Technical & Price Action
52-Week Doublers (100%+ Return) is a Technical & Price Action screen. It checks every NSE-listed stock against 1 condition computed from nightly data, after excluding heavily pledged promoters and very small market caps. This page explains the rule, each figure and its source. It lists no stocks and is not advice.
Doubling in price within a single year is an extraordinary outcome that requires either a fundamental business inflection, a significant earnings re-rating, or in rarer cases a speculative surge. While our new_high screen requires only that a stock has reached a new 52-week high with no return magnitude requirement, doublers represent a high-conviction discovery filter that surfaces only the most dramatic performers. Historically, a 100% return in 52 weeks can reflect genuine business transformation (new product cycle, market share gain, debt reduction, management change) or speculative excess — volume validation is the primary tool for distinguishing between these two cases. High average volume alongside a doubling price typically signals institutional participation, while price doublings on thin volume are more likely speculative. This screen is a discovery tool, not a buy signal, and requires fundamental follow-through to qualify for any recommendation.
A stock must satisfy every condition below. Conditions are grouped under the pillar they test.
Return Magnitude
Volume Validation
Described in the philosophy; not a pass/fail condition in the current rule
Hard excludes
Ranked by 1-Year Return, highest first.
52-Week Price Return (%)
Percentage price return over the trailing 52 weeks, computed as (current_price / price_52wk_ago - 1) * 100 using daily closing prices. The qualifier threshold is ≥100%.
High is better
Current Price (₹)
Latest available closing price of the stock in Indian Rupees, sourced from daily OHLCV data.
High is better
52-Week Average Daily Volume
Average daily traded volume (number of shares) over the trailing 52 weeks, computed as the simple mean of daily volume observations from OHLCV data.
High is better
Type hypothetical values to see which conditions they satisfy. These are not real stocks and nothing here is stored.
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How many stocks pass if this threshold were set differently. Counts only; no stocks are named.
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In the past data we checked, the stocks this screen picked did better than the ones it left out, but a portfolio built from them did not clear our test after trading costs. We looked back over 64 months. Each month we checked whether the stocks this screen picked did better, over the following month (21 trading days), than the stocks it didn't pick. We score that from -1 (the picks always did worse) to +1 (always did better); 0 means no pattern. This screen scored 0.0471. As a measurement, the score is small, but clearly above zero. If the screen had no real edge, a score at least this far from zero would show up less than 1 in 1,000 by luck alone.
We also tested a portfolio of the screen's picks, using only what was known at the time and after estimated trading costs: it earned 0.76 for each unit of ups and downs, per year. Because this screen has been tested 2 times, we mark down results that could be flukes. After that, the chance that it truly beats simply holding the index is 0.608, about 61 in 100.
A pattern can exist and still not be worth trading after costs. This is a record of the past, not a prediction. A screen is still a way to narrow a list by your own rules, whatever the measurement says.
Not yet testable — 5 of 6 points needed to chart a rolling information coefficient.
This is a historical, statistical measurement produced by FINOME TECHNOLOGIES PVT LTD's research harness on past data. It is not a prediction, and past results do not indicate future results. The universe is today's Nifty 500 constituents, so the sample is affected by survivorship bias. It describes how a screen's selections behaved in the past and does not constitute investment advice or a recommendation.
Rule version 1.0.0