TQTradingQuery

Ranges · MYM

How does MYM's first-hour range compare to its full-session range

310.19

avg first hour range

n=1302026-03-05 to 2026-09-07

avg first hour range

310.19

avg full session range

492.71

avg ratio fh to full

0.68

median ratio fh to full

0.67

Methodology

Computed by independently generating and running analysis code against real MYM 1-minute bars from 2026-03-05 to 2026-09-07, 25 separate times in parallel, then taking the answer the largest group of independent attempts agreed on. The exact code is shown below.

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bars_et = to_et(bars)
rth = rth_session(bars_et)
rth = rth.copy()
rth['trading_date'] = trading_date(rth)

first_hour_mask = within_minutes_of_open(rth, 60)
fh = rth[first_hour_mask]

fh_range = fh.groupby('trading_date').agg(high=('high','max'), low=('low','min'))
fh_range['range'] = fh_range['high'] - fh_range['low']

full_range = rth.groupby('trading_date').agg(high=('high','max'), low=('low','min'))
full_range['range'] = full_range['high'] - full_range['low']

merged = fh_range[['range']].join(full_range[['range']], lsuffix='_fh', rsuffix='_full', how='inner')
merged = merged.dropna()

n = len(merged)
if n > 0:
    merged['ratio'] = merged['range_fh'] / merged['range_full']
    avg_fh_range = float(merged['range_fh'].mean())
    avg_full_range = float(merged['range_full'].mean())
    avg_ratio = float(merged['ratio'].mean())
    median_ratio = float(merged['ratio'].median())
else:
    avg_fh_range = None
    avg_full_range = None
    avg_ratio = None
    median_ratio = None

result = {
    'sample_size': int(n),
    'avg_first_hour_range': avg_fh_range,
    'avg_full_session_range': avg_full_range,
    'avg_ratio_fh_to_full': avg_ratio,
    'median_ratio_fh_to_full': median_ratio,
}
  • 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.