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 (₹)? | SMA 20? | SMA 50? | SMA 200? | vs SMA 20? | vs SMA 50? | vs SMA 200? | MA stack? | Themes | Instrument | Rank in screen | vs own 1-mo |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 360ONE | Nifty Financial Services | 1,040.0 | 1,079.8 | 1,132.8 | 1,107.0 | -3.7% | -8.2% | -6.0% | Below All | — | — | 1.1× | |
| AADHARHFC | Nifty Financial Services | 448.4 | 458.7 | 476.7 | 481.7 | -2.2% | -5.9% | -6.9% | Below All | — | — | 1.7× | |
| AARTIIND | Nifty Chemicals | 465.1 | 487.2 | 501.5 | 452.3 | -4.5% | -7.2% | +2.8% | Mixed | Chemicals | — | 0.8× | |
| ABB | Nifty Energy | 6,900.0 | 7,152.8 | 7,376.7 | 6,552.1 | -3.5% | -6.5% | +5.3% | Mixed | Energy | — | 1.3× | |
| ABBOTINDIA | Nifty Healthcare Index | 26,840.0 | 26,394.0 | 26,862.7 | 26,892.7 | +1.7% | -0.1% | -0.2% | Mixed | Pharma · Healthcare | — | 0.8× | |
| ABCAPITAL | Nifty Financial Services | 375.1 | 393.1 | 400.7 | 364.4 | -4.6% | -6.4% | +2.9% | Mixed | — | — | 1.8× | |
| ABDL | Nifty FMCG | 679.5 | 653.4 | 630.4 | 563.9 | +4.0% | +7.8% | +20.5% | Above All | — | — | 1.0× | |
| ABREL | Nifty Realty | 1,100.5 | 1,255.9 | 1,339.9 | 1,364.4 | -12.4% | -17.9% | -19.3% | Below All | Realty | — | 2.2× | |
| ABSLAMC | Nifty Financial Services | 991.7 | 1,037.8 | 1,024.9 | 977.0 | -4.4% | -3.2% | +1.5% | Mixed | — | — | 1.2× | |
| ACC | — | 1,182.8 | 1,240.6 | 1,295.1 | 1,447.7 | -4.7% | -8.7% | -18.3% | Below All | — | — | 1.0× | |
| ACE | — | 1,212.3 | 1,182.8 | 1,137.4 | 962.2 | +2.5% | +6.6% | +26.0% | Above All | — | — | 1.4× | |
| ACMESOLAR | — | 432.6 | 426.9 | 398.3 | 308.3 | +1.3% | +8.6% | +40.3% | Above All | Power / Renewables | — | 0.4× | |
| ACUTAAS | Nifty Healthcare Index | 3,196.5 | 3,281.6 | 3,257.9 | 2,663.8 | -2.6% | -1.9% | +20.0% | Mixed | Pharma · Chemicals | — | 1.1× | |
| ADANIENSOL | Nifty Commodities | 1,326.4 | 1,368.7 | 1,505.2 | 1,283.0 | -3.1% | -11.9% | +3.4% | Mixed | Energy · Commodities +1 | — | 3.7× | |
| ADANIENT | Nifty Metal | 2,816.8 | 2,954.1 | 2,992.2 | 2,567.1 | -4.7% | -5.9% | +9.7% | Mixed | Metals · Aviation +2 | — | 1.2× | |
| ADANIGREEN | Nifty Commodities | 1,276.1 | 1,286.4 | 1,318.8 | 1,196.3 | -0.8% | -3.2% | +6.7% | Mixed | Energy · Infrastructure +2 | — | 4.5× | |
| ADANIPORTS | Nifty Infrastructure | 1,737.8 | 1,759.5 | 1,721.7 | 1,627.5 | -1.2% | +0.9% | +6.8% | Mixed | Infrastructure · Transport / Logistics | — | 1.0× | |
| ADANIPOWER | Nifty Commodities | 196.2 | 204.8 | 206.8 | 187.1 | -4.2% | -5.1% | +4.8% | Mixed | Energy · Commodities | — | 1.8× | |
| AEGISLOG | Nifty Oil & Gas | 1,401.1 | 1,349.8 | 1,329.8 | 924.6 | +3.8% | +5.4% | +51.5% | Above All | Chemicals · Energy +2 | — | 1.1× | |
| AEGISVOPAK | Nifty Oil & Gas | 290.8 | 296.8 | 286.8 | 236.0 | -2.0% | +1.4% | +23.2% | Mixed | Oil & Gas | — | 0.9× | |
| AETHER | — | 1,670.0 | 1,655.5 | 1,616.7 | 1,227.7 | +0.9% | +3.3% | +36.0% | Above All | Chemicals | — | 1.3× | |
| AFFLE | Nifty IT | 1,449.6 | 1,564.5 | 1,608.6 | 1,540.9 | -7.3% | -9.9% | -5.9% | Below All | — | — | 0.4× | |
| AIAENG | — | 3,824.4 | 4,005.6 | 4,293.7 | 4,125.6 | -4.5% | -10.9% | -7.3% | Below All | — | — | 0.5× | |
| AIIL | Nifty Financial Services | 539.3 | 537.5 | 548.5 | 778.2 | +0.3% | -1.7% | -30.7% | Mixed | — | — | 0.4× | |
| AJANTPHARM | Nifty Pharma | 3,581.0 | 3,537.6 | 3,533.2 | 3,101.9 | +1.2% | +1.4% | +15.4% | Above All | 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.
Moving averages — Simple moving averages of CLOSE, and today's distance from each in percent. A short history yields no value rather than a shorter average wearing a longer label, so a recently-listed name is absent from a 200-day cut rather than qualifying on three months of data.
Themes and baskets are a different door onto the same data — browse by what companies actually do →