Does the ICT fair value gap strategy work on the Nasdaq?

Key results

Total return

+37.7%

Buy & hold: +527.2%

Annual return (CAGR)

+3.3%

Buy & hold: +20.2%

Max drawdown

-23.7%

Buy & hold: -37.5%

Win rate

27%

Profit factor

1.08

Trades

852

Longest losing streak

14 trades

Period

Oct 3, 2016 to Oct 1, 2026

10 years

Market

NAS100/USD

15-minute

Equity curve vs buy & hold

Returns year by year

Calendar years, compounded from monthly results. The first and last years can be partial.

The fair value gap is one of the core ideas in ICT (Inner Circle Trader) material: a fast, one-sided move leaves an imbalance on the chart, and price tends to return to it before continuing. A popular way to trade it follows a multi-timeframe logic. Find the zone on a higher timeframe, wait for price to reach it, confirm on a lower timeframe, and only trade in the direction of the higher-timeframe trend. We built exactly that structure on the Nasdaq 100 and ran it over ten years.

The rules we tested

• Market: Nasdaq 100 (NAS100/USD), base chart 15 minutes.
• Period: 3 October 2016 to 1 October 2026, ten years.
• Zone (1 hour): price traded into a bullish fair value gap on the 1-hour chart at least once within the last 12 fifteen-minute bars (three hours).
• Trigger (15 minutes): a bullish engulfing candle prints on the 15-minute chart.
• Bias (4 hours): the 4-hour close is above its 50-period EMA.
• Entry: buy when all three conditions are true together.
• Exit: a fixed stop-loss of 100 index points and a fixed take-profit of 300 points, a 1:3 risk-reward.
• Direction: long only. No short trades.
• Costs: 0.02% commission per side, full position size on each trade.

What the backtest shows

The strategy returned +38% in ten years, about 3.3% a year, from 852 trades. Buy and hold on the Nasdaq 100 returned +527%, about 20.2% a year. The maximum drawdown was about 24%, smaller than the index's 38%, but nowhere near enough to justify the missing return.

Only 27% of trades won: 622 trades hit the stop and 229 hit the target. With a target three times the stop, the break-even win rate before costs is 25%, so the strategy lived just above the line, for a profit factor of 1.08. The average win was about 2.15% of the account and the average loss about 0.73%, and the longest losing streak was 14 trades in a row.

Costs matter at this frequency. Each round trip pays 0.04% of the position, and 852 round trips add up to about 34% of position value paid in commissions over the decade. On a strategy whose edge is this thin, that is a large share of what it earned.

The yearly table tells a clear story. 2020 was the best year at +25%, with 32 winners out of 92 trades, and 2017 and 2019 followed at +20% and +18%. 2022 was the worst at -17%, with only 16 winners out of 96 trades. Since then the strategy has drifted: 2024 finished flat (-0.04%), 2025 lost 4.56% and 2026 so far 2.04%, while trade count rose to its highest level (158 trades in 2025).

Why it works, and where it falls short

Each piece of the setup makes sense on its own: the gap gives a location, the engulfing candle shows buyers reacting there, the 4-hour EMA keeps you with the trend. Together they did produce a small positive edge over ten years.

But the Nasdaq rose so steadily that almost any long exposure made money, and a strategy that holds for a few hours at a time captures only a sliver of that. In recent years the edge faded, and one likely reason is the fixed point stop: the higher the index, the smaller 100 points is relative to its normal swings, so ordinary noise reaches the stop more often.

What you could test next

• Scale the stop to volatility, for example as a multiple of ATR, instead of a fixed number of points.
• Lower the target to 1:2 and see whether the higher win rate beats the smaller payoff.
• Keep the 15-minute trigger but move the zone to the 4-hour chart, so fewer, stronger gaps qualify.
• Add a session filter so entries happen only around the New York open.

Methodology and assumptions

Frequently asked questions

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.

Other backtests