Do beaten-down stocks bounce back?
No. Since 1995, the fifth of US stocks furthest below their 12-month high beat the same day's median stock over the next three months 49 times in 100; the fifth nearest its high, 49 times. A coin flip gives 50. The rank correlation between the depth of the fall and the next three months was 0.004 (t 0.4): no measurable edge in either direction.
The paper
The full study: its data, method, robustness, limits and sources.
Opulence Alpha Research · Published Sep 25, 2026 · Data through Aug 21, 2026
Keywords: beaten-down stocks, do beaten-down stocks bounce back, stocks far below 52-week high, contrarian investing backtest, mean reversion in stocks, do loser stocks rebound·JEL classification: G11, G12, G14, C12, C58
- Universe
- The same for every study: 1,767 US common stocks in the 11 GICS sectors, 422 of them since delisted; S&P 500 members since 1996 plus large and mid-sized companies outside the index
- Period
- Every Wednesday from Jan 4, 1995 to Aug 19, 2026: 1,634 Wednesdays across 7,959 trading sessions
- Sample
- n = 1,763 stocks of the 1,767-stock universe; 1,889,758 stock-weeks, a median of 1,148 stocks per Wednesday
- Outcome
- Return over the next 1, 5, 21 and 63 trading sessions against the same day's median stock
- Inference
- t on non-overlapping dates; proven only when |t| ≥ 3 and the same sign in at least 60% of years
1Introduction
A stock that has fallen far below its recent high is often called cheap, oversold or due for a rebound, and contrarian investors seek such stocks out on the view that markets overreact to bad news. De Bondt and Thaler (1985) reported that stocks with the worst returns over several years later did better than those with the best. This study asks a simpler and more common question: do stocks that sit far below their 12-month high go on to beat other stocks over the following weeks and months?
2Data and method
2.1Sample design
Population and frame. The population is US common stocks listed on the NYSE and Nasdaq; funds, ETFs, trusts, preferred shares, warrants and units are excluded. The sampling frame is a fixed universe of 1,767 companies, drawn once when the platform was built and not re-sampled since, in two strata. Stratum 1 is a census of the S&P 500: every company in the index at any time since 1996 whose price history could be recovered, 1,027 companies of which 413 have since delisted; it holds 76% of the index's members in 1996 and at least 96% in every year from 2010. Stratum 2 is 740 large and mid-sized companies outside the index, selected in proportion to the market's sector weights from the stocks that passed a minimum share price of $15 and a minimum average daily trading value of $25 million; 9 of them have since delisted.
Sample. The unit of observation is a stock-week: one stock on one Wednesday. A stock enters a Wednesday's cross-section when it has a valid close that day, a value of the signal and a measured outcome; bars flagged as bad data and returns that cross a change of issuer are left out. This study's sample is n = 1,763 stocks of the 1,767: 1,889,758 stock-weeks on 1,634 Wednesdays from Jan 4, 1995 to Aug 19, 2026, a median of 1,148 stocks per Wednesday (range 820 to 1,371). 331,954 stock-weeks (17.6%) come from the 422 companies that have since delisted. Every stock and every Wednesday carries equal weight.
Representativeness. Table 1 gives the sample by GICS sector beside the S&P Composite 1500: 7.9% of companies would have to change sector for the two to match exactly. By latest market value, 55% of the active companies are large (at least $10bn), 38% mid ($2–10bn) and 6% small. Because Stratum 2 was chosen from companies listed at construction, its history carries survivorship bias. Section 4 repeats the lead result among the stocks that were S&P 500 members on each date, the part of the sample largely free of that bias.
Companies in this study's sample, of them those since delisted, the size of the active companies, the sample's share of stock-weeks and the sector's share of the S&P Composite 1500.
| Sector | Sample | Delisted | Large | Mid | Small | Stock-weeks | S&P 1500 |
|---|---|---|---|---|---|---|---|
| Information Technology | 282 | 67 | 122 | 76 | 18 | 13.9% | 12.7% |
| Financials | 256 | 60 | 114 | 74 | 8 | 14.6% | 17.2% |
| Industrials | 255 | 53 | 126 | 67 | 11 | 15.9% | 17.5% |
| Health Care | 237 | 47 | 92 | 81 | 16 | 12.4% | 10.9% |
| Consumer Discretionary | 209 | 39 | 69 | 87 | 12 | 12.3% | 12.9% |
| Energy | 105 | 30 | 39 | 31 | 5 | 5.9% | 4.7% |
| Consumer Staples | 101 | 38 | 40 | 17 | 5 | 5.9% | 4.9% |
| Materials | 94 | 34 | 35 | 24 | 2 | 5.6% | 5.1% |
| Real Estate | 84 | 10 | 40 | 32 | 2 | 5.7% | 6.9% |
| Communication Services | 80 | 31 | 28 | 13 | 5 | 3.9% | 3.3% |
| Utilities | 60 | 13 | 35 | 12 | 0 | 4% | 4% |
| All sectors | 1,763 | 422 | 740 | 514 | 84 | 100% | 100% |
Sample: n = 1,763 of the 1,767 companies. Size by latest market value for the 1,338 active companies with one: large ≥ $10bn, mid $2–10bn, small < $2bn. S&P 1500 shares count the constituents of the S&P 500, MidCap 400 and SmallCap 600 (1,506 companies, lists read Sep 25, 2026). Sectors are each company's current GICS sector.
2.2Signals
| Signal | Definition | Since | Wednesdays |
|---|---|---|---|
| Distance below the 12-month high | How far the close sits below the highest close of the past 252 sessions; stocks ranked into fifths each Wednesday | Jan 4, 1995 | 1,634 |
2.3Measurement
Outcome. The return from the close on the Wednesday to the close 1, 5, 21 and 63 trading sessions later, on closes adjusted for splits and dividends, compared with the same day's median stock; half of all stocks beat the median by construction, so chance is 50 in 100 on every date. No delisting return is added.
Each Wednesday the stocks are ranked on the signal. The study reports how often each fifth of that ranking beat the median stock, and the rank correlation (IC) between the signal and the return that followed.
The t-statistic uses non-overlapping dates only. A result is called proven when |t| is at least 3, it held in at least 60% of years and it is large enough to matter; with 1,470 tests across the studies, a looser bar would pass dozens by luck.
Full data and methods3Results
Figure 1 ranks the stocks every Wednesday by how far each sat below its highest close of the past year, from the fifth nearest its high (lowest) to the fifth furthest below it (highest), and reads each fifth over the next three months. The fifth nearest its high beat the median stock 49 times in 100 and the fifth furthest below it 49 times; the three fifths between them also sit close to 50. Figure 2 reads the rank correlation at every horizon: 0.004 at three months (t 0.4), and close to zero over a session, a week and a month.
Share of each fifth that beat the same day’s median stock. Colour only where the relation is proven.
Next three months.
Next week, three-session return against the industry; the same way in 32 of 32 years.
Rank correlation between the signal and the return that followed, with its 95% interval. An interval that crosses zero is no relation.
Rank correlation inside each GICS sector over the next three months, stocks ranked only against their own sector. Colour only where |t| ≥ 2.
Averages tell a different story from the typical stock. Measured against the universe's equal-weighted average return over three months, the most beaten-down fifth averaged 1.77 points and the fifth nearest its high -0.96 points; yet only 49 in 100 stocks of the fallen fifth beat the median stock. The average leans on a minority of large rebounds; the typical stock in that fifth did no better than the typical stock overall. The average is not a tested result, and because no delisting return is added, bankruptcies among the fallen are missing from it (see Limitations).
A deep fall below the year's high gathers two kinds of stock: companies whose price overshot and companies whose business has truly worsened. The price alone cannot tell them apart, and measured across all of them, the depth of the fall carried no measurable information about the next three months.
4Robustness
Table 3 re-measures the three-month relation: the rank correlation was 0.004 across all stocks (t 0.4) and 0.008 among S&P 500 members (t 0.6); its sign held in 9 of 11 sectors but in only 1 of the three decades. Year by year, the fallen fifth beat the median stock more often than the fifth nearest its high in only 12 of 32 years.
Rank IC and its t-statistic on non-overlapping dates.
| Sample | IC | t | Wednesdays |
|---|---|---|---|
| Distance below the 12-month high, next three months | |||
| All stocks, whole period | 0.0040 | 0.4 | 1,621 |
| By decade: 1995–2004 | -0.0002 | 0.6 | 516 |
| By decade: 2005–2014 | 0.0210 | 1.0 | 518 |
| By decade: 2015– | -0.0072 | -0.3 | 587 |
| S&P 500 members on the date | 0.0075 | 0.6 | 1,569 |
| Sectors with the overall sign | 9 / 11 |
5Limitations
- The study reads horizons of up to three months. The overreaction De Bondt and Thaler (1985) reported was found in stocks ranked on their returns over the previous three to five years and followed for years afterwards, a horizon this study does not test.
- Stocks far below their high are among the most likely to be delisted. No delisting return is added, so bankruptcies among them are missing from the fallen fifth's results, which is more likely to flatter that fifth than to harm it.
- Before costs. Averages exclude trading costs, taxes and market impact.
- Same-close timing. Returns start at the close the signal is computed from; a real trade would start later.
- Survivors among smaller companies. The non-index names were chosen from companies listed when the universe was built; no delisting returns are added.
6Conclusion
A deep fall below the 12-month high is widely read as a discount. Measured every Wednesday since 1995 against the same day's median stock, the most beaten-down stocks did not go on to beat other stocks by a measurable margin over a session, a week, a month or three months, and neither did the stocks nearest their highs. Some fallen stocks rebound sharply; which ones, the depth of the fall does not say.
References
- De Bondt, W. F. M. and Thaler, R. (1985). Does the Stock Market Overreact? Journal of Finance 40(3).
- George, T. J. and Hwang, C.-Y. (2004). The 52-Week High and Momentum Investing. Journal of Finance 59(5).
- Benjamini, Y. and Hochberg, Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society, Series B 57(1).
- Grinold, R. C. and Kahn, R. N. (2000). Active Portfolio Management, 2nd ed. McGraw-Hill.
- Harvey, C. R., Liu, Y. and Zhu, H. (2016). … and the Cross-Section of Expected Returns. Review of Financial Studies 29(1).
- Shumway, T. (1997). The Delisting Bias in CRSP Data. Journal of Finance 52(1).
Appendix A. Questions readers ask
- Do beaten-down stocks bounce back?
- Not as a rule. Since 1995, the fifth of US stocks furthest below their 12-month high beat the same day's median stock over the next three months 49 times in 100, against 50 for a coin flip. Some rebound sharply and lift the fifth's average, but the typical fallen stock did no better than the typical stock.
- Do stocks near their 52-week high do better?
- Not in this measure either. George and Hwang (2004) found that they did in earlier decades; here the fifth of stocks nearest their 12-month high beat the median stock over the next three months 49 times in 100. Across the whole ranking, the rank correlation between distance from the high and the next three months was 0.004, with a t-statistic of 0.4.
- Why doesn't a big fall predict a rebound?
- A deep fall below the year's high gathers two kinds of stock: companies whose price overshot and companies whose business has truly worsened. The price alone cannot tell them apart, and measured across all of them, the depth of the fall carried no measurable information about the next three months.
- How were beaten-down stocks measured?
- Every Wednesday from Jan 4, 1995 to Aug 19, 2026, the stocks of the same universe of 1,767 US stocks every study uses were ranked by how far their close sat below the highest close of the past 252 sessions, cut into fifths, and compared with the same day's median stock over the next 1, 5, 21 and 63 trading sessions.
Data availability and citation
Every figure in this paper is quoted from one frozen snapshot, published as JSON with the sample description, the robustness results and the test counts. The same snapshot feeds the research console, so the two cannot disagree.
Opulence Alpha Research (2026). Do beaten-down stocks bounce back? Opulence Alpha Studies, Sep 25, 2026. https://opulencealpha.ai/studies/beaten-down-stocks
Research, not advice. A measured tendency across hundreds of stocks is a nudge for any one of them, never a forecast of its price.