Event days · MYM
How does MYM's daily range on its 10 highest-volume days compare to a typical day
10
top10 count
n=1302026-03-05 to 2026-09-07
top10 count
10
top10 avg range
838.7
typical avg range
492.71
typical median range
456
ratio top10 to typical
1.7
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.
Show the code
bars_et = to_et(bars)
rth = rth_session(bars_et)
rth = rth.copy()
rth['trading_date'] = trading_date(rth)
daily = rth.groupby('trading_date').agg(high=('high','max'), low=('low','min'), volume=('volume','sum'))
daily['range'] = daily['high'] - daily['low']
daily = daily.dropna()
n = len(daily)
if n == 0:
result = {"sample_size": 0, "top10_avg_range": None, "typical_avg_range": None,
"typical_median_range": None, "ratio_top10_to_typical": None}
else:
top_n = min(10, n)
top10 = daily.sort_values('volume', ascending=False).head(top_n)
typical_avg = float(daily['range'].mean())
typical_median = float(daily['range'].median())
top10_avg = float(top10['range'].mean())
ratio = top10_avg / typical_avg if typical_avg != 0 else None
result = {
"sample_size": int(n),
"top10_count": int(top_n),
"top10_avg_range": round(top10_avg, 2),
"typical_avg_range": round(typical_avg, 2),
"typical_median_range": round(typical_median, 2),
"ratio_top10_to_typical": round(ratio, 3) if ratio is not None else 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.
Related
This is historical statistical information only. It is not investment advice, and past performance does not indicate future results. Trading involves risk of loss.