The original taxonomy was four classical families plus a statistics group, with the F1-F12 expansion slotted in as sub-categories. This regroups the whole 71-indicator catalogue into eight top-level families, each with at least five members: Moving Averages (12), Momentum Oscillators (13), Trend & Directional (9), Price Oscillators (5), Volatility & Bands (12), Trailing Stops (5), Volume (9), Price Statistics (7). - Wiki: docs/wiki/indicators/ reorganised into eight family folders; all 71 indicator pages moved with `git mv`. Every internal cross-link is normalised to `../<family>/Indicator-X.md`, each page's `Family` field is set to its new family, and two pre-existing `../Indicator-Chaining.md` links (should have been `../../`) are corrected. A link check confirms every relative wiki link resolves. - Indicators-Overview.md fully rewritten around the eight families; Home.md indicator reference and the README family table follow suit. - Warmup-Periods.md gains the eight F13 indicators; CHANGELOG records the 46-indicator expansion (25 -> 71) and the eight-family taxonomy. - Tests: Node indicators.test.js and Python test_new_indicators.py cover all eight new indicators (Node 91/91, Python 117/117 green). cargo fmt + clippy (core/wickra/data/wasm/node) clean; 508 core tests, 25 data tests and 74 doctests green.
4.8 KiB
UlcerIndex
Ulcer Index — Peter Martin's downside-only risk measure: the root-mean-square of recent drawdowns.
Quick reference
| Field | Value |
|---|---|
| Family | Volatility & Bands |
| Input type | f64 (single close) |
| Output type | f64 |
| Output range | [0, ∞) (percent) |
| Default parameters | period = 14 (Python) |
| Warmup period | 2·period − 1 |
| Interpretation | Depth and duration of drawdowns; 0 means no drawdown at all. |
Formula
max_t = highest price over the trailing `period` bars
drawdown_t = 100 · (price_t − max_t) / max_t
UlcerIndex = √( mean( drawdown² over period ) )
Standard deviation treats an up-move and a down-move as equally
"volatile". The Ulcer Index measures only the pain of being underwater:
for each bar it takes the percentage drop from the trailing high, squares
it, and reports the root-mean-square. A market that only rises has no
drawdown and an Ulcer Index of 0; the deeper and longer the drawdowns,
the higher the reading. It is the volatility term in the Martin ratio
(Ulcer Performance Index).
Parameters
| Name | Type | Default | Valid range | Description |
|---|---|---|---|---|
period |
usize |
14 (Python) |
>= 1 |
Look-back for both the trailing high and the RMS window. 0 errors with Error::PeriodZero. |
The Python binding defaults period to 14.
Inputs / Outputs
From crates/wickra-core/src/indicators/ulcer_index.rs:
impl Indicator for UlcerIndex {
type Input = f64;
type Output = f64;
// update(&mut self, input: f64) -> Option<f64>
}
A single f64 close in, an Option<f64> out. Python maps this to
float | None / numpy.ndarray (NaN warmup); Node to number | null /
Array<number> (NaN warmup).
Warmup
UlcerIndex::new(period).warmup_period() == 2·period − 1. The first
period prices fill the trailing-maximum window; the per-bar squared
drawdown then needs another period − 1 bars to fill the RMS window.
Edge cases
- Pure up-trend. Price never trades below its own running high, so
every drawdown — and the Ulcer Index — is
0(pure_uptrend_yields_zeropins this). - Constant series. A flat series has no drawdown; the output is
0.0(constant_series_yields_zeropins this). - Non-negative. The Ulcer Index is an RMS of real numbers and is
never negative (
output_is_non_negativepins this). - NaN / infinity inputs. Non-finite inputs are silently dropped.
- Reset.
ui.reset()clears both rolling windows and the sum.
Examples
Rust
use wickra::{BatchExt, Indicator, UlcerIndex};
fn main() -> Result<(), Box<dyn std::error::Error>> {
let mut ui = UlcerIndex::new(2)?;
let out: Vec<Option<f64>> = ui.batch(&[10.0, 8.0, 12.0, 9.0]);
println!("{:?}", out);
Ok(())
}
Output:
[None, None, Some(14.142135623730951), Some(17.67766952966369)]
UlcerIndex(2) warms up after 3 bars. At bar 3 the squared drawdowns in
the window are [400, 0], so the index is √(400/2) = √200. At bar 4
they are [0, 625], giving √(625/2) = √312.5. This matches the
reference_values test in
crates/wickra-core/src/indicators/ulcer_index.rs.
Python
import numpy as np
import wickra as ta
ui = ta.UlcerIndex(2)
print(ui.batch(np.array([10.0, 8.0, 12.0, 9.0])))
Output:
[ nan nan 14.1421356 17.6776695]
Node
const ta = require('wickra');
const ui = new ta.UlcerIndex(2);
console.log(ui.batch([10, 8, 12, 9]));
Output:
[ NaN, NaN, 14.142135623730951, 17.67766952966369 ]
Interpretation
UlcerIndex answers "how uncomfortable has holding this been?" — a high
reading means deep or prolonged drawdowns, a low reading means a smooth
ride up. It is most useful for comparing instruments or strategies on a
downside-risk basis, and as the denominator of the Ulcer Performance
Index ((return − risk-free) / UlcerIndex), a Sharpe-ratio analogue that
penalises only downside volatility.
Common pitfalls
- Reading it as two-sided volatility. The Ulcer Index ignores upside
entirely — a wildly choppy up-trend can still score near
0. UseStdDevfor two-sided dispersion. - Forgetting the doubled warmup. Warmup is
2·period − 1, notperiod.
References
Peter Martin and Byron McCann, The Investor's Guide to Fidelity Funds (1989); the index is also documented at StockCharts. The trailing-high drawdown RMS here follows that definition.
See also
- Indicator-StdDev.md — two-sided dispersion.
- Indicator-Atr.md — per-bar range volatility.
- Indicators-Overview.md — the full taxonomy.