Ranges · MNQ

What is the distribution of MNQ's daily trading range

409.12

mean range

n=1302026-03-04 to 2026-09-06

mean range

409.12

median range

377.13

std range

210.43

min range

71.25

max range

1,619.75

p10 range

218.05

p25 range

285.69

p75 range

474.38

p90 range

644.65

p95 range

771.11

Methodology

Computed by independently generating and running analysis code against real MNQ 1-minute bars from 2026-03-04 to 2026-09-06, 25 separate times in parallel, then taking the answer the largest group of independent attempts agreed on. The exact code is shown below.

Show the code


bars_et = to_et(bars)
rth = rth_session(bars_et)
dates = trading_date(rth)

daily = rth.groupby(dates).agg(high=('high','max'), low=('low','min'))
daily_range = daily['high'] - daily['low']
daily_range = daily_range.dropna()

n = len(daily_range)

if n > 0:
    result = {
        "sample_size": int(n),
        "mean_range": float(daily_range.mean()),
        "median_range": float(daily_range.median()),
        "std_range": float(daily_range.std()) if n > 1 else 0.0,
        "min_range": float(daily_range.min()),
        "max_range": float(daily_range.max()),
        "p10_range": float(daily_range.quantile(0.10)),
        "p25_range": float(daily_range.quantile(0.25)),
        "p75_range": float(daily_range.quantile(0.75)),
        "p90_range": float(daily_range.quantile(0.90)),
        "p95_range": float(daily_range.quantile(0.95)),
    }
else:
    result = {
        "sample_size": 0,
        "mean_range": None,
        "median_range": None,
        "std_range": None,
        "min_range": None,
        "max_range": None,
        "p10_range": None,
        "p25_range": None,
        "p75_range": None,
        "p90_range": None,
        "p95_range": None,
    }

Generated and independently re-derived 25 times, then checked for logical consistency, before being shown to you -- the figures above are the answer the largest number of those independent attempts agreed on. Still a generated, one-off calculation, treat it as a rough, one-off analysis rather than a permanent fixture.

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This is historical statistical information only. It is not investment advice, and past performance does not indicate future results. Trading involves risk of loss.

What is the distribution of MNQ's daily trading range

Methodology

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