F&O / Seasonality
Seasonality Analysis
Explore how the selected underlying historically moved by calendar month and day of week across the available NSE archive.
No stored history for BANKNIFTY yet. Run `python manage.py build_seasonality_history --symbol BANKNIFTY` once to build it from NSE's archive (it takes a few minutes); the page reads the stored series.
Historical use
How to read this page
Descriptive-use disclosure
- Not a prediction and not advice. An average return for a past month or weekday is not a forecast of what the next one will do, and nothing here suggests entering, avoiding, or timing a position around any month or day. Past price moves are a record of what the market did, not evidence of what it will do.
- Small samples, named plainly. A calendar-month figure is averaged across however many years of that month the archive holds -- often two or three, not dozens -- and a day-of-week figure across however many occurrences fell in the window. Every stat below carries its own sample size; one built from a single observation is not a statistical pattern, and the count next to it says so.
- Not a strategy. There are no positions, no P&L and no structure here -- just this underlying's own historical daily closes, the same figures the Historical Chain viewer and the backtest engine already read off NSE's archive.
Methodology
How these averages are built
Source and window
NSE F&O end-of-day archive. The stored daily close series spans the available window shown above; no live quote is needed to display these historical results.
Returns and aggregation
Day-over-day returns use consecutive published closes. Calendar-month returns compound those daily changes before averaging the same month across years; weekdays average each occurrence.
Incomplete months
An unfinished trailing month is omitted from its own monthly average. Every value retains its sample count, and historical averages do not establish future outcomes.