The earlier piece on price and market risk found no clean relationship between a stock's price band and its beta — except that its single widest, cheapest bucket, "under ₹1,000," was actually hiding almost 4,900 stocks with wildly different profiles inside one label. Splitting that bucket into four narrower price bands reveals exactly what the wide bucket was averaging away.
Below ₹250 Is Where the Real Risk Lives: Splitting India's Cheapest Stocks Four Ways
1. One bucket, four very different neighbourhoods
Of the 4,862 NSE/BSE stocks priced under ₹1,000, this article split them into four sub-bands — ₹0–250, ₹250–500, ₹500–750 and ₹750–1,000 — using the same Screener.in price data as the earlier piece. The split is lopsided in a way the single "under ₹1,000" label never showed:
| Price sub-band, ₹ | Stocks | Share of the under-1,000 universe, % | Median market cap, ₹ crore |
|---|---|---|---|
| 0–250 | 3,850 | 79.2 | 80 |
| 250–500 | 568 | 11.7 | 1,154 |
| 500–750 | 290 | 6.0 | 3,713 |
| 750–1,000 | 154 | 3.2 | 3,474 |
Nearly 80% of every stock priced under ₹1,000 is actually priced under ₹250, and the median market cap in that bottom slice — ₹80 crore — is a rounding error next to the ₹1,154 crore median just one sub-band up. The "under ₹1,000" bucket in the earlier piece wasn't really one population; it was a huge population of tiny, largely unproven companies with a much smaller population of genuinely small-to-mid-cap businesses riding along at the top of the same label.
2. Beta, return and Sharpe ratio, split four ways
Using the same methodology as the earlier piece — equal-weighted portfolios, 3.5 years of weekly local NSE price data (2 January 2023 to 7 August 2026), a 6.5% risk-free proxy — computed separately for each of the four sub-bands:
| Price sub-band, ₹ | Stocks with computed beta | Median beta | Portfolio return, % p.a. | Portfolio volatility, % p.a. | Sharpe ratio |
|---|---|---|---|---|---|
| 0–250 | 1,086 of 1,267 priced | 1.28 | 14.6 | 24.4 | 0.33 |
| 250–500 | 333 of 374 priced | 1.19 | 24.3 | 21.0 | 0.85 |
| 500–750 | 207 of 229 priced | 1.08 | 25.0 | 19.3 | 0.96 |
| 750–1,000 | 112 of 117 priced | 1.12 | 32.7 | 19.8 | 1.32 |
Unlike the five broad bands in the earlier piece, this is a genuinely clean, close-to-monotonic gradient. Beta falls from 1.28 to roughly 1.08–1.12 as price rises through the sub-bands; annualised volatility falls from 24.4% to about 19–20%; and the Sharpe ratio climbs steadily from 0.33 (poor, per the ranges in the earlier piece) to 1.32 (good) at the top of the range. The ₹0–250 sub-band is the worst-performing, highest-risk group in either piece — worse than the under-₹1,000 band looked as a whole, because that wider label was averaging nearly 4,900 mostly-junk names against a much smaller number of decent ones.
3. Real returns confirm the same pattern
Screener.in's own reported return and profit-growth fields, for the full population in each sub-band rather than a sample, tell the same story independently of the beta/Sharpe calculation above:
| Price sub-band, ₹ | Median 1-year return, % | Median 6-month return, % | Median YoY quarterly profit growth, % |
|---|---|---|---|
| 0–250 | −17.7 | −5.6 | 13.5 |
| 250–500 | 0.4 | 6.1 | 30.1 |
| 500–750 | 4.3 | 11.8 | 21.5 |
| 750–1,000 | 8.3 | 8.3 | 20.9 |
The median stock priced under ₹250 lost 17.7% over the trailing year; every sub-band above it posted a positive median return. This isn't a quirk of one calculation method — the equal-weighted portfolio series, the per-stock median beta, and Screener's own raw return field all point the same direction.
4. Does this contradict the earlier finding?
No — it sharpens it. The earlier piece's finding was that across the five broad price bands (under ₹1,000, ₹1,000–3,000, ₹3,000–5,000, ₹5,000–10,000, above ₹10,000), there was no clean relationship between price and risk: the highest-priced band didn't have the lowest beta, and beta didn't reliably track return. That finding still holds among stocks priced above ₹1,000 — the ₹1,000–3,000, ₹3,000–5,000, ₹5,000–10,000 and above-₹10,000 bands showed betas clustered close to 1.0 with no clean order. What this piece adds is that the relationship reappears sharply inside the bottom band, because price under roughly ₹250 in the Indian market is doing something a ₹1,000-wide bucket further up isn't: it's acting as a rough, imperfect proxy for genuinely tiny, illiquid, largely unproven companies, evidenced directly by the collapse in median market cap (₹80 crore vs. ₹1,154 crore one sub-band up) rather than by price alone. Price itself still isn't the risk factor — market capitalisation and liquidity are, and they happen to correlate tightly with price only at the very bottom of the market, where genuinely small companies rarely get "diluted" up to a higher nominal share price the way an established company's occasional bonus issue or split keeps its own share price in a normal trading range.
Related on this blog
See also: A Slice of Apple Costs About ₹1,700. A Slice of MRF Still Isn't Legal. — the original five-band price segmentation and beta comparison this piece splits further. · Why Bet on One Horse, When You Can Buy the Stable? — the Markowitz/Sharpe-ratio framework and methodology this piece reuses.
Sources
- Price-band segmentation and returns/profit-growth data for 4,862 stocks under ₹1,000, split into four sub-bands — Screener.in company data, 11 Aug 2026
- Beta, portfolio return, volatility and Sharpe ratio for each sub-band — computed from a local historical NSE OHLCV warehouse (adjusted close, year-partitioned parquet, 2 Jan 2023–7 Aug 2026), same methodology and window as this blog's earlier price-segmentation and Markowitz pieces
- Nifty 50 benchmark series and risk-free proxy sourced via Yahoo Finance, cross-checked against Screener.in's Nifty 50 index page
This analysis is based on historical price and fundamentals data cited above. It is provided for informational and research purposes only and does not constitute investment advice. Only 1,086 of the 1,267 ₹0–250-band stocks with at least a year of continuous local weekly price history in this article's data actually had sufficient history to compute a reliable beta (a completion rate broadly consistent with the under-₹1,000 band's data-completeness limitations flagged in the earlier piece); this remains a real, if partial, sample rather than the full 3,850-stock sub-band. Past risk-adjusted returns are backward-looking and specific to the window measured, not a prediction.
About this article: Researched, written and edited by Umashankar Triplicane Dwarakanathan, with AI research assistance; every figure is meant to trace to the primary source cited. See the Editorial Policy for how sourcing, AI use and corrections work.
