Day-of-Week Profile

Mean bar return for each weekday (Monday 0 through Sunday 6). Each bar's simple return is averaged into the bucket of its local weekday.

Quick reference

Item	Value
Family	Seasonality & Session
Input type	Candle (uses close, timestamp)
Output type	DayOfWeekProfileOutput { bins } (length 7)
Output range	unbounded per bin (typically small)
Default parameters	utc_offset_minutes = 0 (UTC)
Warmup period	2
Interpretation	Weekday return seasonality

Formula

weekday = local weekday of bar t (Mon=0 .. Sun=6)
ret_t   = close_t / close_{t-1} - 1
bins[w] = mean of ret over bars whose weekday == w   (0.0 if empty)

See crates/wickra-core/src/indicators/day_of_week_profile.rs.

Parameters

Name	Type	Default	Constraint	Source	Description
utc_offset_minutes	i32	0	none	day_of_week_profile.rs:39	Shifts the instant before deriving the weekday.

DayOfWeekProfile::new is infallible. There are always 7 buckets.

Inputs / Outputs

const _: fn(&mut wickra::DayOfWeekProfile, wickra::Candle) -> Option<wickra::DayOfWeekProfileOutput> =
    <wickra::DayOfWeekProfile as wickra::Indicator>::update;

• Python. update((o,h,l,c,v,ts)) → length-7 ndarray (or None); batch(...) → (n, 7) array, warmup rows NaN.
• Node. update(...) → number[] (or null); batch(...) → flat number[] length n*7.
• WASM. update(...) → Float64Array (or null).

Warmup

warmup_period() == 2. The first bar produces no output (no return yet).

Edge cases

• Buckets by weekday — 1970-01-02 (Friday) lands in bin 4 (test buckets_by_weekday).
• Averages the same weekday across weeks (test averages_same_weekday_across_weeks).
• Zero prior close uses a 0.0 return (test zero_prev_close_uses_zero_return).
• Reset clears all 7 buckets (test reset_clears_state).

Examples

Rust

use wickra::{Candle, Indicator, DayOfWeekProfile};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let day = 24 * 3_600_000;
    let mut prof = DayOfWeekProfile::new(0);
    prof.update(Candle::new(100.0, 100.0, 100.0, 100.0, 1.0, 0)?);          // Thu, no return
    let out = prof.update(Candle::new(101.0, 101.0, 101.0, 101.0, 1.0, day)?).unwrap();
    println!("{}", out.bins[4]); // 0.01 (Friday)
    Ok(())
}

Python

import wickra as ta

DAY = 24 * 3_600_000
prof = ta.DayOfWeekProfile(0)
prof.update((100.0, 100.0, 100.0, 100.0, 1.0, 0))
out = prof.update((101.0, 101.0, 101.0, 101.0, 1.0, DAY))
print(out[4])  # Friday mean return

Node

const wickra = require('wickra');
const DAY = 24 * 3_600_000;
const prof = new wickra.DayOfWeekProfile(0);
prof.update(100, 100, 100, 100, 1, 0);
console.log(prof.update(101, 101, 101, 101, 1, DAY)[4]); // Friday

Streaming

prof = ta.DayOfWeekProfile(0)
for o, h, l, c, v, ts in daily_candle_feed:
    curve = prof.update((o, h, l, c, v, ts))
    # curve[0]=Monday .. curve[6]=Sunday running mean returns

Interpretation

1. Weekday anomalies. Captures classic effects like the "Monday effect"; a persistently negative Monday bin or strong Friday bin informs calendar filters.
2. Crypto weekend regime. For 24/7 instruments the weekend bins (5, 6) often differ markedly from weekdays.

Common pitfalls

• Weekday is by local clock. Set utc_offset_minutes to the venue's clock so late-session bars don't roll into the next weekday.
• Few samples per weekday early on. Each weekday occurs once per week, so the profile needs many weeks to stabilise.

See also

• TimeOfDayReturnProfile — intraday seasonality.
• TurnOfMonth — monthly anomaly.
• Indicators-Overview — full taxonomy.