How we tested this pattern
- Sample
- 4,708 occurrences on 6 markets (crypto, forex, US stocks, ETFs, indices and commodities), 1974 to 2026.
- Detection
- Found by code, never picked by hand: every match of the rule on full price history, winners and losers alike.Five or six alternating swing points: both lines falling (at least 30% of the height each), the upper one faster by at least 30%, final width at most 60% of the initial one. Every swing point lies within 10% of the pattern height of its line, no close strays more than 10% outside the lines while the pattern forms, the pattern is at least 3 ATR tall with at least 3 bars between swing points, and the breakout comes within half the pattern duration after the last point. The standard grade, which accepts most counted occurrences, adds a looser pass: at least 2 ATR tall, swing points within 15% of their lines.
- Benchmark
- Each occurrence is compared with the same assets on random bars: the move 10 bars later, and a 2:1 reward-to-risk trade.
- Checks
- Block bootstrap and a correction for the thousands of tests we run, plus a random-walk self-test that the bench passes: on random prices, no pattern should win.
- Updated
- Data updated November 5, 2026, code version c2a1683f. Read the methodology · Raw data (JSON)
At a glance: what textbooks say, what we measured
- Direction
- Bullish
- Occurrences tested
- 4,708 occurrences, all markets, daily
- Textbook: price should rise after it
- Too close to call · −0.05% vs the market, 10 bars
- Textbook: target reached most of the time
- 34.0% vs 32.2% on random dates, all markets, daily, upward breakouts
- Where it did best, US stocks left out
- Crypto, 4-hour, upward breakouts: +0.16 R 2:1 trade vs random dates, not proven
- Verdict
- 10-bar move: No clear edge2:1 trade: No clear edge
On this page
- What is a falling wedge pattern?
- Types of falling wedge
- Key characteristics of the falling wedge pattern
- How to identify a falling wedge on a chart
- How to find falling wedges
- The psychology behind the falling wedge
- How to trade the falling wedge pattern
- Advanced trading strategies
- Real-world examples of falling wedge breakouts
- Reliability, limitations, and risks
- Frequently asked questions
- Conclusion: what the falling wedge can and cannot do
The falling wedge pattern is one of the best known shapes in technical analysis: two converging trendlines that both slope down, with lower highs and lower lows that get closer together. It is read as a bullish signal. We tested it on 4,708 upside breakouts on daily charts, and the numbers are less clear cut than that reading suggests. Here you will learn how to identify the wedge, how traders use it, and what really happened after the break.
What is a falling wedge pattern?
Definition and core concept
A falling wedge is a price structure made of two lines that both point down and converge. The top boundary joins the lower highs, the bottom boundary joins the lower lows, and the top falls faster than the bottom. Price keeps making new lows, but each push down covers less distance than the one before: sellers are still in control of the trend, but their force is fading. It is a consolidation phase within a downward move.
In our test bench, the rule is precise: five or six alternating pivots, both lines falling, the top one steeper, and a breakout defined as the first close outside the lines before they meet.
The chart above is not drawn by hand. It is the median shape of the falling wedges our bench detected, with the entry at the breakout close, the stop on the bottom boundary and an objective at twice the risk.
Is a falling wedge bullish or bearish?
The falling wedge is read as bullish. After a downtrend, it is treated as a reversal pattern; within an uptrend, as a pause during a pullback, so a continuation signal. In both cases traders expect the price to break through the upper boundary of the wedge. On daily charts, 78.5% of the wedges that broke out went up (4,708 up against 1,287 down). That does not confirm the reading: on random prices, in our three self-test worlds, 72 to 77% of falling wedges also exit up, so the side comes mostly from the construction of the shape. The question is what happened next.
Types of falling wedge
The same shape plays two roles depending on the trend that comes before it. It is important to know which one you are looking at, because the market context changes how traders read the signal.
- Reversal wedge: it forms at the end of a long downtrend. The wedge is the last phase of the decline, a base from which price may turn up.
- Continuation wedge: it forms as a correction within an uptrend. The wedge is a consolidation phase, and the breakout is expected to resume the trend.
Our bench does not require a prior trend, so its statistics mix both types. In terms of shape, the two are identical: only the price history before the wedge tells them apart.
As a reversal at the end of a downtrend, the falling wedge competes with bottoms such as the inverse head and shoulders pattern and the double bottom. The wedge is read from two converging falling lines, the others from the lows themselves.
Key characteristics of the falling wedge pattern
- First low
- First high
- Lower lowlower line falls slower
- Lower highupper line falls faster
- Lowest lowthe lines converge
- Close above the upper line
Shape and slope
To identify a valid falling wedge, a trader checks four technical points:
- Two falling lines that converge toward an apex.
- A series of lower highs on top and a series of lower lows at the bottom, with at least two pivots on each line. Lower highs act as a falling resistance; lower lows show that support keeps giving way.
- A steeper top boundary: the highs fall faster than the lows.
- A narrowing trading range as the consolidation matures.
Volume dynamics during formation
Classic technical analysis says volume should shrink during the consolidation and expand on the break. Price action becomes quieter as the range narrows. Falling volume is read as fading selling interest, and a jump in volume as new demand. We measured the second part: see the volume section below.
Duration and maturity
A wedge can last a few sessions on a 15 min chart or many weeks on weekly bars. What matters is the number of touches, not the clock. In our bench, a wedge needs five or six alternating pivots, and it expires if no breakout comes by the apex or within half its duration after the last pivot (a full duration on the looser standard grade): 99.7% of the daily wedges we detected broke out in time.
How to identify a falling wedge on a chart
Drawing trendlines correctly
Draw the top trendline through at least two lower highs and the bottom one through at least two lower lows. Use the same rule every time, wicks or closes, and never move the lines to make the shape fit. Each new pivot should respect the pattern: lower highs on the top line, lower lows on the bottom one. If the lines are parallel, it is not a wedge. If they diverge, it is a broadening shape. Drawing tools in TradingView or any desktop charting platform make this quick, but the decisions about which pivots to join remain yours, and two traders may not draw the same wedge.
Distinguishing from other patterns
Several chart formations look alike. Two comparisons help.
Falling wedge vs. descending triangle
A descending triangle has a flat support and falling highs: buyers defend the same price every time. In a falling wedge, the lows keep falling too, so there is no fixed support: the lower lows replace the flat floor. The descending triangle is read as bearish, the falling wedge as bullish.
Falling wedge vs. falling channel
In a down-sloping parallel range, the two boundaries never meet: the downtrend keeps its pace. In a falling wedge the lines converge, which is the sign of a slowing decline. The difference matters for the stop: a parallel range gives no apex and no deadline.
A small falling wedge can also form as the handle of a cup and handle pattern, after the price has rebuilt the rim of a rounded base. A short, symmetrical consolidation right after a sharp rise is a pennant pattern instead: a falling wedge slopes against the trend and lasts longer.
How to find falling wedges
You can find wedge patterns by eye or with a scanner. Charting platforms offer drawing tools, and some offer pattern scanners as paid options. Traders who code can pull price data from an exchange API and run their own detection rules. Our bench works this way: the same fixed rule is applied to every market, so a wedge is never picked after the fact.
Be careful with charts shared on social media. A wedge drawn after the breakout always looks clean, because the person who shares it already knows the outcome. The only fair test is a rule that is fixed before the price action happens.
The psychology behind the falling wedge
Market sentiment and exhaustion
The classical reading is a story of exhaustion: each new low attracts fewer sellers. The lower highs show that sellers still act on every rally, at a falling resistance, but the shrinking distance between the lines shows indecision: neither side pushes hard. Market sentiment is still negative, yet the selling force is getting weaker. The bears no longer push price to new lows with the same strength, and the bulls begin to defend each dip.
Why the breakout occurs
Every bearish leg ends sooner than the one before, and every rally fails a little lower. These bearish signals weaken as the lines converge.
When price closes above the upper line, traders who were short have a reason to cover, and those who were waiting have a clear point to act. That demand can feed the move. This is the theory, and it is how breakout strategies built on wedge patterns work: the trader waits, then acts on the break. Whether it works better than chance is a question for the data.
How to trade the falling wedge pattern
- Entry
- Close outside the lines, in the direction of the breakout
- Stop loss (SL)
- On the opposite line, at its level on the breakout bar
- Target (TP)
- Twice the risk (2:1)
A clean case from our bench: US stocksChosen on its shape alone, never on the outcome. A result above +2 R or below −1 R means a bar opened past the target or the stop, and the trade was closed at that open. Stock prices are adjusted for splits and dividends, so they can differ from the prices quoted at the time.
Determining the entry point
The simplest entry is a close above the upper trendline. A more cautious technique waits for a retest of the broken boundary, which then acts as support. Our bench buys the first close above the top, without waiting.
Setting a stop-loss
Establishing a profit target
The textbook target adds the height of the wedge at its widest point to the breakout level, the measured move. Our bench uses a simpler, fixed rule: an objective at twice the distance to the stop, a 2:1 ratio of rewards to risk, and an exit after 100 bars if neither level is reached. On daily charts, winning trades took a median of 34 bars to get there, and losing trades a median of 21 bars to hit the stop.
Advanced trading strategies
Using volume as a confirmation signal
We tested the classic rule. Daily upside breakouts on volume above 1.5 times the 20-bar average reached the 2:1 objective in 28.4% of cases (expectancy +0.19 R), against 32.9% on normal volume (+0.23 R). High volume did not make the break more reliable, and a breakout on low volume was not a weaker signal in our data. These breakdowns are descriptive and not corrected for the number of tests.
Incorporating technical indicators
The wedge can be combined with an indicator. Here are two techniques.
Moving averages and the falling wedge
Breakouts above the 200-day moving average reached the objective in 33.5% of cases (+0.21 R), against 31.6% below it (+0.23 R). The long-term trend barely changed the result: on our data, the trend filter did not turn the wedge into an edge.
Relative strength index (RSI) divergence
One confirmation signal is a bullish RSI divergence: price makes a lower low while the RSI makes a higher low. It fits the idea of a slowing decline. We have not tested it, so treat it as an idea to check, not a rule. On crypto, on-chain signals are another possible filter; we have not tested those either.
Real-world examples of falling wedge breakouts
Two real cases from our bench: one breakout that held while the trade failed, and one wedge that broke down instead of up. Each one shows the price action, the levels and the result. The gallery of this section shows more cases.
Real occurrences from our test bench, each on its market's main timeframe. Crypto and US stock examples come from liquid assets only (the largest coins, the most traded stocks). Best and Worst are the best and worst 2:1 trade results, Textbook the cleanest shapes (chosen on geometry alone, never on the outcome), Most recent the latest detections among the assets the gallery draws from, Typical a random draw. Shaded area: the pattern. Dashed lines: entry, stop loss (SL) and 2:1 target (TP) of the tested trade. Dotted line: 10 bars after the signal. A result above +2 R or below −1 R means a bar opened past the target or the stop, and the trade was closed at that open. Stock prices are adjusted for splits and dividends, so they can differ from the prices quoted at the time. We left out 1 card with a bar far out of line with the bars around it (a likely bad quote). It still counts in the statistics, and is not replaced: our bench picks a fixed number of cards per category.
Falling wedge in cryptocurrency charts: a breakout that held, a trade that failed
ETC/USDT formed a falling wedge from June 3, 2019: highs at 9.8699, 7.6742 (August 22) and 5.2233 (October 9), lows at 5.1015 (July 15) and 4.1 (September 24). Price action broke out on October 29, 2019 with a close at 4.9239. The stop went on the bottom boundary at 3.6063 and the objective at 7.559. Ten days later the coin was 1.0% above the entry, but it peaked at 5.3794 on November 7, far short of the goal, and fell through the stop on November 22, 2019. The breakout itself held for 10 days, but the trade was stopped out at a loss of 1 R: a good beginning says little about the outcome.
A wedge that broke down instead of up
XRP/USDT made lower highs at 0.93 (March 28, 2022), 0.7999 (April 16) and 0.6572 (May 5), with lower lows at 0.6802 (April 11) and 0.5663 (April 30). Instead of breaking up, it closed at 0.4873 on May 9, 2022, below the bottom boundary, and was 13.7% lower ten days later. A trader who had bought inside the wedge, on the idea that it must go up, took the full drop. Our bench traded that break short, with a stop at 0.6306, and the trade ended after 100 bars with a gain of 0.75 R.
Falling wedge in stock trading and forex markets
On US stocks, daily upside breakouts reached the 2:1 objective in 32.3% of cases, against 29.5% for the same rule on random dates. On forex hourly charts, 25.1% against 24.2%, with an expectancy of +0.05 R before costs. The stock trader and the forex trader face the same result: on both markets, the pattern hit its target a little more often, but its average result per trade did not differ from the same trade on random dates by more than chance can explain. Details are in the table below.
Reliability, limitations, and risks
On upward breakouts: moved the expected way 10 bars later, compared with random bars.
Measured on 4,708 daily falling wedge occurrences with upward breakouts across 1,759 assets. Random bars on the same assets are the honest baseline.
No clear edgeFalling wedge against random bars on the same assets, by market, on daily candles. Bars of almost the same length mean no edge.
- All markets
- Crypto
- US stocks
- Forex
- ETFs
- Indices
- Commodities
- All markets
- Crypto
- US stocks
- Forex
- ETFs
- Indices
- Commodities
All statistics
Full results for the falling wedge pattern, market by market
Every occurrence our rule finds on full price history, compared with what the same assets did on random bars. A pattern only earns an edge if it beats random entries after correcting for the thousands of tests we run.
Our verdict
Not a reliable signal on its own here. Use it as context, not as a trigger.
Falling wedge: 4,708 occurrences tested
Bullish pattern · All markets · Daily · Upward breakout · 1,759 assets · 1974-12 to 2026-10
What this means. No measurable difference from the rest of its market over the next 10 bars.
Timeline
- Pattern length, first swing to breakout
- 65 days · middle half 48 to 95 · on 4,708 occurrences
- Breakout, after the last swing
- 4 days · middle half 2 to 7 · on 4,708 occurrences
- Time to the 2:1 target, when hit
- 34 days · middle half 18 to 60 · on 1,476 trades that hit it
- Time to the stop, when hit
- 21 days · middle half 10 to 44 · on 2,271 trades that hit it
- Time in the trade, all exits
- 35 days · middle half 15 to 81 · on 4,640 trades
- Measured-move target reached, when hit
- 35 days · middle half 19 to 58 · on the occurrences that reached it
- Pattern height projected from the breakout
Size and trade path
- Pattern height
- 26.2% · middle half 16.6% to 47.2% · on 4,708 occurrences
- Best open profit during the trade
- 1.13 R · middle half 0.41 R to 2.04 R · on 4,640 trades
- Stopped trades that were first up 1 R
- 20.5% · on 2,271 stopped trades
- Trades a stop moved to breakeven at +1 R would have closed flat instead of at a loss
Medians, each on the cases named on its line; "middle half" spans the 25th to 75th percentile; no value under 30 cases.
How we detect it. Five or six alternating swing points: both lines falling (at least 30% of the height each), the upper one faster by at least 30%, final width at most 60% of the initial one. Every swing point lies within 10% of the pattern height of its line, no close strays more than 10% outside the lines while the pattern forms, the pattern is at least 3 ATR tall with at least 3 bars between swing points, and the breakout comes within half the pattern duration after the last point. The standard grade, which accepts most counted occurrences, adds a looser pass: at least 2 ATR tall, swing points within 15% of their lines.
All measurements (40 rows)
10-bar move: did price go the expected way?
| Market | Occurrences | Pattern | Random bars | Excess | 10-bar move verdict |
|---|---|---|---|---|---|
| Crypto · 1-hour · Upward breakout | 9,374 | 50.2% | 48.1% | −0.02% | No clear edge |
| Crypto · 1-hour · Downward breakout | 3,058 | 45.5% | 50.8% | −0.06% | No clear edge |
| Forex · 1-hour · Upward breakout | 1,299 | 51.6% | 50.5% | +0.02% | Promising |
| Forex · 1-hour · Downward breakout | 486 | 42.7% | 49.4% | −0.03% | Weak, below chance |
| All markets · 1-hour · Upward breakout | 10,673 | 50.4% | 48.4% | −0.01% | No clear edge |
| All markets · 1-hour · Downward breakout | 3,544 | 45.1% | 50.6% | −0.06% | No clear edge |
| Crypto · 4-hour · Upward breakout | 2,823 | 52.1% | 47.1% | −0.02% | No clear edge |
| Crypto · 4-hour · Downward breakout | 976 | 52.9% | 52.5% | +0.09% | No clear edge |
| Forex · 4-hour · Upward breakout | 349 | 52.9% | 50.4% | +0.01% | No clear edge |
| Forex · 4-hour · Downward breakout | 116 | 50.0% | 49.7% | −0.01% | No clear edge |
| All markets · 4-hour · Upward breakout | 3,172 | 52.2% | 47.5% | −0.02% | No clear edge |
| All markets · 4-hour · Downward breakout | 1,092 | 52.6% | 52.2% | +0.08% | No clear edge |
| Crypto · Daily · Upward breakout | 629 | 45.5% | 44.0% | −0.18% | No clear edge |
| Crypto · Daily · Downward breakout | 106 | 41.9% | 56.8% | −0.01% | No clear edge |
| US stocks · Daily · Upward breakout | 3,768 | 55.7% | 53.6% | −0.06% | No clear edge |
| US stocks · Daily · Downward breakout | 1,090 | 43.4% | 46.1% | −0.58% | No clear edge |
| ETFs · Daily · Upward breakout | 124 | 59.7% | 55.3% | +0.73% | No clear edge |
| ETFs · Daily · Downward breakout | 38 | 50.0% | 44.1% | +0.26% | No clear edge |
| Indices · Daily · Upward breakout | 63 | 54.0% | 56.4% | +0.26% | No clear edge |
| Indices · Daily · Downward breakout | 21 | 19.0% | 44.2% | −0.83% | Not enough data |
| Forex · Daily · Upward breakout | 60 | 49.2% | 50.0% | −0.05% | No clear edge |
| Forex · Daily · Downward breakout | 16 | 62.5% | 50.9% | +0.37% | Not enough data |
| Commodities · Daily · Upward breakout | 64 | 43.8% | 51.3% | −0.01% | No clear edge |
| Commodities · Daily · Downward breakout | 16 | 60.0% | 49.1% | +0.22% | Not enough data |
| All markets · Daily · Upward breakout | 4,708 | 54.1% | 52.4% | −0.05% | No clear edge |
| All markets · Daily · Downward breakout | 1,287 | 43.5% | 47.0% | −0.49% | No clear edge |
| Crypto · Weekly · Upward breakout | 58 | 29.1% | 37.1% | +0.33% | Not enough data |
| Crypto · Weekly · Downward breakout | 4 | 75.0% | 64.7% | +7.20% | Not enough data |
| US stocks · Weekly · Upward breakout | 481 | 59.2% | 55.5% | +0.65% | No clear edge |
| US stocks · Weekly · Downward breakout | 113 | 49.1% | 44.9% | +1.93% | No clear edge |
| ETFs · Weekly · Upward breakout | 27 | 55.6% | 57.7% | +0.55% | Not enough data |
| ETFs · Weekly · Downward breakout | 6 | 16.7% | 38.5% | −0.14% | Not enough data |
| Indices · Weekly · Upward breakout | 10 | 80.0% | 63.1% | +1.30% | Not enough data |
| Indices · Weekly · Downward breakout | 5 | 40.0% | 37.7% | −0.96% | Not enough data |
| Forex · Weekly · Upward breakout | 6 | 40.0% | 47.7% | +0.54% | Not enough data |
| Forex · Weekly · Downward breakout | 5 | 60.0% | 56.0% | +2.84% | Not enough data |
| Commodities · Weekly · Upward breakout | 13 | 53.8% | 52.3% | +1.68% | Not enough data |
| Commodities · Weekly · Downward breakout | 2 | 0.0% | 46.7% | −7.58% | Not enough data |
| All markets · Weekly · Upward breakout | 595 | 56.3% | 53.9% | +0.65% | No clear edge |
| All markets · Weekly · Downward breakout | 135 | 47.8% | 45.4% | +1.78% | No clear edge |
2:1 trade: target hit and average result
| Market | Trades | Target hit | Same trade, random dates | Per trade | 2:1 trade verdict |
|---|---|---|---|---|---|
| Crypto · 1-hour · Upward breakout | 9,347 | 25.3% | 24.0% | +0.05 R vs 0.00 R | No clear edge |
| Crypto · 1-hour · Downward breakout | 3,045 | 23.7% | 22.9% | 0.00 R vs +0.01 R | No clear edge |
| Forex · 1-hour · Upward breakout | 1,296 | 25.1% | 24.2% | +0.05 R vs 0.00 R | No clear edge |
| Forex · 1-hour · Downward breakout | 486 | 22.8% | 26.1% | −0.08 R vs +0.02 R | No clear edge |
| All markets · 1-hour · Upward breakout | 10,643 | 25.2% | 24.1% | +0.05 R vs 0.00 R | No clear edge |
| All markets · 1-hour · Downward breakout | 3,531 | 23.6% | 23.3% | −0.01 R vs +0.01 R | No clear edge |
| Crypto · 4-hour · Upward breakout | 2,800 | 28.9% | 24.5% | +0.13 R vs −0.03 R | Promising |
| Crypto · 4-hour · Downward breakout | 948 | 17.9% | 23.3% | −0.14 R vs +0.06 R | No clear edge |
| Forex · 4-hour · Upward breakout | 347 | 25.9% | 24.1% | +0.09 R vs −0.01 R | No clear edge |
| Forex · 4-hour · Downward breakout | 116 | 23.3% | 23.3% | −0.13 R vs −0.03 R | No clear edge |
| All markets · 4-hour · Upward breakout | 3,147 | 28.6% | 24.5% | +0.13 R vs −0.02 R | Promising |
| All markets · 4-hour · Downward breakout | 1,064 | 18.5% | 23.3% | −0.14 R vs +0.05 R | No clear edge |
| Crypto · Daily · Upward breakout | 622 | 31.7% | 27.8% | +0.25 R vs +0.07 R | No clear edge |
| Crypto · Daily · Downward breakout | 69 | 20.3% | 16.4% | +0.15 R vs −0.03 R | No clear edge |
| US stocks · Daily · Upward breakout | 3,711 | 32.3% | 29.5% | +0.23 R vs +0.15 R | No clear edge |
| US stocks · Daily · Downward breakout | 1,052 | 18.7% | 19.4% | −0.21 R vs −0.20 R | No clear edge |
| ETFs · Daily · Upward breakout | 124 | 31.5% | 27.0% | +0.29 R vs +0.14 R | No clear edge |
| ETFs · Daily · Downward breakout | 38 | 23.7% | 25.0% | −0.10 R vs −0.15 R | No clear edge |
| Indices · Daily · Upward breakout | 63 | 22.2% | 26.9% | −0.06 R vs +0.10 R | No clear edge |
| Indices · Daily · Downward breakout | 21 | 14.3% | 23.8% | −0.45 R vs +0.01 R | Not enough data |
| Forex · Daily · Upward breakout | 58 | 20.7% | 29.7% | −0.08 R vs +0.04 R | No clear edge |
| Forex · Daily · Downward breakout | 16 | 12.5% | 17.2% | −0.50 R vs −0.22 R | Not enough data |
| Commodities · Daily · Upward breakout | 62 | 22.6% | 30.6% | −0.02 R vs +0.20 R | No clear edge |
| Commodities · Daily · Downward breakout | 15 | 40.0% | 13.3% | +0.42 R vs −0.33 R | Not enough data |
| All markets · Daily · Upward breakout | 4,640 | 31.8% | 29.2% | +0.22 R vs +0.14 R | No clear edge |
| All markets · Daily · Downward breakout | 1,211 | 19.1% | 19.4% | −0.19 R vs −0.19 R | No clear edge |
| Crypto · Weekly · Upward breakout | 31 | 41.9% | 33.3% | +0.47 R vs +0.20 R | Not enough data |
| Crypto · Weekly · Downward breakout | 0 | n/a | n/a | n/a vs n/a | Not enough data |
| US stocks · Weekly · Upward breakout | 456 | 36.4% | 36.3% | +0.36 R vs +0.36 R | No clear edge |
| US stocks · Weekly · Downward breakout | 82 | 17.1% | 14.6% | −0.31 R vs −0.29 R | No clear edge |
| ETFs · Weekly · Upward breakout | 27 | 40.7% | 32.7% | +0.47 R vs +0.17 R | Not enough data |
| ETFs · Weekly · Downward breakout | 6 | 0.0% | 31.9% | −0.90 R vs +0.09 R | Not enough data |
| Indices · Weekly · Upward breakout | 10 | 40.0% | 43.3% | +0.98 R vs +0.58 R | Not enough data |
| Indices · Weekly · Downward breakout | 5 | 20.0% | 0.0% | −0.17 R vs −0.78 R | Not enough data |
| Forex · Weekly · Upward breakout | 5 | 0.0% | 5.0% | −0.24 R vs −0.63 R | Not enough data |
| Forex · Weekly · Downward breakout | 5 | 60.0% | 55.0% | +0.80 R vs +0.70 R | Not enough data |
| Commodities · Weekly · Upward breakout | 13 | 38.5% | 50.6% | +0.42 R vs +0.64 R | Not enough data |
| Commodities · Weekly · Downward breakout | 2 | 0.0% | 37.5% | −1.00 R vs +0.13 R | Not enough data |
| All markets · Weekly · Upward breakout | 542 | 36.7% | 36.2% | +0.38 R vs +0.34 R | No clear edge |
| All markets · Weekly · Downward breakout | 100 | 18.0% | 17.4% | −0.30 R vs −0.24 R | No clear edge |
After the breakout
| Market | Occurrences | False starts | Same, random dates | Throwbacks |
|---|---|---|---|---|
| Crypto · 1-hour · Upward breakout | 9,374 | 51.2% | 52.9% | 75.3% |
| Crypto · 1-hour · Downward breakout | 3,058 | 53.6% | 51.7% | 72.1% |
| Forex · 1-hour · Upward breakout | 1,299 | 51.1% | 53.4% | 79.0% |
| Forex · 1-hour · Downward breakout | 486 | 56.8% | 52.7% | 73.6% |
| All markets · 1-hour · Upward breakout | 10,673 | 51.2% | 53.0% | 75.8% |
| All markets · 1-hour · Downward breakout | 3,544 | 54.1% | 51.8% | 72.3% |
| Crypto · 4-hour · Upward breakout | 2,823 | 46.2% | 55.0% | 76.8% |
| Crypto · 4-hour · Downward breakout | 976 | 54.2% | 50.7% | 74.1% |
| Forex · 4-hour · Upward breakout | 349 | 48.8% | 51.9% | 75.3% |
| Forex · 4-hour · Downward breakout | 116 | 64.3% | 54.8% | 73.0% |
| All markets · 4-hour · Upward breakout | 3,172 | 46.5% | 54.7% | 76.6% |
| All markets · 4-hour · Downward breakout | 1,092 | 55.2% | 51.1% | 74.0% |
| Crypto · Daily · Upward breakout | 629 | 43.8% | 52.2% | 77.6% |
| Crypto · Daily · Downward breakout | 106 | 44.6% | 44.3% | 60.6% |
| US stocks · Daily · Upward breakout | 3,768 | 44.3% | 47.2% | 75.0% |
| US stocks · Daily · Downward breakout | 1,090 | 60.8% | 59.3% | 71.7% |
| ETFs · Daily · Upward breakout | 124 | 44.9% | 47.1% | 71.9% |
| ETFs · Daily · Downward breakout | 38 | 50.0% | 56.6% | 63.2% |
| Indices · Daily · Upward breakout | 63 | 47.6% | 48.7% | 73.0% |
| Indices · Daily · Downward breakout | 21 | 66.7% | 50.0% | 61.9% |
| Forex · Daily · Upward breakout | 60 | 60.0% | 50.6% | 73.7% |
| Forex · Daily · Downward breakout | 16 | 56.3% | 60.9% | 75.0% |
| Commodities · Daily · Upward breakout | 64 | 46.8% | 41.3% | 88.9% |
| Commodities · Daily · Downward breakout | 16 | 40.0% | 65.6% | 66.7% |
| All markets · Daily · Upward breakout | 4,708 | 44.5% | 47.9% | 75.4% |
| All markets · Daily · Downward breakout | 1,287 | 58.9% | 57.9% | 70.3% |
| Crypto · Weekly · Upward breakout | 58 | 5.0% | 24.8% | 75.9% |
| Crypto · Weekly · Downward breakout | 4 | 100.0% | 37.5% | 100.0% |
| US stocks · Weekly · Upward breakout | 481 | 40.8% | 39.3% | 72.8% |
| US stocks · Weekly · Downward breakout | 113 | 57.3% | 58.3% | 73.5% |
| ETFs · Weekly · Upward breakout | 27 | 40.0% | 50.6% | 74.1% |
| ETFs · Weekly · Downward breakout | 6 | 83.3% | 45.8% | 66.7% |
| Indices · Weekly · Upward breakout | 10 | 20.0% | 36.7% | 70.0% |
| Indices · Weekly · Downward breakout | 5 | 40.0% | 40.0% | 20.0% |
| Forex · Weekly · Upward breakout | 6 | 80.0% | 65.3% | 60.0% |
| Forex · Weekly · Downward breakout | 5 | 20.0% | 31.7% | 60.0% |
| Commodities · Weekly · Upward breakout | 13 | 22.2% | 37.8% | 76.9% |
| Commodities · Weekly · Downward breakout | 2 | 100.0% | 62.5% | 50.0% |
| All markets · Weekly · Upward breakout | 595 | 38.9% | 39.1% | 73.0% |
| All markets · Weekly · Downward breakout | 135 | 57.4% | 55.7% | 70.3% |
Data updated November 5, 2026 · code version c2a1683f · Read the methodology. We measure every pattern on crypto and forex (1-hour, 4-hour, daily and weekly charts) and US stocks, ETFs, indices and commodities (daily and weekly charts). A market or timeframe from that list missing from the tables above had no occurrence.
Success rates and performance statistics
Here are the numbers from our test bench. Each row compares the falling wedge with random bars of the same assets, and the 2:1 rule with the same levels placed on random dates.
What you often read
“The falling wedge pattern is a reliable bullish signal.”
What our data shows
On 4,708 daily occurrences with upward breakouts, it moved in the expected direction 54.1% of the time, against 52.4% for random bars: no clear edge, since the average excess return is not statistically significant.
Table quoted in the text (verdicts and every market: see All measurements)
| Market, timeframe and breakout side | Breakouts (2:1 trades) | Moved with the breakout 10 bars later | Random bars | 2:1 objective reached | Same levels, random dates | Expectancy |
|---|---|---|---|---|---|---|
| All markets, daily, up | 4,708 (4,640) | 54.1% | 52.4% | 31.8% | 29.2% | +0.22 R |
| All markets, daily, down | 1,287 (1,211) | 43.5% | 47.0% | 19.1% | 19.4% | −0.19 R |
| US stocks, daily, up | 3,768 (3,711) | 55.7% | 53.6% | 32.3% | 29.5% | +0.23 R |
| Cryptocurrencies, daily, up | 629 (622) | 45.5% | 44.0% | 31.7% | 27.8% | +0.25 R |
| Cryptocurrencies, hourly, up | 9,374 (9,347) | 50.2% | 48.1% | 25.3% | 24.0% | +0.05 R |
| All markets, 4-hour, up | 3,172 (3,147) | 52.2% | 47.5% | 28.6% | 24.5% | +0.13 R |
| Forex, hourly, up | 1,299 (1,296) | 51.6% | 50.5% | 25.1% | 24.2% | +0.05 R |
| All markets, weekly, up | 595 (542) | 56.3% | 53.9% | 36.7% | 36.2% | +0.38 R |
Read the columns in pairs. On daily charts, 54.1% of upside breakouts were followed by a rise 10 days later, against 52.4% for random days on the same assets. The excess return over the rest of the market after 10 days is −0.05%, with a 95% confidence interval from −0.29% to +0.23%: zero is within it, so no clear edge.
The trades look better at first sight: +0.22 R each before costs. But the same entry, stop and objective on random dates averaged +0.14 R. Most of that gain came from the long-term rise of the assets and the 2:1 rule: the extra over random dates is too small to rule out chance. No row in the table shows a proven edge: the 4-hour trade (rated promising) and the hourly forex move after 10 bars (rated promising) pass a simple test but not our correction for multiple testing; the hourly trade, all markets together (10,643 trades, 25.2% of targets reached against 24.1% on random dates, +0.05 R against 0.00 R, rated no clear edge), does not pass even a simple test; and the daily result was close to zero in both halves of history (+0.05% and −0.15%). Academic work points the same way: in "Foundations of Technical Analysis" (Journal of Finance, 2000), Andrew Lo, Harry Mamaysky and Jiang Wang detected chart formations automatically on US stocks and found modest information in some of them, without showing that they could be traded for a profit.
When does a falling wedge pattern fail?
Most trades did not reach the objective on daily charts (only 31.8% did), and of the trades that hit their stop, 20.5% had first reached +1 R. Tall wedges reached the objective less often than short ones: 27.6% of the trades on tall wedges (+0.20 R per trade), against 36.0% on short ones (+0.24 R). Wedges measured on larger moves (pivots 4 ATR apart) reached it 18.6% of the time (+0.19 R), against 35.1% at 2 ATR (+0.23 R). Downside breaks are a separate case: 1,287 daily wedges broke down, and the short trade on those breaks lost money (−0.19 R on 1,211 closed trades, against −0.19 R on random dates). We did not test what a break of the lower line means for a trader already long, so treat any exit rule there as your own risk decision, not a tested signal.
Risk management rules for pattern traders
- Define the stop-loss before you buy, and size positions on that distance.
- Keep the amount at stake small: a long run of losing trades is normal with a hit rate near one in three.
- Include costs: our results are before fees and slippage on transactions, and many small transactions add up.
- Log every signal, winners and losers, and compare with random entries. A trader who tracks performance learns more from losing signals than from winners.
Frequently asked questions
Is the falling wedge a reversal or continuation pattern?
Both. After a downtrend it is read as a reversal pattern; during an uptrend, as a pause. The expected direction is up in both cases.
How long should you wait for a breakout?
Until price closes outside the lines or reaches the apex. In our bench, the limit is half the wedge's duration after its last pivot (a full duration on the looser standard grade): 99.7% of daily wedges broke out in time; the others expired.
Can a falling wedge appear in any timeframe?
Yes. We found it on hourly, 4-hour, daily and weekly bars, about once every 1,801 eligible bars for upward breakouts on daily charts, over millions of bars of history.
How often does a falling wedge reach its objective?
On daily charts, 31.8% of upside breakouts reached a 2:1 objective, against 29.2% for the same levels on random dates. On weekly charts, 36.7% against 36.2%. The hit rate is higher than on random dates, but the average result per trade is not higher by a margin our test counts as an edge: +0.22 R against +0.14 R on daily charts, +0.38 R against +0.34 R on weekly charts.
Is the falling wedge the most powerful pattern in trading?
No pattern has that title on our data. The falling wedge is appealing because its lines are easy to draw and its stop-loss is clear, but it showed no proven edge over random entries on any market we tested. The best signals for a trader are the ones tested on their own market, with costs.
What mistake should you avoid when trading wedges?
Buying before the break, on the idea that the wedge must go up. 1,287 daily wedges broke down instead.
What does a rising wedge pattern mean?
The rising wedge is the mirror image: two rising, converging lines, read as bearish. The symmetrical triangle and the ascending triangle are other converging shapes.
Conclusion: what the falling wedge can and cannot do
In conclusion, the falling wedge is easy to spot and gives a clear plan: an entry on the break, a stop on the bottom boundary and an objective. On our data, it broke up far more often than down, as it also does on random prices, and what followed was no better than random bars of the same assets. Treat it as a place to look for a trade, not as a reason for one.
This content is educational and is not investment advice. A change in market conditions can make any past statistic irrelevant. Trading involves a risk of loss, and past statistics do not guarantee future results.
About the author and the data. Written by Amaury, founder of PatternsWizard, who is passionate about finance, quantitative trading and data analysis. He built the PatternsWizard test bench, which detects each setup with fixed, published rules on full market history: crypto, forex, US stocks, ETFs, indices and commodities. Trades and win rates are compared with random bars on the same assets, excess returns with the rest of the market, with error margins and a correction for multiple testing, and the whole pipeline is checked on random-walk prices, where nothing can be predicted. Statistics on this page were generated on November 5, 2026. The full methodology explains every step.
Passionate about finance, quantitative trading and data analysis. Amaury built the PatternsWizard test bench, which detects each pattern on full price history and measures what happened next against random entries.
Statistics on this page come from our open methodology: every occurrence our rule finds on full history, compared with chance. How we test patterns.