Data to 5 October 2026

Methods

Market breadth

Code: pipeline/tipsheet/compute/breadth.py, publish/breadth.py.

Bundles: markets/breadth/*.

Stock breadth

Index breadth

Equal weight vs cap weight

The 1-year total-return gap between the equal-weight and cap-weight index, in percentage points:

A positive gap means the typical stock beat the big ones.

Validation

We compared against BSE’s official daily advance/decline and 52-week high/low counts (via India Data Hub), 2015–2026, 2,810 days:

The two exchanges list different stocks, so perfect agreement isn’t expected.

Known limits

Participation level versus change (2026-10-05)

Reuse the existing daily liquid point-in-time stock universe and moving-average eligibility. For 20- and 200-session participation, subtract the reading exactly 21 and 63 market sessions earlier. Changes are percentage points, without filled missing inputs. Net new 52-week highs use those same lags, with changes in counts. History uses the existing 60-session median universe threshold.

Four descriptive states use 200-session participation: at least 50% is a majority above the average, below 50% a minority; a strictly positive 21-session change is rising participation, otherwise flat or falling. Missing inputs leave the state blank. Thresholds are not optimised forecasts. Stock entry, exit and changing eligibility affect these changes; this is not a fixed-stock cohort. Existing equal-weight/cap-weight comparisons remain alongside them.

The accompanying Nifty 500 total-return changes use the same two session endpoints, without forward filling. A positive index return alongside a negative participation change describes narrowing support for the index gain; it is not treated as a tested bearish signal.

This note is the repository file docs/methods/breadth.md, rendered as-is.