Key results
- Total return
- +23.7%
- Buy & hold: +21.2%
- Annual return (CAGR)
- +11.2%
- Buy & hold: +10.1%
- Max drawdown
- -3.9%
- Buy & hold: -18.9%
- Win rate
- 41.43%
- Profit factor
- 1.95
- Trades
- 70
- Longest losing streak
- 7 trades
- Period
- Oct 2, 2024 to Oct 1, 2026
- 2 years
- Market
- US30/USD
- 1-minute
Equity curve vs buy & hold
Returns year by year
| Year | Return | Trades |
|---|---|---|
| 2024 | +2.7% | 7 |
| 2025 | +13.2% | 39 |
| 2026 | +6.4% | 24 |
Calendar years, compounded from monthly results. The first and last years can be partial.
The liquidity sweep is one of the most discussed setups in ICT and smart money concepts trading. The idea: when several lows line up at the same price, stop-loss orders pile up just below them. A fast push through that level triggers those stops, and if price immediately closes back above, the drop was a hunt for liquidity rather than a real breakdown. Traders buy the reclaim. We tested that reading on the Dow Jones, on the 1-minute chart.
The rules we tested
- Market: Dow Jones (US30/USD), 1-minute candles.
- Period: 2 October 2024 to 1 October 2026, two years. This page does not cover a longer history.
- Entry: buy when a liquidity sweep of equal lows completes: a candle wicks below a pool of equal lows and closes back above it.
- Exit: a fixed stop-loss of 250 index points and a fixed take-profit of 750 points, a 1:3 risk-reward.
- Direction: long only. The strategy does not trade sweeps of equal highs.
- Costs: 0.02% commission per side, full position size on each trade.
What the backtest shows
The strategy returned +24% over two years, about 11.2% a year, from 70 trades. Buy and hold on the Dow returned +21% over the same window, about 10.1% a year. That makes this one of the few strategies in our library that finished ahead of its benchmark.
The bigger difference is risk. The strategy's maximum drawdown was about 3.9%, against about 18.9% for the index. It was only in the market for short stretches, so it never sat through the index's larger declines.
About 41% of trades won. The 1:3 structure did the heavy lifting: the average win was about 1.7% against an average loss of about 0.6%, for a profit factor of 1.95. Of the 70 trades, 41 hit the stop and 29 hit the target. The longest losing streak was seven trades.
By year: the last three months of 2024 made +2.7% on 7 trades, 2025 made +13.2% on 39 trades (16 winners), and 2026 to date made +6.4% on 24 trades (10 winners). Every period finished positive.
A good result on a small sample
70 trades over two years is a modest sample, and it all comes from one market regime. A few lucky or unlucky trades would move these numbers noticeably. Treat this as a promising lead to test further, not as proof.
Why it works, at least here
The setup combines a precise location with a clear failure point. Equal lows are visible to everyone, so they attract stops; a close back above them is concrete evidence that sellers could not hold the break. The stop sits beyond the sweep, and the 1:3 target lets a minority of winners pay for the losers.
The strategy is also very selective: about 35 trades a year despite running on 1-minute data. That keeps commissions low and means each trade is a distinct event rather than noise.
What you could test next
- Run it over a longer history, if your data allows, to see whether the edge survives other market regimes.
- Add the short side, selling the mirror setup on sweeps of equal highs, in a separate test.
- Move it to the 5-minute chart, where the same idea produces fewer but larger sweeps.
- Test the same rules on the Nasdaq 100 or gold to check the edge is not specific to the Dow.
Methodology and assumptions
- Starting capital
- 10,000
- Position size
- 100% of equity
- Commission
- 0.02% per side
- Data window
- Oct 2, 2024 to Oct 1, 2026
- Run date
- October 2, 2026
- No repainting: every signal is computed on closed candles only, so the backtest never acts on a price a trader could not have seen yet.
- Past performance does not predict future results. A backtest is a historical simulation, not a forecast.
Frequently asked questions
What is a liquidity sweep in trading?
A liquidity sweep is a quick move through a level where many stop orders likely sit, such as a cluster of equal lows, followed by a fast return. In ICT and smart money concepts, it is read as larger players triggering those stops to fill their own orders before the real move.
What win rate did the liquidity sweep strategy have?
About 41% over 70 trades. Winners averaged about 1.7% and losers about 0.6%, so the strategy made close to two dollars for every dollar lost (profit factor 1.95).
Why only two years of data for this backtest?
The strategy runs on the 1-minute chart, and this run covers 2 October 2024 to 1 October 2026. It is a real result over that window, but two years is one market regime, not a full cycle.
Can I trade the liquidity sweep on other markets?
The same rules can be run on other indices, gold or forex pairs. Whether the edge holds elsewhere is exactly what a backtest should answer before you risk money on it.
Reproduce it, then change it
Every number on this page comes from the Backtrex engine. Rebuild the strategy in the app, then change the market, the timeframe or a parameter and see whether the result holds.
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