC applies twice.
• StochRsi — another double-normalised oscillator.