Chart patternBullish
Inverse Head and Shoulders Pattern: A Complete Guide to Trading Bullish Reversals
What is the inverse head and shoulders pattern? How to recognize its three lows, how to trade the neckline breakout, and what our bench found market by market.
How we tested this pattern
- Sample
- 5,968 occurrences on 6 markets (crypto, forex, US stocks, ETFs, indices and commodities), 1973 to 2026.
- Detection
- Found by code, never picked by hand: every match of the rule on full price history, winners and losers alike.After a decline: left shoulder, lower head, right shoulder. The close one pattern duration before the left shoulder lies at least 60% of the head depth above the higher neckline peak. Each shoulder falls at least 35% of the head depth below the neckline, shoulders within 20% of each other, head below both by at least 25%, head at least 4 ATR deep, at least 3 bars between swing points, time symmetry between 1:2 and 2:1, neckline slope at most 35% of the head depth. Confirmed by a close above the neckline drawn through the two peaks, within half the pattern duration after the right shoulder. The standard grade, which accepts most counted occurrences, widens this: the head beyond both shoulders by at least 10% of its size, shoulders within 30% of each other and at least 25% of the head size from the neckline, time symmetry between 1:3 and 3:1, a neckline slope of at most 60%, a prior move of at least 30% of the height over the two pattern durations before, a breakout within one pattern duration. The first trough is a true low: from one first-leg duration before the pattern up to that trough, price never fell more than 10% of the pattern height below it.
- 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
- 5,968 occurrences, all markets, daily
- Textbook: price should rise after it
- Too close to call · −0.03% vs the market, 10 bars
- Textbook: target reached most of the time
- 42.1% vs 42.2% on random dates
- Where it did best, US stocks left out
- Crypto, 1-hour: 0.00 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 the inverse head and shoulders pattern?
- Anatomy of the pattern
- Market psychology behind the pattern
- How to identify an inverse head and shoulders on a chart
- Real examples
- Step-by-step trading strategy
- Inverse head and shoulders trading strategies
- Best indicators to confirm the pattern
- Pre-trade checklist
- Avoiding common mistakes and false breakouts
- Reliability and success rate
- Inverse head and shoulders across different markets
- Advanced tips for professional traders
- Advantages and disadvantages of the pattern
- Real-world trading examples
- Scanners and charting software
- Frequently asked questions
- Summary of key points
The inverse head and shoulders pattern is a bullish reversal chart pattern made of three lows: a left shoulder, a lower head, and a right shoulder at roughly the level of the first. A line drawn through the two peaks between those lows is the neckline. When price closes above the neckline following a downtrend, chartists read it as the end of the decline and a potential trend reversal.
This guide covers the definition, how to identify the pattern on a chart, how traders enter, where they put the protective exit and the profit objective, and what actually happened after it. Our test bench detected every inverse head and shoulders pattern on full price history, 5,968 breakouts on daily charts alone across stocks, ETFs, indices, crypto, forex and commodities, and compared the outcome with random days on the same assets.
What is the inverse head and shoulders pattern?
The inverse head and shoulders pattern, also called the inverted head and shoulders pattern or head and shoulders bottom, is the mirror image of the classic head and shoulders pattern. The top version marks the end of an uptrend; the inverse version marks the possible end of a downtrend. It is a classic reversal pattern of technical analysis, described by Richard Schabacker in the 1930s and by Edwards and Magee in Technical Analysis of Stock Trends (1948).
Understanding one point is important before trading it: the pattern only exists once price breaks above the neckline on a closing basis. Before that, three troughs with a lower one in the middle are just a range at the bottom of a decline: on daily charts, 70.9% of the formations our bench found went on to break the neckline, and the rest did not.
It is easy to see on a past chart and harder to trade in real time, which is why understanding how it is validated matters.
Anatomy of the pattern
An inverse head and shoulders pattern has four parts. Each one tells you something about the balance between buyers and sellers.
- High before the declinethe pattern comes after a decline
- Left shoulder
- Left peak
- Headbelow both shoulders by at least 25% of its height (10% at the standard grade)
- Right peak
- Neckline
- Right shoulderwithin 20% of the head height of the left one (30% at the standard grade)
- Close above the necklineconfirms the pattern
The chart above is not drawn by hand. It is the median form of the real inverse head and shoulders patterns our bench drew at random from all markets. One detail stands out: on the median pattern, the second peak sits under the first, so the neckline slopes down slightly. A perfectly flat neckline is the textbook picture, not the typical case.
The left shoulder
The left shoulder forms during the downtrend: price makes a new low, then bounces to a first peak. At this point nothing distinguishes it from any other low in a falling market.
The head
Sellers push price to a lower low, the lowest point of the formation. Then buyers lift price back up to a second peak, roughly as high as the first one.
The right shoulder
Price falls a third time, but now it stops above the head, close to the left shoulder. The right shoulder is the first rising trough in the sequence, the first sign that sellers are losing strength.
The importance of the neckline
The neckline is the line that joins the two peaks between the lows. It can be flat, rising or falling. It is the resistance level that decides the outcome: a close above it means the pattern is confirmed, while a drop below the last low before that cancels it. In classical chart analysis (Edwards and Magee), the old resistance acts as support after the breakout, and it is the first level to watch on a pullback.
Volume dynamics during formation
Edwards and Magee describe a specific volume profile: heavy volume on the left shoulder, often lighter volume on the head, lighter again on the third low, and a clear rise in volume on the breakout. We measured the last part, volume on the breakout bar, and the result is in the reliability section: high breakout volume did not raise the share of trades that reached the target.
Volume is important in theory because it measures the strength behind a move: a breakout on heavy volume shows more buying strength than one on thin volume. One rule waits for a volume spike before entering; our data does not support it.
Market psychology behind the pattern
The inverted head and shoulders pattern tells the story of a downtrend running out of sellers. It is a story, not a measurement, but it explains why the classic rule waits for a close above the neckline before calling the pattern complete.
Shift from selling to buying sentiment
In a downtrend, each bounce fails sooner and each low is lower than the one before. The head is the last new low. The bounce from the head reaches about as high as the previous one, and the third low holds above the head and under the previous high. Classical analysis reads it as a shift: the market no longer accepts lower prices, and buyers are willing to pay more on each dip, a sign of growing strength.
Capitulation and the exhaustion of sellers
In the classical story, the central low forms on a sharp, emotional sell-off, the moment when the last weak holders give up. Once that selling is absorbed, fewer sellers are left. A long and strong decline before the formation matters for the same reason: the more sellers there were, the more there are to exhaust. The right shoulder is the test: if price cannot make a new low, the selling pressure is exhausted, and a breakout above the neckline shows that buyers have taken control of the price action.
That reading is plausible, but it is a story told after the fact. Whether the breakout actually predicts a rise is a question for data, not for the story. We come back to it in the reliability section.
How to identify an inverse head and shoulders on a chart
To identify an inverse head and shoulders pattern, look at the trend, the three lows, the neckline and the breakout, in that order. Trading the formation well starts with drawing it correctly while it is still forming, without bending the rules after the fact.
Key criteria for a valid pattern
The most important criterion is the last one: until price breaks the neckline, the pattern is only forming.
- A prior decline: the formation must follow a downtrend. On our bench, the swing before the left shoulder must start above the neckline, and the close one pattern duration before the left shoulder must lie at least 60% of the head depth above the neckline on a textbook pattern (on the looser standard grade, 30%, at any close within two pattern durations). The left shoulder must also be a true low: over the swing into it and a span as long before that swing, price never went more than 10% of the head depth below it.
- Three troughs, with the head clearly under both sides. Our bench mirrors its head and shoulders rule: the head below both shoulders by at least 25% of its depth on a textbook pattern (10% on the looser standard grade), and at least 4 ATR deep.
- Two sides at a similar level: on our bench, the two shoulders within 20% of the head depth of each other on a textbook pattern, 30% on the standard grade.
- Rough time symmetry: the time from left shoulder to head and from head to right shoulder can be different, within limits (between 1:2 and 2:1 on a textbook pattern on our bench, between 1:3 and 3:1 on the standard grade).
- Price action between the lows: each bounce should stall at about the same height.
- Confirmation: a close above the neckline. An intraday move through the line is not enough.
Our bench finds the turning points validated by a move of 2, 4 or 8 times the average true range (ATR), so the same code finds small setups on hourly charts and large ones on weekly charts.
Distinguishing between valid and failed patterns
Many formations never complete. On daily charts, 70.9% of the formations our bench found were validated by a close above the neckline; the others broke below their last low first or faded out without a breakout. A failed head and shoulders pattern is a formation where price closes below the right shoulder before it closes above the neckline. That failure can itself be traded as a sell signal. On daily charts we found 3,184 failed inverse formations, and that sell signal reads no clear edge on the 2:1 trade.
Comparison with double bottoms and triple bottoms
The double bottom has two lows at the same level; the triple bottom has three. The inverse head and shoulders also has three lows, but the central one is lower. All three are bullish chart patterns that signal a potential reversal once price closes above their resistance level. On daily charts, the double bottom reached its 2:1 target in 21.0% of cases against 22.2% for random dates, and the triple bottom in 18.6% against 20.4%. None of the three showed a measurable difference from chance in average result per trade.
Inverse pattern and classic top
The top version is the bearish mirror: three peaks with the highest in the middle, after an uptrend. Both share the same logic. On daily charts the classic head and shoulders pattern reached its 2:1 target in 15.9% of cases against 17.5% for random dates, slightly below chance. That gap is too small for our tests to separate from chance, which is why the table labels the trade No clear edge, and its 10-bar move reads worse than chance: no usable edge there either.
Real examples
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 6 cards with a shape that does not read as the definition on this page. They still count in the statistics, and are not replaced: our bench picks a fixed number of cards per category.
Step-by-step trading strategy
The classic inverse head and shoulders trading strategy buys the breakout above the neckline, with a protective exit below the right shoulder and a profit objective based on the height of the formation. It is important to wait for the close before you enter: a move above the neckline during the session can still reverse.
- Entry
- Close above the neckline
- Stop loss (SL)
- Below the right shoulder
- Target (TP)
- Twice the risk (2:1)
A clean case from our bench: US stocksChosen on its shape alone, never on the outcome. Stock prices are adjusted for splits and dividends, so they can differ from the prices quoted at the time.
Entry strategy: breakout or retest
There are two usual entries. The aggressive entry buys at the close of the first bar above the neckline. This is the trade our bench simulates on every occurrence. A strong close well above it gives a cleaner signal but a later entry. Others confirm the breakout with a second close. The conservative entry waits for a retest: on daily charts, price came back to within a quarter of an average true range of the broken neckline, within as many bars as the pattern took to form, after 79.7% of breakouts, and the trader buys if it holds as support. The retest approach can provide a better entry price and less risk per share, but you miss the trade when price does not return. Consider which one fits your trading plan before the setup appears, not after.
Setting the stop-loss
The classic stop goes below the third trough, the right shoulder. If price falls back under it, the structure that defined the formation is gone. Our bench uses this exit. A tighter exit just under the neckline reduces the risk per trade but is hit more often by a normal retest. On real daily setups the classic stop can be far from the entry: in the three examples below it sits 5.6% to 8.7% under the entry price, so size the position on that distance, not on your conviction.
Calculating profit targets using the measured move
The measured move takes the distance from the head to the neckline and projects it upward from the breakout point, a rough estimate of the potential upward move. If the head is 10 points below the neckline, the target is 10 points above it. When the neckline is slanted, measure from the head to the neckline straight up, and project from the breakout point. A second approach sets the objective as a multiple of the risk, for example twice the gap between entry and exit. That is the version we test: on daily charts, winning trades took a median of 38 days to get there, while losing trades were closed after a median of 23 days.
Inverse head and shoulders trading strategies
Three trading strategies use this pattern as their entry signal. Each adds a filter the formation alone does not have, and each should be tested on your own market before you put money on it. All three strategies use the same exit logic.
Strategy 1: the neckline breakout
Go long at the close above the neckline, put the stop under the last low, aim for twice the risk. This is the plain version, and the one our statistics measure.
Strategy 2: the neckline retest
Wait for the breakout, then wait for price to come back to the neckline, now acting as support. Enter long when a bullish candle closes off that support. The trade is cheaper and the exit closer, but fewer setups get filled.
Strategy 3: the trend-filtered reversal
Take only the formations that appear while the long-term trend is still up, for example above a rising 200-day moving average: the pattern then marks the end of a pullback rather than the bottom of a bear market. Our data covers the side of the average, not its slope, and that filter did not give the pattern a measurable edge (see below).
Best indicators to confirm the pattern
Classical analysis does not use the formation alone: it combines it with technical indicators that describe momentum, trend or volume. No indicators turn a weak setup into a strong one, but some indicators provide context: momentum for the head, trend for the larger picture.
Using RSI for divergence confirmation
One rule looks for a bullish divergence: the head makes a lower low in price while the RSI makes a higher low. The idea is that downside momentum was already fading. Like all technical indicators used in trading, the RSI lags price. We have not tested an RSI filter: if you use one, test it on your own market first.
Moving averages as trend filters
We tested the 200-day moving average. On daily charts, breakouts above it reached the 2:1 target in 23.8% of cases, with an expectancy of +0.16 R; breakouts below it in 33.1% of cases, with an expectancy of +0.12 R. Breakouts below the average reached the target more often, yet the expectancy was close in both groups. This breakdown is descriptive, not corrected for the number of tests we run.
Volume profile and breakout volume
Edwards and Magee insist on strong volume at the breakout. On daily charts, breakouts with volume above 1.5 times the 20-day average reached the 2:1 target in 26.3% of cases, against 29.2% for breakouts on normal volume, with an expectancy of +0.15 R against +0.14 R. In our data, high breakout volume did not make the target more likely, and it did not change the expectancy; this breakdown is not corrected for the number of tests we run.
Pre-trade checklist
Before entering any trade, go through these points. It takes a minute.
- Trend: is there a clear downtrend before the pattern? A reversal needs a trend to reverse.
- Head: is the central low the lowest point, with both sides at similar levels?
- Neckline: can you draw it through the two highs the way other traders would?
- Confirmation: has a bar closed above the neckline? If it is still forming, there is no trade yet.
- Risk: is the gap from entry to the exit acceptable for your capital?
- Support and resistance levels: is there a major resistance just above the neckline that could block the upward move?
- Plan: are the exits for a winning and a losing trade written down before entering the long position?
Avoiding common mistakes and false breakouts
On intraday and daily charts alike, a few errors are worth avoiding with this pattern, starting with impatience.
Identifying "trap" patterns
The danger of trading in low liquidity
On thin markets, a single large order can print a close that does not hold. Prefer liquid assets and timeframes where a close means something, consider skipping the trade when the spread is wide, and remember that our results are before fees and slippage.
Why timeframes matter for reliability
The pattern occurs on every timeframe, but results differ. On hourly crypto charts, 45.2% of breakouts were followed by a higher price 10 hours later, against 48.2% for random hours. On weekly charts across all markets, 56.3% were higher 10 weeks later, against 56.2% for random weeks. A longer timeframe gives a cleaner picture, not a better edge over chance.
Reliability and success rate
The pattern is not reliable on its own, and this is the key point of this guide: across every market and timeframe with enough data, no row showed a significant gap in average excess return in favor of the pattern. Here are the numbers from our test bench, which detects every occurrence on full price history and compares it with random bars on the same assets.
Moved the expected way 10 bars later, compared with random bars.
Measured on 5,968 daily inverse head and shoulders occurrences across 1,787 assets. Random bars on the same assets are the honest baseline.
No clear edgeInverse head and shoulders 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 inverse head and shoulders 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.
Inverse head and shoulders: 5,968 occurrences tested
Bullish pattern · All markets · Daily · 1,787 assets · 1973-06 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
- 85 days · middle half 62 to 142 · on 5,968 occurrences
- Breakout, after the last swing
- 2 days · middle half 0 to 8 · on 5,968 occurrences
- Time to the 2:1 target, when hit
- 38 days · middle half 19 to 60 · on 1,663 trades that hit it
- Time to the stop, when hit
- 23 days · middle half 11 to 44 · on 2,988 trades that hit it
- Time in the trade, all exits
- 39 days · middle half 17 to 87 · on 5,919 trades
- Measured-move target reached, when hit
- 32 days · middle half 16 to 58 · on the occurrences that reached it
- Pattern height projected from the breakout
Size and trade path
- Pattern height
- 20.6% · middle half 13.9% to 31.7% · on 5,968 occurrences
- Best open profit during the trade
- 1.00 R · middle half 0.38 R to 2.02 R · on 5,919 trades
- Stopped trades that were first up 1 R
- 19.2% · on 2,988 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. After a decline: left shoulder, lower head, right shoulder. The close one pattern duration before the left shoulder lies at least 60% of the head depth above the higher neckline peak. Each shoulder falls at least 35% of the head depth below the neckline, shoulders within 20% of each other, head below both by at least 25%, head at least 4 ATR deep, at least 3 bars between swing points, time symmetry between 1:2 and 2:1, neckline slope at most 35% of the head depth. Confirmed by a close above the neckline drawn through the two peaks, within half the pattern duration after the right shoulder. The standard grade, which accepts most counted occurrences, widens this: the head beyond both shoulders by at least 10% of its size, shoulders within 30% of each other and at least 25% of the head size from the neckline, time symmetry between 1:3 and 3:1, a neckline slope of at most 60%, a prior move of at least 30% of the height over the two pattern durations before, a breakout within one pattern duration. The first trough is a true low: from one first-leg duration before the pattern up to that trough, price never fell more than 10% of the pattern height below it.
All measurements (20 rows)
10-bar move: did price go the expected way?
| Market | Occurrences | Pattern | Random bars | Excess | 10-bar move verdict |
|---|---|---|---|---|---|
| Crypto · 1-hour | 10,930 | 45.2% | 48.2% | −0.15% | Opposite of the textbook |
| Forex · 1-hour | 1,792 | 51.0% | 50.6% | +0.01% | No clear edge |
| All markets · 1-hour | 12,722 | 46.0% | 48.6% | −0.13% | Opposite of the textbook |
| Crypto · 4-hour | 2,716 | 45.7% | 47.5% | −0.31% | No clear edge |
| Forex · 4-hour | 480 | 51.7% | 50.4% | +0.02% | No clear edge |
| All markets · 4-hour | 3,196 | 46.6% | 47.9% | −0.26% | Weak, below chance |
| Crypto · Daily | 446 | 49.7% | 44.4% | −0.77% | No clear edge |
| US stocks · Daily | 5,092 | 54.2% | 53.9% | +0.05% | No clear edge |
| ETFs · Daily | 191 | 52.4% | 55.8% | −0.21% | No clear edge |
| Indices · Daily | 106 | 62.3% | 57.0% | +0.10% | No clear edge |
| Forex · Daily | 76 | 51.4% | 50.1% | +0.18% | No clear edge |
| Commodities · Daily | 57 | 42.1% | 51.8% | −1.06% | No clear edge |
| All markets · Daily | 5,968 | 53.8% | 53.2% | −0.03% | No clear edge |
| Crypto · Weekly | 17 | 43.8% | 40.6% | +78.93% | Not enough data |
| US stocks · Weekly | 664 | 56.4% | 56.3% | −0.08% | No clear edge |
| ETFs · Weekly | 40 | 52.5% | 61.2% | +0.60% | No clear edge |
| Indices · Weekly | 14 | 71.4% | 61.5% | −0.25% | Not enough data |
| Forex · Weekly | 13 | 61.5% | 51.4% | +0.24% | Not enough data |
| Commodities · Weekly | 9 | 55.6% | 53.5% | −1.00% | Not enough data |
| All markets · Weekly | 757 | 56.3% | 56.2% | +1.64% | 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 | 10,912 | 24.9% | 25.1% | +0.01 R vs +0.01 R | No clear edge |
| Forex · 1-hour | 1,789 | 20.0% | 20.7% | −0.01 R vs −0.02 R | No clear edge |
| All markets · 1-hour | 12,701 | 24.2% | 24.5% | +0.01 R vs 0.00 R | No clear edge |
| Crypto · 4-hour | 2,711 | 27.8% | 27.8% | +0.04 R vs +0.02 R | No clear edge |
| Forex · 4-hour | 472 | 22.2% | 22.9% | 0.00 R vs −0.01 R | No clear edge |
| All markets · 4-hour | 3,183 | 27.0% | 27.1% | +0.03 R vs +0.02 R | No clear edge |
| Crypto · Daily | 441 | 35.6% | 29.7% | +0.12 R vs −0.03 R | No clear edge |
| US stocks · Daily | 5,051 | 27.5% | 29.2% | +0.14 R vs +0.19 R | No clear edge |
| ETFs · Daily | 190 | 25.3% | 31.1% | +0.15 R vs +0.31 R | No clear edge |
| Indices · Daily | 106 | 34.0% | 27.0% | +0.34 R vs +0.13 R | No clear edge |
| Forex · Daily | 74 | 18.9% | 20.4% | −0.11 R vs −0.09 R | No clear edge |
| Commodities · Daily | 57 | 29.8% | 30.8% | +0.29 R vs +0.17 R | No clear edge |
| All markets · Daily | 5,919 | 28.1% | 29.2% | +0.14 R vs +0.17 R | No clear edge |
| Crypto · Weekly | 16 | 43.8% | 43.2% | +0.31 R vs +0.30 R | Not enough data |
| US stocks · Weekly | 642 | 39.9% | 38.6% | +0.41 R vs +0.37 R | No clear edge |
| ETFs · Weekly | 40 | 52.5% | 44.2% | +0.75 R vs +0.45 R | No clear edge |
| Indices · Weekly | 14 | 42.9% | 39.3% | +0.39 R vs +0.56 R | Not enough data |
| Forex · Weekly | 13 | 30.8% | 32.7% | +0.53 R vs +0.20 R | Not enough data |
| Commodities · Weekly | 8 | 75.0% | 46.9% | +1.25 R vs +0.48 R | Not enough data |
| All markets · Weekly | 733 | 40.9% | 39.0% | +0.43 R vs +0.37 R | No clear edge |
After the breakout
| Market | Occurrences | False starts | Same, random dates | Throwbacks |
|---|---|---|---|---|
| Crypto · 1-hour | 10,930 | 49.4% | 49.8% | 77.8% |
| Forex · 1-hour | 1,792 | 48.4% | 47.0% | 77.9% |
| All markets · 1-hour | 12,722 | 49.3% | 49.4% | 77.8% |
| Crypto · 4-hour | 2,716 | 50.3% | 49.1% | 76.8% |
| Forex · 4-hour | 480 | 46.0% | 49.4% | 77.7% |
| All markets · 4-hour | 3,196 | 49.6% | 49.1% | 76.9% |
| Crypto · Daily | 446 | 44.3% | 48.7% | 85.1% |
| US stocks · Daily | 5,092 | 43.1% | 41.9% | 79.2% |
| ETFs · Daily | 191 | 41.1% | 42.6% | 80.9% |
| Indices · Daily | 106 | 47.2% | 47.8% | 79.2% |
| Forex · Daily | 76 | 47.8% | 52.0% | 80.3% |
| Commodities · Daily | 57 | 42.0% | 45.9% | 78.6% |
| All markets · Daily | 5,968 | 43.3% | 42.7% | 79.7% |
| Crypto · Weekly | 17 | 36.4% | 47.4% | 85.7% |
| US stocks · Weekly | 664 | 36.6% | 38.7% | 78.8% |
| ETFs · Weekly | 40 | 32.4% | 44.8% | 76.3% |
| Indices · Weekly | 14 | 35.7% | 27.6% | 71.4% |
| Forex · Weekly | 13 | 22.2% | 44.9% | 81.8% |
| Commodities · Weekly | 9 | 16.7% | 38.5% | 88.9% |
| All markets · Weekly | 757 | 35.9% | 39.1% | 78.8% |
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.
What you often read
“The inverse head and shoulders pattern is a reliable bullish signal.”
What our data shows
On 5,968 daily occurrences, it moved in the expected direction 53.8% of the time, against 53.2% 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 and timeframe | Breakouts tested (2:1 trades) | Higher 10 bars later | Random bars | 2:1 target hit | Same trade, random dates | Expectancy (R) | Random dates (R) |
|---|---|---|---|---|---|---|---|
| All markets, daily | 5,968 (5,919) | 53.8% | 53.2% | 28.1% | 29.2% | +0.14 | +0.17 |
| US stocks, daily | 5,092 (5,051) | 54.2% | 53.9% | 27.5% | 29.2% | +0.14 | +0.19 |
| ETFs, daily | 191 (190) | 52.4% | 55.8% | 25.3% | 31.1% | +0.15 | +0.31 |
| Indices, daily | 106 (106) | 62.3% | 57.0% | 34.0% | 27.0% | +0.34 | +0.13 |
| Commodities, daily | 57 (57) | 42.1% | 51.8% | 29.8% | 30.8% | +0.29 | +0.17 |
| Crypto, daily | 446 (441) | 49.7% | 44.4% | 35.6% | 29.7% | +0.12 | −0.03 |
| Crypto, 4-hour | 2,716 (2,711) | 45.7% | 47.5% | 27.8% | 27.8% | +0.04 | +0.02 |
| Crypto, hourly | 10,930 (10,912) | 45.2% | 48.2% | 24.9% | 25.1% | +0.01 | +0.01 |
| Forex, hourly | 1,792 (1,789) | 51.0% | 50.6% | 20.0% | 20.7% | −0.01 | −0.02 |
| All markets, weekly | 757 (733) | 56.3% | 56.2% | 40.9% | 39.0% | +0.43 | +0.37 |
Read the table in pairs of columns. On daily charts, 53.8% of inverse head and shoulders breakouts were followed by a higher price 10 days later. That sounds bullish until you see that 53.2% of random days on the same assets were too: stocks rise a little more often than they fall. The excess return over the rest of the market after 10 days is −0.03%, with a 95% confidence interval from −0.21% to +0.14%. No clear edge.
The 2:1 trade enters at the breakout close, exits below the last low or at twice the risk, and closes after 100 bars if neither exit is reached. On daily charts it reached its objective in 28.1% of cases, against 29.2% for the same entry and exit distances on random dates. The expectancy of +0.14 R per trade before costs looks attractive, but the random trades averaged +0.17 R, and on US stocks +0.14 R against +0.19 R: the gain comes from the long-term rise of the markets, not from the formation. None of these gaps in average result per trade passes our statistical test.
A few rows look better than chance on the raw 10-bar rate: daily indices, daily crypto, daily and 4-hour forex, and hourly forex by a hair. None of these gaps in average excess return is statistically significant, and the daily indices and daily forex rows rest on only 106 and 76 cases. The ETF row (No clear edge) shows lower raw rates than random dates, on a small sample. Intraday crypto goes the other way: the hourly row reads worse than chance, and the 4-hour row, also below random bars on the raw rate, reads no clear edge. The commodities row, with only 57 cases, reads No clear edge.
Is it a powerful signal?
The descriptive breakdowns on daily charts point the same way. Smaller formations (height below the median) reached the 2:1 target in 31.1% of cases against 25.1% for taller ones, likely because their exit levels are closer. The result was similar in the first and second half of the history. None of these splits makes it a reliable signal on its own.
How often does the pattern occur?
One breakout every 1,421 eligible bars on daily charts, and one every 1,343 on hourly crypto charts. On US stocks it is one every 1,437 daily bars. With about 252 trading days a year, a single stock gives one only once every few years, and a watchlist of 500 stocks several a month.
What academic research says
Our results sit within a long debate. Andrew Lo, Harry Mamaysky and Jiang Wang (Foundations of Technical Analysis, Journal of Finance, 2000) detected this family of chart formations automatically on US stocks and found that several of them carried some information about later returns, especially on Nasdaq stocks, without measuring profits after costs. Carol Osler and Kevin Chang (Federal Reserve Bank of New York, 1995) tested the top version on currencies and reported profits for some of them but not others. Our bench adds one control that matters for traders: every trade is compared with the same trade on random dates of the same asset.
The All measurements table, with every market, timeframe and verdict, is in the statistics section of this page. The method is published in our methodology.
Inverse head and shoulders across different markets
It is defined the same way in every market. What changes is the data behind it.
Trading in stock markets
US stocks give the largest sample: 5,092 breakouts on 1,421 companies since 1973. The breakout was followed by a rise 10 days later in 54.2% of cases, against 53.9% for random days. The 2:1 trade reached its objective in 27.5% of cases against 29.2% on random dates.
Application in forex currency pairs
On hourly forex charts, 1,792 breakouts on 25 currency pairs since 2012: 51.0% rose over the next 10 hours, against 50.6% for random hours. The average excess return over the rest of the market does not pass our statistical test: no clear edge. Daily forex gives only 76 cases, which read no clear edge as well.
Analyzing crypto market reversals
Crypto gives the largest sample on intraday charts: 10,930 breakouts on hourly charts across 579 coins since 2017. Their direction after 10 hours was below chance (45.2% against 48.2%, an average excess return of −0.15% with a confidence interval entirely below zero: worse than chance), and the 2:1 trade reached its objective in 24.9% of cases against 25.1% on random dates, but the gap in average result per trade is not statistically significant.
Commodities and precious metals
On 57 daily cases across 16 commodities since 2001, only 42.1% rose over the next 10 days, against 51.8% for random days. On a sample this small the gap is not statistically significant: no clear edge.
Advanced tips for professional traders
Multi-timeframe analysis approach
A setup on a daily chart inside a weekly downtrend is fighting the larger trend; inside a weekly uptrend, it marks the end of a pullback. Consider also the next support levels on the weekly chart. A simple routine: read the direction on the longer timeframe and take signals on the shorter one only in its direction. We have not tested this combination.
Managing risk and position sizing
Advantages and disadvantages of the pattern
Pros: high reward-to-risk potential
- Clear structure that is easy to identify.
- A precise invalidation point.
- Defined exits before you take the trade.
- Can be drawn on every market and timeframe, from hourly charts for trading intraday to weekly charts for position trading.
- Widely described in the classic literature, so the levels it defines are easy to share and check.
Cons: inherent lag and false signals
- Lag: by the time the pattern is confirmed, a large part of the rise from the head is already done.
- Wide exits, which reduce the position size.
- On its own, the breakout did not show a measurable edge over chance on any market or timeframe we tested.
Real-world trading examples
Here are three real setups from our bench on daily US stocks, with their actual outcome. None of the three is a chart of the gallery in the Real examples section, which shows other cases. Prices are adjusted for splits and dividends, so we give the moves in percent.
Case study: a breakout that reached its target
Morgan Stanley (MS) formed a left shoulder on October 4, 2023, a head on October 27, about 9.6% lower, and a right shoulder on November 28. It closed above the neckline on December 1, 2023. The stop under the right shoulder sat 5.6% below the entry. On December 14, nine sessions later, the stock traded through the 2:1 target, so the trade closed at +2 R. MS was 13.2% higher 10 sessions after the signal.
Case study: failed breakouts and exit management
Cisco (CSCO) formed a left shoulder on June 10, 2010, a head on July 1 and a right shoulder on July 20, then closed above the neckline on August 4, 2010. On August 12, six sessions later, the stock opened 11.3% below the entry, under the stop set 8.7% below it, and the gap turned the planned 1 R loss into a loss of 1.30 R. CSCO was 7.2% lower 10 sessions after the signal. A slower failure: Microsoft (MSFT) broke out on June 15, 2000, with its stop 8.6% below the entry. It was 6.6% higher 10 sessions after the signal, then gave the whole gain back and hit the stop 63 sessions after entry, for a full 1 R loss. A stop is a level, not a guaranteed price: when the market gaps through it, the loss is larger than planned.
Scanners and charting software
TradingView offers pattern scanners and community scripts that flag the head and shoulders pattern and its inverted version. Check the rules each scanner uses: tolerances for the shoulder levels, the slope and the confirmation are different from one to the next, and so are the results. Before trading the pattern with real money, mark the last thirty formations on your market on historical charts, write down the trade you would have taken, and compare the outcome with the same trade on random days. That is the test we run at scale.
Frequently asked questions
Is the inverse head and shoulders always bullish?
Yes, by definition it is a bullish reversal pattern: it forms following a downtrend and is confirmed by a breakout above the neckline. In our data, the breakout was followed by a rise about as often as a random bar on the same assets.
How reliable is the pattern in 2026?
Our statistics run through October 2026. Neither half of the history showed a clear edge over chance.
What defines a failed inverse head and shoulders?
A setup where price breaks below the third trough before closing above the neckline. On daily charts we found 3,184 of them, and trading them as a sell signal read no clear edge.
Is the inverse head and shoulders a reliable reversal signal?
Not on its own. On 5,968 daily breakouts, the reversal signal was followed by a rise in 53.8% of cases, against 53.2% for random days. Its value lies in the structure it gives to a trade: you know where you are wrong before you enter.
How do you tell a bullish setup from a sell setup?
A bullish reversal, such as this one and most other bottom chart patterns, occurs following a downtrend and signals a potential rise. A bearish reversal, such as a double top, occurs after an uptrend and signals a potential decline. Check the direction of the move before the pattern and the direction of the breakout.
Should I trade this pattern on intraday or swing timeframes?
No timeframe stood out. Among the rows of our table, weekly setups had the highest raw rate of 2:1 targets hit (40.9%), but random weeks came close (39.0%), and the gap reads no clear edge.
How do I know if the neckline is slanted?
Draw it through the two highs. If the second peak is lower, the neckline slopes down; this is the typical case in our median pattern. A neckline that slopes down gives an earlier breakout; a rising one gives a later, more expensive breakout.
Is this financial advice?
No. This page is an educational guide based on historical data. It is not financial advice, and past results do not guarantee future ones.
Summary of key points
- The inverse head and shoulders pattern has three lows, the central one lowest, and is validated by a close above the neckline following a downtrend.
- On 5,968 daily breakouts, 53.8% were higher 10 days later, against 53.2% of random days on the same assets.
- The 2:1 trade reached its objective in 28.1% of cases, against 29.2% for the same trade on random dates, but the gap in average result per trade is within the margin of error.
- Neither high breakout volume nor the 200-day moving average gave the pattern a measurable edge.
- Treat the pattern as a framework for a trade plan, not as an edge on its own.
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.