The shooting star candlestick pattern is a single bar with a small real body near the bottom of its range, a long upper shadow at least twice the size of the body and little or no lower shadow, printed after an uptrend. Technical analysis reads it as a potential bearish reversal: buyers pushed price up during the session, then sellers drove it back near the open by the close.

This guide covers the definition, how to identify a shooting star, how traders use it, and what actually happened after it. Our test bench applied its rule to full price history, which gave 16,646 occurrences on the daily timeframe alone across stocks, crypto, forex, ETFs, indices and commodities, and compared the outcome with random days on the same assets.

What is the shooting star candlestick pattern?

The shooting star is a one-bar bearish reversal pattern that appears after a rise in price. Its shape is easy to remember: a small body at the bottom, like the head of a falling star, and a thin tail trailing above it.

Definition and origin

The name comes from Japanese candlestick analysis, which Steve Nison brought to Western traders in Japanese Candlestick Charting Techniques (1991). His description has three conditions: a small real body near the bottom of the range, a long upper shadow, and little or no lower shadow. Its color does not matter. The formation must come after an uptrend: the same shape after a decline is a different pattern, the inverted hammer.

Our test bench applies a stricter version without judgment: after an uptrend (the last close before the bar is at least one ATR above the close 10 bars earlier and in the upper half of the last 40 closes), a small real body, a top wick at least twice its size, and almost no wick underneath, on a bar at least as wide as the average of the 10 prior bars. Sizes are measured against the 10 prior bars, as in the open-source TA-Lib library, but our definition is stricter than common use: we find 13% of the occurrences TA-Lib flags, so our counts are not the total a looser scanner would report.

Visual representation

The figure below is not drawn by hand. It is the median shape of the clean occurrences our bench detected, with the faded bars showing the rise before it, and the lines of the position we test: entry under the bottom of the bar, stop loss above its top, target at twice the risk.

Bearish setup on the median shape of 1,607 daily occurrences drawn at random from all markets, with entry, stop loss (SL) and 2:1 target (TP)

The psychology behind the pattern

The bar tells the story of one session. Price opens, buyers extend the advance and push it well above the open, in the textbook case to a new peak of the move. Then selling pressure appears, absorbs the buying and drives price back toward the open by the close. The long upper shadow is the trace of that rejected rally. Traders read it as a shift in market sentiment: buyers could not hold the gains, and sellers are now defending a level.

That reading is plausible, but it describes one session. Whether one rejected rally turns the trend is a question for data. We come back to it in the reliability section.

Anatomy of a shooting star

A shooting star candlestick has three parts, and each one is measured against the bars before it.

Long upper shadow≥ 2 × body
Short bodyafter an uptrend
Very short lower shadow

Median shape of 1,607 daily occurrences drawn at random from all markets, those with the candle colors drawn here (54% of the 3,000 drawn), found by our test bench.

The small real body

The real body, the distance between the opening and closing price, is small compared with recent bars and sits in the bottom part of the range. Red means the session closed under its open; green means it closed slightly above. Both count.

The long upper shadow

The upper shadow runs from the top of the real body to the peak of the session and is at least twice its size: it is the heart of the setup. On the median occurrence our bench found on the daily timeframe, the whole bar spans 2.79% of price, or 1.11 times the average true range (ATR) of the asset. The typical occurrence is not a huge bar: its range is only slightly above the average range of recent sessions.

The absence of a lower shadow

The wick underneath is tiny or absent: the session ends at or just above its bottom. Wicks on both sides make it a high-wave bar or a spinning top, which signal indecision rather than a bearish reversal.

How to identify a shooting star pattern

To identify a shooting star, check three key points in order: the trend before it, the gap, and the proportions. Then wait for the session to end.

Step 1: establish the preceding uptrend

It is a reversal pattern, so there must be a rise to reverse. Our rule: the last close before the bar is at least one ATR above the close 10 bars earlier and in the upper half of the last 40 closes. Without a prior rise, the shape is just a bar with a tall wick, not a shooting star.

Step 2: assess the gap up

In the textbook case, the bar opens with a gap above the prior session, at a new peak of the move, or next to a resistance level. Nison treats the gap as a plus rather than a requirement, and our bench does not require it. We have not measured a gap filter separately, so we cannot tell you how much it changes the odds.

Step 3: verify the wick-to-body ratio

Measure the upper shadow against the body: at least two times in our rule. Then check that the tail underneath is tiny. Only once the session has ended is the shape final: before the close, a long upper shadow can still turn into a strong close.

Shooting star vs. inverted hammer: key differences

The shooting star and the inverted hammer are the same shape in different places. You cannot tell them apart by looking at one bar alone.

Positional context in the market

Location decides the name. After an uptrend, it is the bearish version. After a downtrend, the same shape is an inverted hammer. The test is the rule of step 1, mirrored for the inverted hammer: compare the last close before the bar with the close 10 bars earlier and with the last 40 closes.

Differences in trend implication

The shooting star is read as bearish: buyers failed at the top. The inverted hammer is read as bullish: buyers showed up for the first time after a decline, even if they could not hold their gains. On the daily timeframe, the inverted hammer setup (entry above its top) reached its 2:1 target in 30.7% of cases against 31.1% for the same setup on random days, and its average result per trade, −0.08 R against −0.08 R at random, does not pass even a simple test, and it still loses money before costs. Its 10-bar move did pass a simple test (promising, +0.27% against the rest of the market), but not our correction for multiple testing. Its bearish twin showed no significant difference either.

The hanging man is the other bearish one-bar reversal after a rise, with the wick underneath instead of above. The gravestone doji is the extreme version, with open and close at the same price.

What does the shooting star indicate?

Price exhaustion and selling pressure

The formation indicates that the rally ran into supply. Buyers pushed price to a peak, then selling pressure took over for the rest of the session.

Rejection of higher price levels

Its top marks a price level that the market refused. It can be treated as a short-term resistance, with the protective order just above it.

Potential shift in market sentiment

A potential shift is not a confirmed one. In our data, it did not change the odds: on the daily timeframe, 44.3% of shooting stars were followed by a fall 10 days later, against 46.0% of random days on the same assets, an average excess return of −0.10% that is not statistically significant.

How to trade the shooting star pattern

The classic trading plan sells a break under the bottom of the signal bar, with a stop loss above its top and a target set as a multiple of the risk. Our bench simulates this setup on every occurrence.

Entry: Sell stop at the pattern low
Stop loss (SL): At the pattern high
Target (TP): Twice the risk (2:1)

The trade our bench tests, drawn on the typical shape. Median shape of 1,607 daily occurrences drawn at random from all markets, those with the candle colors drawn here (54% of the 3,000 drawn).

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.

TextbookVZ April 10, 2014Daily chart3.2% in the expected direction after 10 bars2:1 trade: stopped out, −1.00 R

Determining the entry point

There are two classic entries. The aggressive one sells at the close of the signal bar. The conservative one places a sell stop just under its bottom and waits for price to trade through it within the next sessions. In our tests the sell order was triggered in 79.4% of cases on the daily timeframe; in 20.6%, price broke the top first and the setup was canceled before any entry. The remaining orders were never reached within the 20 bars the order stays active, or the data ended first.

Setting the stop loss

Establishing profit targets

The target we test is twice the risk (a 2:1 reward-to-risk ratio). On the daily timeframe, setups that reached that target took a median of 6 days; setups that failed lost after a median of 3 days. A prior support level under price is another possible target, which we have not tested.

Essential confirmation techniques

Using volume as a confirmation tool

A classic filter wants heavier activity on that session than on the prior sessions. We measured it: on the daily timeframe, occurrences printed on volume above 1.5 times the 20-day average reached the 2:1 target in 29.3% of cases, against 28.6% on normal volume, with expectancies of −0.11 R and −0.15 R. The difference is small, and this breakdown is descriptive (not corrected for the number of tests): treat it as a mild plus, not a filter that changes the outcome.

Waiting for the next candle close

A stricter approach waits for confirmation: a bearish bar that closes under the bottom of the setup bar. The sell order at that level is a form of confirmation, and it is the version we measured. Waiting for a full down session gives a later entry, further from the exit level.

Analyzing support and resistance levels

Classic analysis gives more weight to a formation that appears at a known resistance: a prior swing peak, a round number, a falling average. The logic is that the rejection happens where sellers already had a reason to act. We have not measured resistance levels, so treat this as a reasonable practice, not a tested rule.

Advanced trading strategies

Used alone, it did not beat chance in our tests. Each of the trading strategies below adds a filter that one bar does not have, and each should be tested on your own market before you risk money on it.

Combining with moving averages

This is the filter we did test. On the daily timeframe, setups above the 200-day moving average reached the 2:1 target in 28.8% of cases, against 28.8% under it, with expectancies of −0.14 R and −0.14 R. The long-term trend barely moved the result.

Using the relative strength index (RSI)

One rule is to take the setup only when the RSI is overbought (above 70), on the idea that the rally is stretched. We have not tested an RSI filter.

Integrating Fibonacci retracement levels

After a bounce inside a larger downtrend, you can look for this bar at the 38.2%, 50% or 61.8% retracement of the prior decline, where the bounce may end. This is a matter of confluence. We have not measured it.

Trading shooting stars with pivot points

On intraday charts, you can watch for it on a 1-hour or 4-hour view at a daily pivot or resistance level. On hourly crypto data, the bar alone was no better than chance, so any edge would have to come from the pivot, a filter we have not tested.

Identifying bearish divergence with MACD

A bar like this at a new peak while the MACD makes a lower peak combines two signs of fading momentum. We have not tested this combination either.

Advantages of the shooting star pattern

Early reversal detection

It is a one-bar setup, so it appears at the top of a move, not several sessions later. That is its appeal, and also why it is noisy.

Versatility across timeframes

It forms on every market and timeframe: on our data, about once every 458 bars on the hourly timeframe, 509 on the daily and 517 on the weekly.

Simple risk-to-reward ratio management

The top of the bar gives a clear invalidation point, which makes the risk easy to define before entry.

Limitations and common pitfalls

False signals and late reversals

Measured on its own, it did not beat chance on any market or timeframe we tested, and on a few rows it did slightly worse: the 2:1 trade on hourly charts with all markets together (30.5% of targets reached against 31.9% on random dates, −0.05 R against −0.01 R) and on daily indices, plus the 10-bar move on hourly forex. Each of these rows is rated Weak, below chance: the gap passes a simple test but not our correction. Many losing setups also reversed late: on the daily timeframe, of the setups that hit their stop, 22.9% had first been up 1 R.

Importance of trend context

Avoiding over-reliance on a single candle

One bar is not a trading system. Use it as one input among others: the trend, a resistance level, and above all a risk plan.

Shooting star in different markets

Application in forex trading

On 4,333 hourly occurrences (3,678 closed trades) across 25 currency pairs since 2012, the 2:1 setup reached its target in 30.7% of cases against 32.5% on random dates, with an expectancy of −0.08 R. On the 4-hour forex timeframe, the 2:1 setup did about as well as random entries (31.6% against 32.5%, −0.04 R against −0.02 R per trade), a gap that does not pass our statistical test.

Application in stocks, ETFs and indices

On 317 daily occurrences on 15 indices since 1970, 35.3% of occurrences were followed by a fall 10 days later, against 42.8% for random days. On 14,652 daily occurrences on 1,616 US stocks, the figures were 43.6% against 45.4%. On 350 daily ETF occurrences, 39.7% were followed by a fall against 42.8% for random days, an average excess return of +0.05% over the rest of the market, within the margin of error: no clear edge. On indices, the 2:1 setup reached its target in 24.5% of cases against 32.6% on random dates, a shortfall that passes a simple test but not our correction (Weak, below chance).

Application in cryptocurrency trading

On 32,439 hourly occurrences on 584 coins since 2017, 52.2% were followed by a fall 10 hours later, against 50.7% of random hours. More shooting stars than random hours were followed by a fall, but the average excess return, −0.03%, is within the margin of error, hence the label No clear edge. On daily crypto data, the setup reached its target in 30.8% of cases against 29.8% on random dates, but its average result per trade does not pass our statistical test on 986 occurrences (867 closed trades).

Historical accuracy and backtesting

The shooting star is not reliable on its own: across every market and timeframe we tested, its average excess return over the rest of the market did not pass our statistical test, except on hourly forex, where it slightly moved against the expected direction relative to its market, a gap that passes a simple test but not our correction. Here are the numbers from our test bench.

44.3%vs 46.0% at random

Moved the expected way 10 bars later, compared with random bars.

Measured on 16,646 daily shooting star occurrences across 2,120 assets. Random bars on the same assets are the honest baseline.

No clear edge

Shooting star against random bars on the same assets, by market, on daily candles. Bars of almost the same length mean no edge.

Moved the expected way 10 bars laterShooting starRandom bars

All markets
All markets, Shooting star: 44.3%
All markets, Random bars: 46.0%
Crypto
Crypto, Shooting star: 57.6%
Crypto, Random bars: 55.1%
US stocks
US stocks, Shooting star: 43.6%
US stocks, Random bars: 45.4%
Forex
Forex, Shooting star: 44.7%
Forex, Random bars: 49.4%
ETFs
ETFs, Shooting star: 39.7%
ETFs, Random bars: 42.8%
Indices
Indices, Shooting star: 35.3%
Indices, Random bars: 42.8%
Commodities
Commodities, Shooting star: 46.5%
Commodities, Random bars: 47.8%

2:1 trade hit its targetShooting star tradeSame trade, random dates

All markets
All markets, Shooting star trade: 28.8%
All markets, Same trade, random dates: 29.7%
Crypto
Crypto, Shooting star trade: 30.8%
Crypto, Same trade, random dates: 29.8%
US stocks
US stocks, Shooting star trade: 28.6%
US stocks, Same trade, random dates: 29.5%
Forex
Forex, Shooting star trade: 32.1%
Forex, Same trade, random dates: 34.0%
ETFs
ETFs, Shooting star trade: 31.9%
ETFs, Same trade, random dates: 30.0%
Indices
Indices, Shooting star trade: 24.5%
Indices, Same trade, random dates: 32.6%
Commodities
Commodities, Shooting star trade: 30.6%
Commodities, Same trade, random dates: 31.7%

All statistics

Full results for the shooting star candlestick 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.

10-bar move No clear edge2:1 trade No clear edge

Shooting star: 16,646 occurrences tested

Bearish pattern · All markets · Daily · 2,120 assets · 1970-09 to 2026-10

Moved the expected way after 10 bars

44.3%

vs 46.0% on random bars

Excess return vs its market, 10 bars

−0.10%

95% interval −0.30% to +0.09%

Excess return is signed so that positive favors the pattern. On a bearish setup, it means the asset lagged its market.

2:1 trade hit the target

28.8%

vs 29.7% for the same trade on random dates

Average result per trade

−0.14 R

vs −0.11 R on random dates

What this means. No measurable difference from the rest of its market over the next 10 bars.

Timeline

Entry triggered, after the pattern: 1 day · middle half 1 to 1 · on 13,221 triggered entries; Stop order beyond the pattern's extreme. 32 of these entries are not among the 13,189 trades: still open at the end of our data, or left out by the trade rules.
Time to the 2:1 target, when hit: 6 days · middle half 3 to 12 · on 3,800 trades that hit it
Time to the stop, when hit: 3 days · middle half 1 to 7 · on 9,338 trades that hit it
Time in the trade, all exits: 4 days · middle half 2 to 8 · on 13,189 trades

Size and trade path

Pattern range, high to low: 2.8% · middle half 2.0% to 4.1% · on 16,646 occurrences
Range vs average bar (ATR): 1.11× · middle half 1.01× to 1.27× · on 16,646 occurrences
Best open profit during the trade: 0.85 R · middle half 0.27 R to 2.05 R · on 13,189 trades
Stopped trades that were first up 1 R: 22.9% · on 9,338 stopped trades; Trades a stop moved to breakeven at +1 R would have closed flat instead of at a loss
Entry order triggered: 79.4% · on 16,646 occurrences

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 an uptrend: short body, upper shadow at least twice the body, very short lower shadow, range at least the average of the 10 previous candles. Candlestick counts are not checked against planted examples, so they may not be exhaustive.

All measurements (20 rows)

10-bar move: did price go the expected way?

Figures in gray: fewer than 30 occurrences, not interpreted. Excess return is signed so that positive favors the pattern. The test uses the bootstrap’s standard error and the interval its percentiles: near the 0.05 line, or on a few extreme moves, an interval can leave out zero while the test does not pass, and the test decides. Stock data misses most delisted companies, a survivorship bias we have not sized, which can flatter stock rows.
Market	Occurrences	Pattern	Random bars	Excess	10-bar move verdict
Crypto · 1-hour	32,439	52.2%	50.7%	−0.03%	No clear edge
Forex · 1-hour	4,333	48.0%	49.3%	−0.01%	Weak, below chance
All markets · 1-hour	36,772	51.7%	50.5%	−0.02%	No clear edge
Crypto · 4-hour	7,447	54.7%	52.0%	+0.18%	No clear edge
Forex · 4-hour	863	49.1%	49.4%	−0.02%	No clear edge
All markets · 4-hour	8,310	54.2%	51.7%	+0.16%	No clear edge
Crypto · Daily	986	57.6%	55.1%	+0.50%	No clear edge
US stocks · Daily	14,652	43.6%	45.4%	−0.14%	No clear edge
ETFs · Daily	350	39.7%	42.8%	+0.05%	No clear edge
Indices · Daily	317	35.3%	42.8%	−0.20%	No clear edge
Forex · Daily	197	44.7%	49.4%	−0.15%	No clear edge
Commodities · Daily	144	46.5%	47.8%	−0.28%	No clear edge
All markets · Daily	16,646	44.3%	46.0%	−0.10%	No clear edge
Crypto · Weekly	57	50.0%	60.5%	−17.09%	Not enough data
US stocks · Weekly	2,700	40.6%	42.0%	−0.53%	No clear edge
ETFs · Weekly	101	44.6%	38.0%	+0.70%	No clear edge
Indices · Weekly	40	35.0%	36.9%	−1.58%	No clear edge
Forex · Weekly	57	50.0%	49.7%	−0.40%	No clear edge
Commodities · Weekly	50	51.0%	47.5%	+3.07%	No clear edge
All markets · Weekly	3,005	41.2%	42.4%	−0.74%	No clear edge

2:1 trade: target hit and average result

R = initial risk of the trade. Entry by an order at the trigger level, filled at the open when a bar opens beyond it. Exit at the stop or the target, or at the open when a bar opens beyond either one; otherwise at the close after 100 bars. When one bar touches both the stop and the target, the loss is counted. No fees or slippage. n/a = not measured. Per trade: average result, against the same trade on random dates. Figures in gray: fewer than 30 closed trades, not interpreted.
Market	Trades	Target hit	Same trade, random dates	Per trade	2:1 trade verdict
Crypto · 1-hour	27,620	30.5%	31.8%	−0.05 R vs −0.01 R	No clear edge
Forex · 1-hour	3,678	30.7%	32.5%	−0.08 R vs −0.02 R	No clear edge
All markets · 1-hour	31,298	30.5%	31.9%	−0.05 R vs −0.01 R	Weak, below chance
Crypto · 4-hour	6,426	27.6%	29.5%	−0.11 R vs −0.07 R	No clear edge
Forex · 4-hour	746	31.6%	32.5%	−0.04 R vs −0.02 R	No clear edge
All markets · 4-hour	7,172	28.0%	29.8%	−0.11 R vs −0.06 R	No clear edge
Crypto · Daily	867	30.8%	29.8%	−0.02 R vs −0.04 R	No clear edge
US stocks · Daily	11,548	28.6%	29.5%	−0.15 R vs −0.12 R	No clear edge
ETFs · Daily	254	31.9%	30.0%	−0.04 R vs −0.12 R	No clear edge
Indices · Daily	253	24.5%	32.6%	−0.26 R vs −0.03 R	Weak, below chance
Forex · Daily	159	32.1%	34.0%	−0.02 R vs +0.02 R	No clear edge
Commodities · Daily	108	30.6%	31.7%	−0.07 R vs −0.05 R	No clear edge
All markets · Daily	13,189	28.8%	29.7%	−0.14 R vs −0.11 R	No clear edge
Crypto · Weekly	44	20.5%	22.2%	−0.39 R vs −0.30 R	Not enough data
US stocks · Weekly	2,115	24.9%	25.5%	−0.25 R vs −0.23 R	No clear edge
ETFs · Weekly	78	24.4%	27.6%	−0.28 R vs −0.16 R	No clear edge
Indices · Weekly	33	33.3%	33.1%	0.00 R vs −0.01 R	No clear edge
Forex · Weekly	48	41.7%	43.4%	+0.28 R vs +0.32 R	No clear edge
Commodities · Weekly	35	22.9%	17.1%	−0.33 R vs −0.49 R	No clear edge
All markets · Weekly	2,353	25.2%	25.9%	−0.24 R vs −0.22 R	No clear edge

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 shooting star candlestick pattern is a reliable bearish reversal signal.”

What our data shows

On 16,646 daily occurrences, it moved in the expected direction 44.3% of the time, against 46.0% 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	Occurrences	Down 10 bars later	Random bars	Closed trades	2:1 target hit	Same setup, random dates	Expectancy
All markets, daily	16,646	44.3%	46.0%	13,189	28.8%	29.7%	−0.14 R
US stocks, daily	14,652	43.6%	45.4%	11,548	28.6%	29.5%	−0.15 R
Crypto, hourly	32,439	52.2%	50.7%	27,620	30.5%	31.8%	−0.05 R
Crypto, 4-hour	7,447	54.7%	52.0%	6,426	27.6%	29.5%	−0.11 R
Forex, hourly	4,333	48.0%	49.3%	3,678	30.7%	32.5%	−0.08 R
All markets, weekly	3,005	41.2%	42.4%	2,353	25.2%	25.9%	−0.24 R

Read the table in pairs of columns. On the daily timeframe, 44.3% of shooting stars were followed by a fall 10 days later. That alone says little: 46.0% of random days on the same assets were too. The excess return over the rest of the market after 10 days is −0.10%, with a 95% confidence interval from −0.30% to +0.09%. Zero is inside the interval: no clear edge.

The 2:1 setup tells the same story. It reached its target in 28.8% of cases against 29.7% for the same entry, exit level and target on random dates, for an expectancy of −0.14 R per trade before costs, against −0.11 R at random. Both lose money: a 2:1 setup needs to win more than one time in three to break even before fees.

Statistical reliability of the pattern

Across the market and timeframe groups we could test, the expectancy of the 2:1 setup ranged from −0.33 R to +0.28 R, and no group showed an edge that survives our correction for multiple testing. The result did not change between the first and second half of the daily history (−0.04% and −0.16% of excess return). This is in line with academic work on the subject: in the study "Candlestick technical trading strategies: Can they create value for investors?" (Journal of Banking and Finance, vol. 30, 2006), Ben Marshall, Martin Young and Lawrence Rose found no benefit from candlestick rules on the Dow Jones components they tested.

Factors affecting success rates

The horizon matters a little. On the daily timeframe, the next bar was down 47.8% of the days against 48.1% for random days; after 20 days, 44.9% against 45.0%. Activity and the 200-day average changed the target-hit rate by about one point or less. The full table, with every market and timeframe, is in the statistics section of this page, and the method is in our methodology.

Real examples of the shooting star

The gallery in this section shows real shooting stars picked by our bench, with their actual outcome. The written-up cases below are not gallery cards: they come from our bench's detections on daily crypto data. These are recorded market sessions, not simulations, and none of the three written-up cases reached its 2:1 target.

Case study: the right call, stopped anyway

On April 22, 2026, BNB/USDT printed a shooting star with a top at 654.19 and a bottom at 631.19. The sell order at the bottom was triggered the next day, with a stop at 654.19 and a 2:1 target at 585.19. Price slid to 610.26 within a week, then climbed back and traded above the top 13 days after entry: a full 1 R loss, although BNB was 3.0% lower 10 days after the signal.

Case study: stopped out

On July 14, 2025, SOL/USDT printed another, with a top at 168.65 and a bottom at 160.61. The entry was triggered the next day, and one day after entry price traded above the top: a full 1 R loss. Ten days later, SOL was 12.7% higher.

Case study: canceled before entry

On May 13, 2026, BNB/USDT printed a shooting star with a top at 685.68 and a bottom at 663.77. The next day price broke the top before the bottom, so the setup was canceled without a trade. BNB was 2.3% lower 10 days later: a canceled setup can be followed by the decline it predicted, which is one more reason not to judge it by memorable cases.

Execution tips

Scanning for patterns on higher timeframes

Weekly occurrences are rarer and cover more of the market's story, but they did no better against chance in our data: 25.2% of 2:1 targets hit, against 25.9% at random, and −0.24 R against −0.22 R per trade, a gap that is not statistically significant. Charting platforms such as TradingView can scan for this formation, and the open-source TA-Lib library provides a CDLSHOOTINGSTAR function. Check which definition your tool uses, because thresholds differ from one tool to the next.

Managing trades during high volatility

When volatility rises, the wick grows, so the distance to the exit level grows too. Keep each loss a small, fixed share of the account and size the position on that distance. Our data shows the median losing setup fails within 3 days on the daily timeframe.

Frequently asked questions

Is the shooting star a bullish or bearish pattern?

By definition it points down: it appears after a rise and is read as a potential reversal. In our data, its average excess return over the rest of the market was within the margin of error, apart from a weak result on hourly forex, where it moved against the expected direction relative to its market.

Does the color of the candle matter?

Not for the definition, and we have not measured whether a red one does better. Our published statistics count both colors together.

How accurate is the shooting star pattern?

On 16,646 daily occurrences, 44.3% were down 10 days later, against 46.0% for random days. The 2:1 setup (13,189 closed trades) hit its target in 28.8% of cases, close to the 29.7% of random entries (−0.14 R against −0.11 R, a gap too small to separate from chance).

Can I use this pattern for day trading?

Yes, it forms on intraday timeframes, but on hourly forex charts it slightly moved against the expected direction relative to its market, and on hourly crypto and forex charts its 2:1 trade did no better than the same trade on random dates. Costs weigh more when each move is small.

What is the difference between a shooting star and a hanging man?

Both appear after a rally. The shooting star has a long upper shadow; the hanging man has a tall wick underneath.

What happens if there is a long lower shadow?

Then it no longer qualifies. Wicks on both sides describe a high-wave bar, a sign of indecision.

Key takeaways for traders

A shooting star has a small body at the bottom, a top wick at least twice its size and almost no wick underneath, after an uptrend.
The same shape after a decline is an inverted hammer.
On 16,646 daily occurrences, 44.3% were down 10 days later, against 46.0% for random days.
The 2:1 short setup reached its target in 28.8% of cases, against 29.7% for the same setup on random dates, with a negative expectancy of −0.14 R before costs.
Volume and the 200-day moving average changed the results only slightly.

If you trade it, treat it as a location for a trade, not a reason for one. Define the exit level above the top before entry, size the position on that distance and keep the risk small. Any edge has to come from what you combine it with.

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.

How we tested this pattern

Every pattern's results on one sheet