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

Analysis code was generated by an AI model up to 25 times, run in a sandbox against real MNQ 1-minute bars from 2026-03-04 to 2026-09-06, and reviewed automatically. Attempts that computed the same set of measures were grouped, and the figures shown are the median of the largest group. Agreement between attempts lowers the chance of a one-off coding slip; it does not prove the code matches the question, so the exact code is shown below.

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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 by an AI model up to 25 times, run in a sandbox, and reviewed automatically; the figures above are the median of the largest group of attempts that computed the same measures. Agreement between attempts lowers the chance of a one-off coding slip -- it does not prove the code matches the question, so check the definition and code. A one-off calculation, not 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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