Screen
Research tool · not investment advice. Full disclaimer →
Screen
build a shortlist, share it as a linkSource: computed from NSE prices · accumulation · CPR · credibility.
A shortlist to study and never a buy list: liquid stocks ranked by how many independent pillars — momentum, accumulation, relative strength, structure — line up right now, each turned into a shape beside its raw numbers. Sort any column, filter it, and the URL becomes the screen you saved.
| Symbol | Sector? | Price (₹)? | From 52w high? | Surge 1m? | Wolfe | Wolfe quality | Accum score? | Accum state? | Confluence (0–6)? | Themes | Instrument | Rank in screen | vs own 1-mo |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 360ONE | Nifty Financial Services | 1,040.0 | -14.0% | 1.11× | Bull | 14 | -0.95 | Strong Distrib | 1 | — | — | 1.1× | |
| AADHARHFC | Nifty Financial Services | 448.4 | -19.4% | 1.69× | Bear | 19 | -0.77 | Strong Distrib | 0 | — | — | 1.7× | |
| AARTIIND | Nifty Chemicals | 465.1 | -14.4% | 0.84× | Bear | 20 | -0.87 | Strong Distrib | 2 | Chemicals | — | 0.8× | |
| ABB | Nifty Energy | 6,900.0 | -10.8% | 1.26× | Bull | 17 | -0.82 | Strong Distrib | 1 | Energy | — | 1.3× | |
| ABBOTINDIA | Nifty Healthcare Index | 26,840.0 | -11.3% | 0.80× | Bull | 17 | 0.05 | Neutral | 0 | Pharma · Healthcare | — | 0.8× | |
| ABCAPITAL | Nifty Financial Services | 375.1 | -11.7% | 1.76× | Bear | 15 | -0.29 | Distrib | 2 | — | — | 1.8× | |
| ABDL | Nifty FMCG | 679.5 | -6.1% | 1.01× | Bear | 16 | 0.55 | Accum | 2 | — | — | 1.0× | |
| ABREL | Nifty Realty | 1,100.5 | -41.8% | 2.15× | Bull | 20 | -0.30 | Distrib | 0 | Realty | — | 2.2× | |
| ABSLAMC | Nifty Financial Services | 991.7 | -17.3% | 1.23× | Bear | 12 | -0.07 | Neutral | 1 | — | — | 1.2× | |
| ACC | — | 1,182.8 | -38.2% | 0.98× | Bull | 13 | -0.31 | Distrib | 1 | — | — | 1.0× | |
| ACE | — | 1,212.3 | -3.3% | 1.38× | Bear | 14 | 0.37 | Accum | 2 | — | — | 1.4× | |
| ACMESOLAR | — | 432.6 | -5.7% | 0.40× | Bear | 15 | 0.36 | Accum | 3 | Power / Renewables | — | 0.4× | |
| ACUTAAS | Nifty Healthcare Index | 3,196.5 | -13.5% | 1.06× | Bear | 10 | -0.25 | Distrib | 0 | Pharma · Chemicals | — | 1.1× | |
| ADANIENSOL | Nifty Commodities | 1,326.4 | -23.8% | 3.67× | Bull | 12 | -1.16 | Strong Distrib | 0 | Energy · Commodities +1 | — | 3.7× | |
| ADANIENT | Nifty Metal | 2,816.8 | -12.3% | 1.24× | Bear | 12 | -0.28 | Distrib | 0 | Metals · Aviation +2 | — | 1.2× | |
| ADANIGREEN | Nifty Commodities | 1,276.1 | -20.5% | 4.48× | Bear | 12 | -0.06 | Neutral | 2 | Energy · Infrastructure +2 | — | 4.5× | |
| ADANIPORTS | Nifty Infrastructure | 1,737.8 | -7.7% | 0.98× | Bull | 9 | 0.23 | Accum | 1 | Infrastructure · Transport / Logistics | — | 1.0× | |
| ADANIPOWER | Nifty Commodities | 196.2 | -21.2% | 1.77× | Bear | 18 | -0.08 | Neutral | 1 | Energy · Infrastructure +1 | — | 1.8× | |
| AEGISLOG | Nifty Oil & Gas | 1,401.1 | -5.7% | 1.12× | — | — | -0.09 | Neutral | 2 | Chemicals · Energy +2 | — | 1.1× | |
| AEGISVOPAK | Nifty Oil & Gas | 290.8 | -8.7% | 0.88× | Bear | 11 | 0.35 | Accum | 2 | Oil & Gas | — | 0.9× | |
| AETHER | — | 1,670.0 | -5.5% | 1.29× | — | — | -0.15 | Distrib | 1 | Chemicals | — | 1.3× | |
| AFFLE | Nifty IT | 1,449.6 | -29.7% | 0.44× | Bear | 12 | 0.06 | Neutral | 2 | — | — | 0.4× | |
| AIAENG | — | 3,824.4 | -24.7% | 0.47× | Bull | 14 | -0.95 | Strong Distrib | 1 | — | — | 0.5× | |
| AIIL | Nifty Financial Services | 539.3 | -19.3% | 0.42× | Bear | 19 | 0.10 | Neutral | 1 | — | — | 0.4× | |
| AJANTPHARM | Nifty Pharma | 3,581.0 | -3.7% | 0.81× | Bear | 17 | -0.72 | Strong Distrib | 0 | Pharma | — | 0.8× |
Each row is one liquid stock on the latest exchange close. Every value is a stored, precomputed number — nothing is recomputed or predicted on the fly.
How to read this screen
plain EnglishSource: Patearn glossary.
How to read this screen SCREENscope · views · columns · the URL
Pick a scope (an index, your watchlist, everything liquid, or a theme), then a view — a named set of columns for one question. Add or drop whole column families, sort on any column, and narrow with the filter box. Nothing is hidden behind a plan: every column, filter and export is free.
Numeric cuts. Any number column can also be cut to a threshold, straight from the address bar: ?f=su1:gte:3 keeps only rows whose Surge 1m is 3 or more, and ?f=su1:gte:3,dlv:gte:60 asks for both at once (gte = at least, lte = at most; up to six cuts). Each active cut appears as a chip you can click to remove. A name whose value for that column is unknown is left OUT — a cut lists the names that met it, never the names nobody measured.
The Confluence column counts how many independent pillars line up on a name today (delivery positioning · accumulation · relative strength · structure · credibility · geometry). It is a way to sort a shortlist, not a score to act on — the pillars were built and tested separately, and several of them are explicitly descriptive-only.
The address bar is the saved screen. Every choice you make is in the URL, so you can bookmark it, share it, or paste it to a colleague and they see exactly your screen. The CSV button downloads that same screen — same scope, same filter, same sort, same columns.
Only liquid names are shown: a stock must trade at or above the 30th percentile of the day's exchange turnover. That floor re-derives from the data every day rather than sitting at a fixed rupee number. How many names it removed is printed beside the count above — and if the floor could not be derived on this host, that line says the fence is not in force rather than repeating this paragraph.
Wolfe geometry — Descriptive only — the studied edge was in SELECTION, not in the geometry itself. Never a target or an entry.
Accumulation — Descriptive only — the accumulation/distribution read failed its out-of-sample gate. It describes the tape; it never ranks and never triggers.
Confluence — How many independent pillars line up right now. A sorting heuristic for building a shortlist — not a validated model, not a score to act on.
Themes and baskets are a different door onto the same data — browse by what companies actually do →