Is the ascending triangle really a bullish pattern?
No. Since 1995, US stocks showing an ascending triangle beat the same day's median stock over the next month 50 times in 100, and over three months 49 times; a coin flip gives 50. At every horizon the reading leaned faintly below chance, too weakly to rely on. Only 26 in 100 reached the drawn target before the stop. No horizon clears the bar for a proven edge.
26 of 100 reached the drawn target before the stop
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: ascending triangle pattern, does the ascending triangle work, ascending triangle breakout, ascending triangle success rate, ascending triangle backtest, bullish triangle pattern·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: 1,550 Wednesdays across 7,959 trading sessions
- Sample
- n = 1,764 stocks of the 1,767-stock universe; 1,361,444 formation detections, a median of 906 per Wednesday
- Outcome
- Return over the next 5, 21 and 63 trading sessions against the same day's median stock; whether the drawn target was reached
- Inference
- Date-clustered intervals; t on non-overlapping dates; proven only when |t| ≥ 3
1Introduction
An ascending triangle is a flat ceiling of roughly equal highs above a floor of rising lows. Chart readers take it as demand slowly absorbing supply at a fixed price, expect a break above the ceiling and project a rise about as tall as the triangle's widest part. It is one of the most commonly taught bullish patterns. This study asks whether stocks showing an ascending triangle go on to beat other stocks, and how often the projected target is reached.
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 formation detection: one stock on one Wednesday on which the pattern detector recorded a formation. Weeks the platform's regime model flags as a likely change of market regime are left out, as are bars flagged as bad data. This study's sample is n = 1,764 stocks of the 1,767: 1,361,444 detections on 1,550 Wednesdays from Jan 4, 1995 to Aug 19, 2026, a median of 906 stocks with a formation per Wednesday. 217,945 detections (16%) come from the 420 companies that have since delisted. Every detection 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 by market volatility.
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 | 283 | 67 | 122 | 76 | 18 | 13.5% | 12.7% |
| Financials | 255 | 59 | 114 | 74 | 8 | 14.7% | 17.2% |
| Industrials | 255 | 52 | 126 | 67 | 11 | 15.9% | 17.5% |
| Health Care | 237 | 47 | 92 | 81 | 16 | 12.3% | 10.9% |
| Consumer Discretionary | 209 | 39 | 69 | 87 | 12 | 12.4% | 12.9% |
| Energy | 105 | 30 | 39 | 31 | 5 | 6% | 4.7% |
| Consumer Staples | 101 | 38 | 40 | 17 | 5 | 5.9% | 4.9% |
| Materials | 95 | 34 | 35 | 24 | 2 | 5.6% | 5.1% |
| Real Estate | 84 | 10 | 40 | 32 | 2 | 5.9% | 6.9% |
| Communication Services | 80 | 31 | 28 | 13 | 5 | 3.9% | 3.3% |
| Utilities | 60 | 13 | 35 | 12 | 0 | 4.1% | 4% |
| All sectors | 1,764 | 420 | 740 | 514 | 84 | 100% | 100% |
Sample: n = 1,764 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 |
|---|---|---|---|
| Ascending triangle | Roughly equal highs forming a flat ceiling above rising lows; bullish, scored on the Wednesday it is detected | Jan 4, 1995 | 1,550 |
2.3Measurement
Outcome. The return from the close on the detection's Wednesday to the close 5, 21 and 63 trading sessions later, in excess of the S&P 500, compared with the same day's median stock, so chance is 50 in 100 on every date; and whether the price reached the formation's drawn target before its stop.
Each detection is scored on its Wednesday: a bullish formation is a hit when the stock beat the same day's median stock, a bearish one when it trailed it. The detector also records whether the price reached the formation's drawn target before its stop (21 sessions for bullish formations, 42 for bearish).
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 the pattern at every horizon, as the share of detections whose stock beat the same day's median stock, which is the call an ascending triangle makes. The share was 49.6 in 100 over the next week, 49.8 over the next month and 49.4 over the next three months: each a fraction below 50, with t-statistics of -2.1, -2.0 and -2.3. None reaches the size a relation needs to count as proven, a t of 3, and every interval still contains 50: a faint lean below chance rather than above it, not reliable on its own.
Share of detections that beat (bullish) or trailed (bearish) the same day's median stock. The line at 50 is chance; the grey band is the range chance produces for this sample (95%, clustered by date).
Share of detections that reached the drawn target before the stop, by the pattern's stage at detection.
The further away the drawn target, the less often it was reached.
Figure 2 asks the chartist's own question. Of every 100 detections, 26 reached the drawn target before the stop within 21 sessions; those that did took a median of 10 sessions. Figure 3 splits the target by stage: 58 in 100 for triangles already past the breakout, 27 for triangles still forming and 13 for broken triangles, whose price had already moved against the pattern. A breakout starts nearer its target by construction, so reaching it more often is not the same as beating other stocks, which Figure 1 measures directly.
The pattern tells a tidy story, rising lows pressing against a flat ceiling, and the triangles that get shared are the ones that broke out. Counted on every stock where the shape appeared, before the outcome was known, the stocks beat other stocks no more often than a coin flip would predict.
4Robustness
Table 3 splits the month's reading by the market's volatility on the detection date: the edge is close to zero in the low, normal and high regimes and below zero in the elevated and extreme ones; none of these splits was tested on its own. Year by year, the pattern's stocks beat the median stock less than half the time in 20 of 32 years and more than half the time in the rest.
Edge over 50 in points at 21 sessions, by the market's volatility regime on the detection date.
| Volatility regime | Detections | Edge, points |
|---|---|---|
| Low | 47.9K | 0.09 |
| Normal | 46.5K | -0.07 |
| Elevated | 17.2K | -1.54 |
| High | 7.3K | -0.01 |
| Extreme | 1.6K | -1.17 |
5Limitations
- The formations are found by a detector working to fixed rules, not drawn by eye; a chartist may pick out different triangles, and may discard some the detector counts.
- The target is graded within 21 sessions; a target reached later counts as a miss.
- 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
The ascending triangle promises a break higher. Measured on every stock where the detector found one, against the same day's median stock, the pattern's stocks beat other stocks no more often than a coin flip would predict, with a faint lean below chance at every horizon that is too weak to rely on. Triangles that had already broken out reached their target more often, as their geometry implies, yet the pattern carried no reliable edge over other stocks.
References
- Lo, A. W., Mamaysky, H. and Wang, J. (2000). Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. Journal of Finance 55(4).
- Bulkowski, T. N. (2005). Encyclopedia of Chart Patterns, 2nd ed. Wiley.
- 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
- Does the ascending triangle pattern work?
- Not as a forecast. Since 1995, stocks showing an ascending triangle beat the same day's median stock over the next month 50 times in 100 and over three months 49 times, against 50 for a coin flip. The small tilt runs below chance, and is too weak to rely on.
- How often does an ascending triangle reach its target?
- Of every 100 detections, 26 reached the target drawn above the triangle before the stop, within 21 sessions. Triangles that had already broken out reached it 58 times in 100; those still forming, 27. Neither figure measures whether the stocks went on to beat other stocks; over the next month they did so 50 times in 100.
- Why do traders trust the ascending triangle?
- The pattern tells a tidy story, rising lows pressing against a flat ceiling, and the triangles that get shared are the ones that broke out. Counted on every stock where the shape appeared, before the outcome was known, the stocks beat other stocks no more often than a coin flip would predict.
- How was the ascending triangle measured?
- Every Wednesday from Jan 4, 1995 to Aug 19, 2026, a pattern detector scanned the same universe of 1,767 US stocks every study uses. Each ascending triangle it found was compared with the same day's median stock over the next 5, 21 and 63 trading sessions, and checked for whether the price reached the drawn target before the stop.
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). Is the ascending triangle really a bullish pattern? Opulence Alpha Studies, Sep 25, 2026. https://opulencealpha.ai/studies/ascending-triangle
Research, not advice. A measured tendency across hundreds of stocks is a nudge for any one of them, never a forecast of its price.