# Fundamental stock scanners for NSE > Fundamental screeners for NSE stocks: promoter buying and selling, shareholding patterns, market-cap filters and sector scans — point-in-time data with no restatement leakage. Canonical: https://patternsradar.com/scans/fundamentals These scans read what the filings say rather than what the chart does: who owns the company, how the ownership is shifting, how big the business is, and which sector block it trades with. The shareholding scans are the heart of the group — promoter stake changes are the closest thing to a public insider signal Indian markets offer, and a promoter adding or cutting a full percentage point in one quarter is a deliberate act with a filing date attached. The sector and industry scans express rotation directly: membership first, technical condition second, which is the query shape no price-only screener can write. Everything here is point-in-time — a scan on any past date sees only what had been filed by that date, so a result published after the close counts from the next session and a restatement counts from its own filing, never retroactively. That discipline is what makes the hit-rate replays on these pages honest. Coverage is the standing caveat: fundamentals exist only where a filing has been collected and parsed — about three in four listed equities on any given day — and a stock without data is NULL, which never matches, so these scans understate rather than guess. ## The scans (13) ### Promoters buying https://patternsradar.com/screener/promoter-buying.md ```sift where promoter_change_qoq > 0.5 and close > sma(200) ``` Promoter stake up over half a percentage point last quarter, in a stock holding its long-term trend. Promoters know their company better than any outside analyst, and they raise their stake with their own money for exactly one reason. A half-point increase in a single quarter is a deliberate act, not drift. The trend filter keeps the list to stocks the market already agrees with — insider buying into a broken chart is a different, harder trade. ### Promoters selling https://patternsradar.com/screener/promoter-selling.md ```sift where promoter_change_qoq < -1 ``` Promoter stake cut by more than a percentage point in a quarter — the insiders reducing. A full percentage point of promoter stake sold in one quarter is rarely noise. It is not automatically bearish — stakes also fall through pledged-share invocation, dilution from a fundraise, or regulatory minimum-float selling — but every one of those is worth knowing about in a stock you hold, and the benign explanations are checkable in the filings once the scan has pointed at the stock. ### High promoter holding in an uptrend https://patternsradar.com/screener/high-promoter-holding.md ```sift where promoter_pct > 70 and close > sma(200) ``` Promoters holding over 70% and the price above its 200-day average — tight float, aligned owners. When promoters hold seventy percent, the tradable float is thin and the people with the most information have the most to lose. In an uptrend that combination compounds: modest buying moves a tight float further than it would a wide one. The cost is liquidity — these stocks move fast in both directions — which is exactly what the liquidity-ranked universe tier is limiting. ### Institutions on both sides https://patternsradar.com/screener/institutional-ownership.md ```sift where fii_pct > 15 and dii_pct > 15 ``` FII and DII each holding over 15% — the rare stocks both kinds of institutional money agree on. Foreign and domestic institutions often sit on opposite sides of the Indian tape — one selling the very exposure the other is accumulating. A stock where both hold more than fifteen percent is the overlap of two separate due-diligence processes, and the overlap shows up in behaviour: deep institutional ownership means research coverage, index membership, and someone on the bid in a selloff. It is a quality list, not a timing signal — pair it with a technical scan for entries. Ownership comes from quarterly shareholding filings, so changes land on filing dates, not trade dates. ### Tight public float https://patternsradar.com/screener/tight-float.md ```sift where public_pct < 25 ``` Public shareholders holding under a quarter of the company — scarcity as a price amplifier. When public shareholders hold less than 25%, whoever holds the rest — promoters, the government, a foreign parent — is not selling at market prices. The tradable float is a fraction of the listed size, so the same buying moves the price further, in both directions. Listed subsidiaries and recent listings sitting at the minimum public shareholding live on this list. It reads best alongside a demand signal — a volume or delivery scan — because scarcity only amplifies interest that already exists; on its own it is a property of the stock, not an event. ### Pledged promoter stakes https://patternsradar.com/screener/pledged-promoters.md ```sift where promoter_pledged_pct > 20 ``` More than a fifth of the promoter holding pledged as loan collateral — the risk screen, not a buy list. Pledged shares are a standing margin call: fall far enough and the lender sells the collateral into the decline, which is how bad weeks become terrible ones. A fifth of the promoter stake pledged is past the point of routine treasury management. This scan inverts the rest of the category — it is a list to check holdings against, not to buy from — and it is short by design, because heavy pledging is rare among liquid names precisely for the reason it is worth screening: the market punishes it. Filings report a pledge only where one exists, so absence from this list usually means zero, occasionally just an unparsed filing. ### Large-cap pullback https://patternsradar.com/screener/mega-cap-dip.md ```sift where marketcap > 20000cr and rsi(14) < 40 ``` Stocks above ₹20,000 crore market cap washed out below RSI 40 — size as the quality filter. A market-cap floor is the simplest quality screen there is: a twenty-thousand-crore company has institutional ownership, analyst coverage and a business that survived scrutiny, so an oversold reading is more often a pullback than a collapse. One mechanical caveat: market cap is the day's close times the latest filed share count, so the size floor moves with the price itself — a stock that crashes through the threshold drops off this list even as it becomes more oversold. ### Low PE in an uptrend https://patternsradar.com/screener/low-pe-uptrend.md ```sift where pe < 15 and close > sma(200) ``` Stocks under fifteen times trailing earnings, holding above the 200-day — cheap, and no longer ignored. A low P/E on its own is a value-trap list: businesses priced cheap because they deserve to be. The trend filter changes the question — a stock below fifteen times trailing earnings that also holds above its 200-day average is cheap and being re-rated, not cheap and forgotten. The earnings side is point-in-time trailing twelve months, so a stock appears only once four quarters are on file, and loss-makers — where a P/E means nothing — are NULL and excluded by construction. ### Earnings growth with revenue behind it https://patternsradar.com/screener/earnings-growth.md ```sift where profit_growth_yoy > 25 and revenue_growth_yoy > 15 ``` Latest quarter profit up 25% on the year with revenue up 15% — growth the top line can explain. Profit growth alone is the easiest number to flatter: a tax writeback, an asset sale, a soft base quarter. Requiring revenue growth alongside filters for the version that lasts — more business, not just better accounting. Both numbers compare the latest filed quarter to the same quarter a year earlier, counted from the filing date, so the scan sees each result exactly when the market did. The base-effect caveat survives the filter — a company recovering from a terrible year still posts spectacular percentages — which the revenue leg tempers but cannot eliminate. ### Quality compounders https://patternsradar.com/screener/quality-compounders.md ```sift where profit_cagr_5y > 15 and pe < 30 and interest_cost_growth_yoy < 5 and sector is not "Financial Services" ``` Profit compounding above 15% a year for five years, still under 30× earnings, with the interest bill flat — growth that was not bought with debt. Three legs, each closing a hatch the others leave open. Five years of trailing-twelve-month profit growth is the compounding test: one good year against a soft base cannot carry a five-year rate, and a company that grew through a full cycle is a different animal from one that caught a single upswing. The P/E ceiling is the price test — compounding the market has already paid for is not an opportunity. The interest leg is the honest approximation available here: Indian quarterly filings carry a profit-and-loss statement and no balance sheet, so there is no debt figure to screen on, and the interest bill is what we can see. Flat interest beside compounding profit is growth funded from earnings; a jump is the tell that it was funded with borrowing. Lenders are excluded for exactly that reason — for a bank, interest paid is the cost of goods and rises with a healthy loan book. Coverage is the real limit: the results backfill starts in 2018, so roughly half of covered names can answer a five-year question at all and the rest are NULL, which never matches. Widen it with `profit_cagr_3y`, lengthen it with `profit_cagr_7y`, or add `profit_growth_yoy > 15` to insist the latest quarter is still delivering. ### IT stocks in an uptrend https://patternsradar.com/screener/it-stocks-uptrend.md ```sift where sector is "Information Technology" and close > sma(200) and rsi(14) > 55 ``` The Information Technology sector filtered to names above the 200-day with momentum intact. Sector rotation is half of Indian market behaviour, and this is how a rotation scan is written: membership first, then the technical condition. IT stocks trade as a block — the same currency, the same client geographies, the same rate cycle — so when the sector turns, the strong names turn first. One caveat: sector membership is today's classification applied retroactively, so historical replays lean on the current list. ### Banks near 52-week highs https://patternsradar.com/screener/banks-near-highs.md ```sift where industry is "Banks" and close within 3% of high_52w ``` Banking stocks within 3% of their 52-week high — the market's most-watched industry at its strongest. Banks lead Indian indices by weight and by narrative, and a bank pressing its yearly high is a statement about credit conditions, not just one chart. Scanning the industry tier rather than the broader Financial Services sector keeps out the NBFCs and insurers, which trade on different cycles. The proximity form catches stocks at the high without demanding the breakout print itself. ### Commodity stocks above the 200-day https://patternsradar.com/screener/commodity-uptrends.md ```sift where macro_sector is "Commodities" and close > sma(200) ``` The commodities macro-sector filtered to long-term uptrends — a cycle scan in one line. Commodity stocks are the market's purest cycle plays: metals, mining, oil and gas move on global prices no company controls, and they move together. The macro-sector tier is the right altitude for that question — broader than any single industry, and the 200-day filter sorts the names already in an upcycle from the ones still waiting for it. ## Common questions ### What does a change in promoter holding tell you? Promoters are the ultimate insiders, and stake changes are disclosed quarterly. An increase is unambiguous — they bought with their own money. A decrease needs reading: it can mean genuine selling, but also pledge invocation, dilution from a fundraise, or regulatory float requirements. The scan points at the stock; the filing explains the move. ### Why point-in-time fundamentals? Because backtests lie without it. If a scan replayed on last March sees earnings that were filed in May, it is trading on information nobody had — look-ahead bias in its most common form. Point-in-time means every number becomes visible only from its filing date, so a replayed scan holds only stocks it could genuinely have found that day. ### Why does a fundamental scan return fewer stocks than a price scan? Coverage. Every listed instrument has a price bar, but a fundamental value exists only where a filing has been collected and parsed — ETFs and indices never file results, and some companies file late or in shapes the parser rejects. A stock with no data is NULL, and NULL never matches a condition — the scan understates rather than guesses.