Plain-English guides to the tools behind the scanner — and original, measured findings from our own scan data that you won't find anywhere else. 62 pieces and counting.
Findings from our own measured scan data — unique to StockLearn.
We tested ~2,000 NSE stocks. A volume surge without price follow-through underperformed the market by ~0.48% over three days.
Our healthiest tag lagged on a raw basis — and the cause was entry timing, not the picks.
The same signal predicts opposite things at 3 days versus 3 weeks. The term structure of volume.
We split the data into calm and volatile regimes — the underperformance concentrates in the crash.
Stocks in an uptrend beat the rest — over a rising market. Skill, or beta?
The most popular buy trigger, measured across our scan history. On its own, it wasn't an edge.
The most expensive misreading in technical analysis. Why strong uptrends live in overbought territory.
Finance's most-documented factor, why it skips the last month, and the construction detail that trips people up.
Measured from a full NSE universe snapshot: the Nifty 50 holds 44.8% of total market capitalisation, and its own top ten constituents are 49.1% of the index.
Stage distribution, trend direction, RSI and distance from 52-week highs across the full NSE universe for one session. Most of the market, most of the time, is not.
Measured across 1,710 NSE stocks: median delivery percentage is 51.1%, half the market sits between 41.4% and 60.0%, and large caps run about 13 points above.
The methodology behind each signal, with worked examples.
Structure before signals — the four stages, derived from daily data on ~2,000 NSE stocks.
A daily trigger locates a moment; the 30-week trend decides whether it's worth anything.
Weinstein's second pillar, and the ingredient most screeners skip. How we measure it.
What separates a real breakout from a fake one.
The advancing-stage breakout that trend-followers wait for.
The four scanner verdict labels defined, plus the real distribution across ~1,930 NSE stocks — where caution is the majority state and bullish covers under 4% of.
Every named scanner signal with its frequency across 1,762 NSE stocks. EMA alignment covers 60% of the market; a MACD crossover covers 5%. Why we publish base rates.
StockLearn's 30-week trend line is computed from daily closes as a 150-session moving average. Why there is no separate weekly scan, and why the old weekly gate was.
Data-driven analysis across 1,700+ Indian mutual funds.
We checked 496 equity funds. In this window, 80% of last year's winners stayed above median.
Category set a ~6-point baseline — but within a category, funds spread 7–12 points.
Across 830 funds, the median fund's 5-year return swung 10.6 points depending on the window.
International led the year; Pharma leads the quarter. The leaderboard reshuffles faster than you rebalance.
It sounds trivial. Over 10 years a 1% ratio quietly erased ~8.6% of the corpus.
The middle half of arbitrage funds sits within 0.27 percentage points of one-year return, against 8.79 points for small caps. Why the category is structurally.
Measured across 35 fund categories: in 80% of them, the one-year leader is not the five-year leader. Median rank shifts run to eight places in ELSS and Large & Mid.
Median maximum drawdown across 1,767 funds by category group, why large-cap funds show deeper drawdowns than small caps, and two debt-fund figures that are data.
574 equity funds split into AUM quintiles: expense ratios fall steadily with size, and the largest quintile shows a lower one-year return. Why that isn't evidence.
How the fund scanner, sector-momentum and fund pages work.
1,761 funds ranked nightly from public NAV data — SIP-health, peer rank, and what every column means.
Using one fund house's Nifty index funds as clean sector proxies, so the gaps are sector performance.
Every fund measured against the best 1-year performer in its own category — rank and gap.
Returns, risk, SIP-vs-lumpsum, and the rolling-window table that a single trailing number hides.
Category sizes in our universe run from 1 fund to 365. Why a rank is not comparable across categories, why the spread matters more than the ordering, and why the.
Base TER, total TER, direct versus regular plans, and daily accrual. What the layers of a mutual fund expense ratio are, and which one StockLearn displays.
Reading F&O open-interest positioning on NSE stocks.
Four positioning states from price and open interest — across every NSE F&O stock.
How forceful today's positioning is, versus what the chart says — and why they can disagree.
Long buildup, short buildup, short covering and long unwinding explained from first principles — including why all four are inferences rather than.
NSE lists three futures expiries per symbol. Why StockLearn reports the total rather than near-month only, what that choice hides, and why every page also carries a.
NSE revises futures lot sizes to keep contract values in band, which makes contract counts discontinuous over time and incomparable across symbols. Converting to.
The dual-axis chart on every StockLearn F&O page shows price and futures open interest over recent sessions. What it's good for, and why the two lines crossing.
How we keep the data honest — and measure ourselves.
Most scanners never check. Why “it worked” is far harder to prove than it looks.
The mistake that flatters every screener that tests today's index constituents on the past.
The split & bonus adjustment nobody does — and how it turns real data into fake crashes.
High volume with low delivery is churn; with high delivery it's accumulation.
StockLearn measures individual components over fixed horizons rather than backtesting complete trading systems. Why that distinction matters, and what it costs.
What a t-statistic measures, why StockLearn's bar sits at 2.4 rather than the conventional 2.0, and what happened when one of our own published results landed.
Unstable symbols, ampersands that break XML, an irregular holiday calendar, a shifting F&O universe and glitch NAVs. A concrete list of what building on NSE and.
Where StockLearn's data dates come from, when a page is legitimately older than you expect, and the caching failure mode that made deleted files look present.
NSE indices are reviewed and reconstituted on a schedule. Why using today's constituent list for a historical study produces a flattering, meaningless answer, and.
The scanner runs on NSE end-of-day bhavcopy: six numbers per stock per day. What that rules out, why we haven't bought an intraday feed, and what daily data is.
What the product does, what it deliberately doesn't, and how it's priced.
No tips, no targets, no stop-losses, no portfolio advice, no intraday data, no SEBI registration. A plain statement of the product's boundaries and the reasoning.
What sits on each side of StockLearn's free boundary, why data volume rather than feature-gating decides it, and why the mutual fund screener is free entirely.
Plain-English guides to the core technical indicators.
SMA vs EMA, and how the key averages define a trend.
What the relative strength index measures, and how to read it in bands.
Moving-average convergence-divergence, in plain English.
How to measure whether a move has real conviction behind it.
The price levels where trends pause, break, or reverse.
Weinstein's four stages — the structure behind every setup.
When price and momentum disagree, momentum often tells the truth first.
Why fading volume in a base can precede a breakout.
Buying strength on a dip instead of chasing the breakout.
Why a daily signal only counts when the weekly trend agrees.