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Seasonality · registered 2026-09-05

Early session of the month — what happened next

The answer

The sample holds 64,533 events on 356 dates. Once same-day clustering is accounted for, that is 9,638 effective observations. The condition was followed by a higher close in 45.1% of cases. The horizon is 5 trading days. For a matched market control on the same dates, the figure was 43.4%. That is a gap of +1.8pp, more often than the control. Its 95% interval is +0.6 to +3.0pp.

≥300 effective observations and the same sign in both halves of the period. Enough to report, but not enough to lead with. How grades are decided.

Moderate sampleData through 2026-08-06.
Past events across many stocks are counted and compared with a matched market control. Uncertainty sits beside each figure. These frequencies do not predict the next event or recommend a security. All price data is at least 30 days old.
Gap versus a matched market control, 5 trading days
+1.8pp
95% interval +0.6 to +3.0pp
Observed 45.1%Matched control 43.4%Needed to cover charges 55.6%

In plain English. The third trading session of a calendar month, for a stock trading above its hundred-day average price.

t is the third trading session of its calendar month (session_offset = 2)
AND close[t] > sma(close, 100)[t]

Written down on 5 September 2026, before it was measured. The headline uses the middle setting chosen in advance: the third trading session of the month and a 100-day average price. See the registration log.

The sample this rests on

The sample

Events64,533raw count
Effective observations9,638design effect 6.70
Distinct securities2,189
Distinct dates356
What the count is worth. The same events are counted under two designs. Without a control, everything that fired on one day shares one market move. With a control, that shared move is differenced away.
DesignSame-day correlationDesign effectEffective observations
Raw rate, no control0.12723.932,697
Paired against the control (published)0.0326.709,638
Period2011-10-05 to 2026-08-05
Mean events per date181.3
Smallest gap this sample can resolve+1.4pp
Censored observations1.7%
Largest share in one quarter4.2%
Largest share from one security0.2%
Largest share from one sectornot available
Controls drawn per event16.6
Control match qualityrung 0: 20.8% · rung 1: 34.8% · rung 2: 27.4% · rung 3: 13.9% · rung 4: 3.2%

The public daily bhavcopy has no sector data for past dates. So the sector-concentration check could not be run, and there is no sector-matched version. A pattern that is really a whole sector moving together would not be caught by this sample. What that means.

Every horizon, with its control

Every horizon, with its control and its interval. The last column is the frequency the same bracket would need just to cover published charges. That is arithmetic on the charge schedule. It is not a claim about the future.
Trading daysObservedMatched controlGap95% intervalMedian changeExcess medianBreak-even at 2%
141.9%40.9%+1.1pp0.0 to +2.2pp−0.34%−0.02%55.6%
345.4%44.2%+1.2pp+0.2 to +2.4pp−0.35%+0.06%55.6%
545.1%43.4%+1.8pp+0.6 to +3.0pp−0.50%+0.02%55.6%
1047.5%45.3%+2.1pp+0.4 to +3.6pp−0.39%+0.21%55.6%
2049.7%46.5%+3.2pp+1.8 to +4.3pp−0.05%+0.64%55.6%

The distribution is the answer

Where the 5-day change landed — the condition against its matched control
−15.5%0+17.0%
After the conditionMatched control| Vertical line: the eligible-universe median over the same window
Historical distribution across 64,533 events (9,638 effective observations), 2011-10-05 to 2026-08-05. Matched market control shown for comparison. Past frequencies are not a forecast.
The distribution is the answer. A 54% frequency with a 10th percentile of −11% is a different fact from one with a 10th percentile of −2%.
Daysp10p25Medianp75p90Trimmed meanBest point reachedWorst point reached
1−2.9%−1.6%−0.34%+1.0%+2.7%−0.20%+1.3%−1.5%
3−4.8%−2.6%−0.35%+2.1%+5.3%+0.02%+2.5%−2.6%
5−6.6%−3.4%−0.50%+2.6%+6.8%−0.15%+3.2%−3.4%
10−8.7%−4.5%−0.39%+4.3%+10.2%+0.32%+4.8%−4.7%
20−11.7%−6.0%−0.05%+6.9%+15.4%+1.15%+7.0%−6.8%

Year by year, and by market state

Year by year. An effect that exists in only a few years is a regime, not a base rate. It is published as that.
Year2011201220132014201520162017201820192020202120222023202420252026
Gap+1.1pp+5.6pp+2.2pp−3.8pp+1.0pp+3.9pp+1.5pp−1.2pp+0.2pp−2.5pp+2.9pp+2.1pp+2.9pp+2.9pp−0.4pp+5.4pp
Effective n673663014624063894834244195198659407441,547999631
Six market states come from two splits. The first is whether the eligible-universe reference line was above or below its 200-day average on the event date. That is a trailing average, known on the day. The second is where that day’s volatility sat across the whole sample period. The volatility band is a full-sample label. It is used only to slice these results, never to select an event, and it is what makes the six cells comparable across fifteen years.
Market vs its 200-day averageVolatilityGapEffective n
Abovelowest third−10.2pp31
Abovehighest third−2.7pp269
Belowlowest third+3.5pp2,425
Belowmiddle third+1.4pp3,601
Belowhighest third+1.6pp3,285

Robustness

Does it survive being pushed?

This is one of 25 pre-registered variants of this pattern. It is also one of 1,125 tests on this site. The figures below are adjusted for that.

First half of the period+1.0ppSplit at the median event date.
Second half of the period+2.5pp
Same sign in both halvesyesAn effect present in only one half is a regime, not a base rate.
Years with the same sign12 of 16
Non-overlapping subsample+1.8ppOne event per security per window, so no two observations share days.
After published charges+2.0ppA move counts only if it cleared the round-trip charge.
Censoring worst case+1.1ppEvery censored observation counted as a loss.
Median across the parameter grid+1.4ppThe headline sits far from the grid median — flagged as a knife edge.
Entering one session later+1.7ppA multi-session pattern survives it. An artefact of the entry bar does not.
Placebo: same securities, unrelated dates+0.9ppShould be near zero. If it is not, the method itself is creating a gap.
Sector-matched variantnot availableSector classification is not reconstructible point-in-time from the public bhavcopy.
Multiple-testing adjusted p0.0018Survives the false-discovery adjustment.
The whole declared grid, not just the centre — session offset down, ma length across
session offset2050100150200
0−1.0pp−0.2pp+0.5pp+0.8pp+0.8pp
1−0.7pp+0.4pp+1.4pp+1.7pp+1.7pp
2+0.1pp+0.9pp+1.8pp+1.7pp+1.7pp
3−0.4pp+0.4pp+1.5pp+1.6pp+1.8pp
4+0.4pp+1.8pp+2.8pp+2.9pp+3.0pp

A real pattern is a plateau across neighbouring settings. A single bright cell in a field of noise is an artefact of one threshold. The outlined cell is the pre-declared centre. The headline is taken from that cell whether or not it is the strongest.

The quality checks

Every quality check, and what this sample measured against it. If a sample fails any one of them, no rate is shown, however large the sample is.
CheckRequiredThis sampleResult
Effective sample size>= 1009638passed
Distinct event dates>= 60356passed
Distinct securities>= 252189passed
Calendar span>= 5 years14.8 yearspassed
Largest share in one quarter<= 20.0%4.2%passed
Largest share from one security<= 5.0%0.2%passed
Censoring rate<= 2.0%1.7%passed
Events on relaxation rung 3-4<= 20.0%17.0%passed

What this does not tell you

  • It does not tell you what happens next. A base rate describes a sample of past events. The future is not drawn from that sample.
  • It does not identify any security. These figures are aggregates across hundreds of securities over many years. No individual security's behaviour can be inferred from them.
  • It does not account for your costs, your position size or your taxes. It also does not account for your ability to sit through the losses. The break-even column shows the frequency required to cover published charges alone. It excludes slippage, impact, and everything specific to you.
  • A gap versus the control is not an edge. It is an observation about a sample, measured with uncertainty. That observation may not persist.
  • The interval matters more than the number. Where the interval includes zero, this sample does not distinguish the pattern from the market.
  • Sample size is not what it looks like. Events on the same day are not independent observations. Use the effective sample size shown above.

Questions about this page

What is the matched control, and why does every number have one?

For every event, comparable securities were drawn from the same date — same price band, same realised-volatility band, same traded-value band — that did not themselves meet the condition. The Indian market rose in roughly two of every three rolling twenty-day windows over this period, so any long-side pattern shows a frequency near 60% and means nothing on its own. The publishable number is the gap between the two, not either one.

Why is the effective sample smaller than the number of events?

Events on the same day are not independent observations. They share one market move. Effective sample size accounts for that link. Each interval and check uses it instead of the raw count.

Does this tell me what will happen next time?

No. These figures count past events in a sample, with uncertainty beside each result. They do not predict the next event or recommend a security.

Would this have covered costs?

The break-even column shows the frequency a symmetric 2% target and stop would need just to cover published charges. On this page that level is 55.6%, against an observed 45.1%. It excludes slippage, impact and anything specific to you, all of which move it the wrong way.

What the terms mean · Work out the frequency your own bracket needs

Next step

How this figure was produced

The point-in-time universe, the matched control drawn from the same dates, the interval, and the quality checks a sample must pass before any rate is shown.

Read the methodology

Source. NSE daily bhavcopy. Data through 2026-08-06. Stock list: point-in-time, as it stood on each date. Measured on 2026-09-05. How it is measured · What the terms mean · Download these figures, under the CC BY 4.0 licence.

These are past frequencies. They are not a forecast, and not advice.