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Chandelier Exit

A trailing stop-loss indicator that dynamically adjusts with volatility. The long line sits at the highest high over the look-back period minus a multiple of ATR; the short line sits at the lowest low plus the same multiple. A close crossing below the long line, or above the short line, signals a potential trend reversal or exit.

Inputs: [high, low, close]  |  Options: [period, step]  |  Outputs: [long, short]

Basic

use tulip_rs::indicators::chandelierexit::indicator;

let high  = vec![82.15, 81.89, 83.03, 83.30, 83.85,
                 83.90, 83.33, 84.30, 84.84, 85.00,
                 85.90, 86.58, 86.98, 88.00, 87.87_f64];
let low   = vec![81.29, 80.64, 81.31, 82.65, 83.07,
                 83.11, 82.49, 82.30, 84.15, 84.11,
                 84.03, 85.39, 85.76, 87.17, 87.01_f64];
let close = vec![81.59, 81.06, 82.87, 83.00, 83.61,
                 83.15, 82.84, 83.99, 84.55, 84.36,
                 85.53, 86.54, 86.89, 87.77, 87.29_f64];

let inputs = [high.as_slice(), low.as_slice(), close.as_slice()];
// Options: [period, step]  — step is the ATR multiplier (default 2)
let (outputs, mut state) = indicator(&inputs, &[14.0, 2.0], None).unwrap();
println!("{:?}", outputs[0]); // long stop values
println!("{:?}", outputs[1]); // short stop values

// State continuation — feed new bars without reprocessing history
let new_high  = vec![88.50_f64];
let new_low   = vec![87.30_f64];
let new_close = vec![88.10_f64];
let continued = state.batch_indicator(
    &[new_high.as_slice(), new_low.as_slice(), new_close.as_slice()],
    None,
).unwrap();
println!("{:?}", continued[0]);

import numpy as np
import tulip_rs

high  = np.array([82.15, 81.89, 83.03, 83.30, 83.85,
                  83.90, 83.33, 84.30, 84.84, 85.00,
                  85.90, 86.58, 86.98, 88.00, 87.87], dtype=np.float64)
low   = np.array([81.29, 80.64, 81.31, 82.65, 83.07,
                  83.11, 82.49, 82.30, 84.15, 84.11,
                  84.03, 85.39, 85.76, 87.17, 87.01], dtype=np.float64)
close = np.array([81.59, 81.06, 82.87, 83.00, 83.61,
                  83.15, 82.84, 83.99, 84.55, 84.36,
                  85.53, 86.54, 86.89, 87.77, 87.29], dtype=np.float64)

outputs, state = tulip_rs.indicators.chandelierexit.indicator(
    [high, low, close], [14.0, 2.0]
)
print(outputs[0])  # long stop values
print(outputs[1])  # short stop values

# State continuation
new_high  = np.array([88.50], dtype=np.float64)
new_low   = np.array([87.30], dtype=np.float64)
new_close = np.array([88.10], dtype=np.float64)
continued = state.batch_indicator([new_high, new_low, new_close])
print(continued[0])

import * as ti from 'tulip-rs-node';

const high  = Float64Array.from([82.15, 81.89, 83.03, 83.30, 83.85, 83.90, 83.33, 84.30, 84.84, 85.00, 85.90, 86.58, 86.98, 88.00, 87.87]);
const low   = Float64Array.from([81.29, 80.64, 81.31, 82.65, 83.07, 83.11, 82.49, 82.30, 84.15, 84.11, 84.03, 85.39, 85.76, 87.17, 87.01]);
const close = Float64Array.from([81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36, 85.53, 86.54, 86.89, 87.77, 87.29]);

const [outputs, state] = ti.chandelierexit.indicator([high, low, close], [14, 2]);
console.log('Long stop:', outputs[0]);
console.log('Short stop:', outputs[1]);

// State continuation
const n = high.length - 5;
const [, state2] = ti.chandelierexit.indicator([high.slice(0, n), low.slice(0, n), close.slice(0, n)], [14, 2]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n), close.slice(n)]);
console.log('Continued long stop:', continued[0]);

import { init } from 'tulip-rs-wasm';
import * as ti from 'tulip-rs-wasm';

await init(); // bundler resolves the WASM asset automatically

const high  = [82.15, 81.89, 83.03, 83.30, 83.85, 83.90, 83.33, 84.30, 84.84, 85.00, 85.90, 86.58, 86.98, 88.00, 87.87];
const low   = [81.29, 80.64, 81.31, 82.65, 83.07, 83.11, 82.49, 82.30, 84.15, 84.11, 84.03, 85.39, 85.76, 87.17, 87.01];
const close = [81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36, 85.53, 86.54, 86.89, 87.77, 87.29];

const [outputs, state] = ti.chandelierexit.indicator([high, low, close], [14, 2]);
console.log('Long stop:', outputs[0]);
console.log('Short stop:', outputs[1]);

// State continuation
const n = high.length - 5;
const [, state2] = ti.chandelierexit.indicator([high.slice(0, n), low.slice(0, n), close.slice(0, n)], [14, 2]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n), close.slice(n)]);
console.log('Continued long stop:', continued[0]);

Optional Outputs

chandelierexit exposes 4 optional outputs: atr, tr, min, max. Pass a boolean mask as the third argument — one bool per optional output, in order.

use tulip_rs::indicators::chandelierexit::indicator;

let high  = vec![82.15, 81.89, 83.03, 83.30, 83.85, 83.90, 83.33, 84.30, 84.84, 85.00,
                 85.90, 86.58, 86.98, 88.00, 87.87_f64];
let low   = vec![81.29, 80.64, 81.31, 82.65, 83.07, 83.11, 82.49, 82.30, 84.15, 84.11,
                 84.03, 85.39, 85.76, 87.17, 87.01_f64];
let close = vec![81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36,
                 85.53, 86.54, 86.89, 87.77, 87.29_f64];

let mask = [true, true, false, false];
let (outputs, _state) = indicator(
    &[high.as_slice(), low.as_slice(), close.as_slice()],
    &[14.0, 2.0],
    Some(&mask),
).unwrap();

let long = &outputs[0]; // long (primary)
let short = &outputs[1]; // short (primary)
let atr  = &outputs[2]; // atr (optional — requested)
let tr   = &outputs[3]; // tr (optional — requested)
// min and max not requested — omitted from outputs

import numpy as np
import tulip_rs

high  = np.array([82.15, 81.89, 83.03, 83.30, 83.85, 83.90, 83.33, 84.30, 84.84, 85.00,
                  85.90, 86.58, 86.98, 88.00, 87.87], dtype=np.float64)
low   = np.array([81.29, 80.64, 81.31, 82.65, 83.07, 83.11, 82.49, 82.30, 84.15, 84.11,
                  84.03, 85.39, 85.76, 87.17, 87.01], dtype=np.float64)
close = np.array([81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36,
                  85.53, 86.54, 86.89, 87.77, 87.29], dtype=np.float64)

outputs, state = tulip_rs.indicators.chandelierexit.indicator(
    [high, low, close], [14.0, 2.0],
    optional_outputs=[True, True, False, False],
)

long  = outputs[0]  # long (primary)
short = outputs[1]  # short (primary)
atr   = outputs[2]  # atr (optional — requested)
tr    = outputs[3]  # tr (optional — requested)
# min and max not requested — omitted from outputs

chandelierexit exposes 4 optional outputs: atr, tr, min, max.

const [allOut] = ti.chandelierexit.indicator([high, low, close], [14, 2], [true, true, true, true]);
const long  = allOut[0]; // primary
const short = allOut[1]; // primary
const atr   = allOut[2]; // optional 0: atr
const tr    = allOut[3]; // optional 1: tr
const min   = allOut[4]; // optional 2: min (rolling lowest low)
const max   = allOut[5]; // optional 3: max (rolling highest high)

// Request only atr and tr
const [partial] = ti.chandelierexit.indicator([high, low, close], [14, 2], [true, true, false, false]);

The WASM API is identical to Node.js — pass the boolean mask as the third argument.

const [allOut] = ti.chandelierexit.indicator([high, low, close], [14, 2], [true, true, true, true]);
const long  = allOut[0]; // primary
const short = allOut[1]; // primary
const atr   = allOut[2]; // optional 0: atr
const tr    = allOut[3]; // optional 1: tr
const min   = allOut[4]; // optional 2: min (rolling lowest low)
const max   = allOut[5]; // optional 3: max (rolling highest high)

// Request only atr and tr
const [partial] = ti.chandelierexit.indicator([high, low, close], [14, 2], [true, true, false, false]);

SIMD

By assets — same options, N assets in parallel:

use tulip_rs::indicators::chandelierexit::indicator_by_assets;

let inputs: [&[&[f64]; 3]; 4] = [
    &[h1.as_slice(), l1.as_slice(), c1.as_slice()],
    &[h2.as_slice(), l2.as_slice(), c2.as_slice()],
    &[h3.as_slice(), l3.as_slice(), c3.as_slice()],
    &[h4.as_slice(), l4.as_slice(), c4.as_slice()],
];
let results = indicator_by_assets::<4>(&inputs, &[14.0, 2.0], None).unwrap();
for (i, asset_outputs) in results.iter().enumerate() {
    println!("Asset {}: long={:?}", i + 1, asset_outputs[0]);
}

By options — same asset, N option sets in parallel:

use tulip_rs::indicators::chandelierexit::indicator_by_options;

let opts: [&[f64; 2]; 4] = [&[10.0, 2.0], &[14.0, 2.0], &[20.0, 2.0], &[30.0, 3.0]];
let results = indicator_by_options::<4>(&inputs, &opts, None).unwrap();
for (i, out) in results.iter().enumerate() {
    println!("Period={} step={}: long={:?}", opts[i][0], opts[i][1], out[0]);
}

By assets — same options, N assets in parallel (must be 2, 4, 8, or 16):

simd_inputs = [
    [h1, l1, c1],
    [h2, l2, c2],
    [h3, l3, c3],
    [h4, l4, c4],
]
outputs_list, states = tulip_rs.indicators.chandelierexit.simd_by_assets(simd_inputs, [14.0, 2.0])
for i, asset_outputs in enumerate(outputs_list):
    print(f"Asset {i+1}: long={asset_outputs[0]}")

By options — same asset, N option sets in parallel:

simd_options = [[10.0, 2.0], [14.0, 2.0], [20.0, 2.0], [30.0, 3.0]]
outputs_list, states = tulip_rs.indicators.chandelierexit.simd_by_options(
    [high, low, close], simd_options
)
for i, out in enumerate(outputs_list):
    print(f"Period={simd_options[i][0]} step={simd_options[i][1]}: long={out[0]}")

By assets — same options applied to 4 assets in parallel:

const simdInputs = [
    [high.slice(), low.slice(), close.slice()],
    [high.map(v => v * 1.1), low.map(v => v * 1.1), close.map(v => v * 1.1)],
    [high.map(v => v * 0.9), low.map(v => v * 0.9), close.map(v => v * 0.9)],
    [high.map(v => v * 1.02), low.map(v => v * 1.02), close.map(v => v * 1.02)],
];
const [results] = ti.chandelierexit.simdByAssets(simdInputs, [14, 2]);
results.forEach((out, i) => console.log(`Asset ${i + 1}: long=`, out[0]));

By options — same asset, 4 different option sets in parallel:

const simdOptions = [[10, 2], [14, 2], [20, 2], [30, 3]];
const [results] = ti.chandelierexit.simdByOptions([high, low, close], simdOptions);
results.forEach((out, i) => console.log(`Period=${simdOptions[i][0]} step=${simdOptions[i][1]}: long=`, out[0]));