VWAP

easyTradingacceptance —~15 min

Implement vwap(bars) — the session volume-weighted average price. Each bar is [high, low, close, volume]; use the typical price (high + low + close) / 3 for the bar and weight it by the bar's volume: Σ typical·volume / Σ volume.

VWAP is the benchmark every execution desk is measured against, and the line this site once drew wrong — the confession is at /learn/broken-vwap. Return the price rounded to 4 decimal places.

example 1

input

bars=[[101.0, 99.0, 100.0, 1000.0], [102.0, 100.0, 101.0, 1000.0], [103.0, 101.0, 102.0, 1000.0]]

output

example 2

input

bars=[[101.0, 99.0, 100.0, 3000.0], [102.0, 100.0, 101.0, 1000.0], [103.0, 101.0, 102.0, 500.0]]

output

100.4444

note

Three times the volume traded at the low bar — the VWAP has to sit lower than the plain average.

constraints

1 ≤ len(bars) ≤ 390
total volume > 0

teacher · 3 hints · the first is free

↗ read the theory

the chapter this problem is cut from

●solution.py· utf-8 · spaces:4

def vwap(bars: list) -> float:
    """Session VWAP from [high, low, close, volume] bars, rounded to 4 dp."""
    total = 0.0
    for h, l, c, v in bars:
        total += (h + l + c) / 3
    # TODO: weight each bar by its volume — this is a plain average, not a VWAP
    return round(total / len(bars), 4)

ln 1, col 1tab indent · esc leave editor

python 3.13 · pyodide

+ 6 hidden on submit

input · keyword arguments to vwap()

bars=[[101.0, 99.0, 100.0, 1000.0], [102.0, 100.0, 101.0, 1000.0], [103.0, 101.0, 102.0, 1000.0]]

expected

the judge calls vwap() with exactly these inputs · outputs are compared to 6 decimal places

● standing bypython 3.13 in your browser · pyodide 0.28.3 · judged on the server to 6 dp⌘↵ run · ⌘⇧↵ submit

paper only · educational · not advice