Do stocks that break out to a new 10-day high keep running?
The opposite, by a small margin. Since 1995, US stocks on the day they closed above their 10-day high beat the same day's median stock over the next week 49 times in 100; a coin flip gives 50. The shortfall is small but proven: breakouts lagged in 27 of 32 years. Over the next month (49) and three months (49) no measurable edge remained.
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: breakout trading, do breakouts work, new high breakout, Donchian channel breakout, breakout strategy backtest, 10 day high breakout·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 closes above the highest price of its recent sessions is said to break out, and the breakout rule, which goes back to Richard Donchian's price channels, holds that such a stock tends to keep running. It is one of the most repeated ideas in trend following. This study takes a short form of the rule, a close above the high of the previous 10 sessions, and asks whether stocks that break out go on to beat other stocks over the following week, month and three 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 reads the result horizon by horizon and year by year.
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 |
|---|---|---|---|
| Breakout to a 10-day high | The close rises above the highest high of the previous 10 sessions, counted on the day it happens | Jan 4, 1995 | 1,631 |
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 showing the reading are scored against the same day's median stock. A state counts on every Wednesday it holds; a cross or breakout counts only on the Wednesday it happens.
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 reads every horizon. Stocks closing above their 10-day high beat the median stock 49 times in 100 over the next session, 49 over the next week, 49 over the next month and 49 over the next three months. The week is a proven relation against the breakout and the session a faint one, not reliable on its own; the month and the three months show no measurable edge. Out of every 100 stocks that broke out, 49 beat the median stock over the following week (Figure 2).
Share of stocks showing the reading that beat the same day's median stock, by horizon. The line at 50 is chance, the grey band the range chance alone produces; a filled square is a proven relation.
Each square is one calendar year; filled = a year in which the average stock showing the signal lagged the median stock over the next week. Years are counted, not shown in order.
A signal with an edge would fill most squares, or leave most empty.
The shortfall is a tendency measured across 176.5K breakouts, not a forecast for any one of them, and it is brief: over the next month the breakouts beat the median stock 49 times in 100, too close to a coin flip to count as an edge either way.
A close above the 10-day high comes after a run of strong days. Across US stocks, short-term winners have tended to give back part of their lead over the following days and weeks, a pattern known as short-term reversal (Jegadeesh 1990). It is one plausible reason, and the breakout sits on the wrong side of it.
4Robustness
Table 3 reads the breakout horizon by horizon. Over the next week it lagged the median stock in 27 of 32 years; over the next month it lagged in 22 of 32, but too weakly on average to count as an edge.
Share that beat the median stock, its t-statistic on non-overlapping dates, and the years in which it pointed the same way.
| Horizon | Beat the median | t | Years, same way |
|---|---|---|---|
| Breakout to a 10-day high, session | 49.1 | -4.9 | 22 / 32 |
| Breakout to a 10-day high, week | 48.7 | -5.8 | 27 / 32 |
| Breakout to a 10-day high, month | 49.1 | -1.5 | 22 / 32 |
| Breakout to a 10-day high, three months | 49.2 | -1.9 | 23 / 32 |
5Limitations
- Only the 10-day channel is measured here; the longer channels many traders use, such as 20 or 55 days, are not part of this reading and may behave differently. The 52-week high has its own study.
- A breakout is counted only when it happens on a Wednesday, the day the studies observe; breakouts on other days are not in the sample.
- 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 close above the recent high describes strength that has already happened. Measured against the same day's median stock, stocks that broke out to a new 10-day high did not go on to beat other stocks: over the following week they trailed them, by a small margin that held in most years, and after that they were indistinguishable from the rest. On this evidence, the breakout marks a move already made, not one still to come.
References
- Brock, W., Lakonishok, J. and LeBaron, B. (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. Journal of Finance 47(5).
- Jegadeesh, N. (1990). Evidence of Predictable Behavior of Security Returns. Journal of Finance 45(3).
- Park, C.-H. and Irwin, S. H. (2007). What Do We Know About the Profitability of Technical Analysis? Journal of Economic Surveys 21(4).
- 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 breakouts to new highs work?
- Not as a sign of more to come. Since 1995, US stocks on the day they closed above their 10-day high beat the same day's median stock over the next week 49 times in 100, against 50 for a coin flip. That small shortfall is a proven relation, and it runs against the breakout.
- Do breakouts keep going over the next month?
- Not measurably. Over the next month they beat the median stock 49 times in 100, and over three months 49: a little under a coin flip, within the range chance alone produces.
- Why would a breakout lag?
- A close above the 10-day high comes after a run of strong days. Across US stocks, short-term winners have tended to give back part of their lead over the following days and weeks, a pattern known as short-term reversal (Jegadeesh 1990). It is one plausible reason, and the breakout sits on the wrong side of it.
- How was the breakout measured?
- Every Wednesday from Jan 4, 1995 to Aug 19, 2026, the stocks whose close that day rose above the highest high of the previous 10 sessions were compared with the same day's median stock over the next 1, 5, 21 and 63 trading sessions, on the same universe of 1,767 US stocks every study uses.
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 stocks that break out to a new 10-day high keep running? Opulence Alpha Studies, Sep 25, 2026. https://opulencealpha.ai/studies/breakout-to-new-highs
Research, not advice. A measured tendency across hundreds of stocks is a nudge for any one of them, never a forecast of its price.