momentummedium-high risk
MACD Crossover Strategy (Crypto)
Does a MACD crossover strategy work on crypto? Backtested on real Hyperliquid perps from 2024-08-15 to 2026-09-29, the default settings earned a Sharpe of 1.87 — +408.8% total return with a 33.3% worst drawdown across 2,746 trades in 1,142 positions, net of fees, slippage, and funding.
By Keel Research · Data as of 2026-09-29 · how this backtest was produced
Sharpe
1.87
default settings
Total return
+408.8%
Worst drawdown
−33.3%
Trades
2,746
2024-08-15 → 2026-09-29 · net of fees, slippage, and funding · price-only Sharpe 2.00 · these are the default settings, not a hand-picked best case.
At $1,000, this strategy’s worst historical dip was about $333. Free account, your own Hyperliquid keys — Keel only trades.
How it works
How it works
This strategy trades the top-15 Hyperliquid perpetuals on four-hour bars. It goes long a coin when its MACD histogram (12/26/9) turns positive — a confirmed shift in momentum — and its price is above its 200-bar average, which keeps entries on the trending side. Otherwise it holds cash. Positions are equal-weight, 1x gross, long-or-flat, and it trades only when a position drifts 20% from target.
When it works best
Sustained, multi-day trends — exactly the legs the four-hour timeframe is quick enough to catch. The timeframe is the whole edge here: the identical rules run on daily bars barely break even, because by the time a daily MACD confirms, crypto's move is largely over. The MACD periods themselves make little difference. Over 2024-08-15 to 2026-09-29 the default four-hour settings returned +408.8% with a Sharpe of 1.87 and a maximum drawdown of −33.3%, net of fees, slippage, and funding.
When it struggles
Choppy, directionless markets, where the trend filter flips on and off and each entry gives back a little. It is long-or-flat, so it sits out downtrends rather than profiting from them, and drawdowns can run deep — the test window saw a −33.3% maximum. At 2,746 trades over the window, turnover is meaningful, so fees matter.
How it’s built
The exact strategy behind this backtest — no black box. Switch to code to see or copy the full definition.
Configuration
Globalsconfig
target_timeframe4h
UniverseassetsTop by Volume · HL Perps · 15 assets15 resolved
Executiontrading
rebalanceOn Change
Factories
trend_vs_200factory
Pipeline7 steps
PriceDataLoaderData Loader
ohlcvstore
Parallel2 branches
entries
Parallel2 branches
const
ConstantForecastForecast Mapper
value1
setup
Parallel2 branches
macd_up
MACDIndicator
fast_period12slow_period26signal_period9
AboveThresholdFilterSignal Transform
threshold0
uptrend
trend_vs_200call
AboveThresholdFilterSignal Transform
threshold0
MaskAndSignal Composer
ApplyMaskSignal Composer
score_signalconstfilter_signalsetup
macd_entrystore
exits
Parallel2 branches
const
ConstantForecastForecast Mapper
value1
cross_down
MACDIndicator
fast_period12slow_period26signal_period9
BelowThresholdFilterSignal Transform
threshold0
ApplyMaskSignal Composer
score_signalconstfilter_signalcross_down
macd_exitstore
TradeManagerPosition Manager
entriesmacd_entrypricesohlcv
Parallel1 branches
macd_cross_down
macd_exitload
ExitPosition Manager
ExposurePosition Manager
EqualWeightSizerPosition Sizer
target_leverage1max_weight0.2
Globals(target_timeframe="4h")Universe(mode="top_volume", top_n=15, market="perp", resolved=["BTC", "DOGE", "ETH", "GRAM", "HYPE", "LINK", "LIT", "PUMP", "SOL", "SUI", "VVV", "XPL", "XRP", "ZEC", "kPEPE"], resolved_at="2026-07-06T20:36:37.412320+00:00")Execution(rebalance="on_change")trend_vs_200 = Pipeline([ { "px": [EWMA(window=2)], "trend": [EWMA(window=200)], }, Crossover(fast_key="px", slow_key="trend"),], name="trend_vs_200")Pipeline([ PriceDataLoader(), Store("ohlcv"), { "entries": [ Pipeline([ { "const": [ConstantForecast(value=1.0)], "setup": [ Pipeline([ { "macd_up": [MACD(fast_period=12, slow_period=26, signal_period=9), AboveThresholdFilter(threshold=0.0)], "uptrend": [trend_vs_200, AboveThresholdFilter(threshold=0.0)], }, MaskAnd(), ], name="setup"), ], }, ApplyMask(score_signal="const", filter_signal="setup"), Store("macd_entry"), ], name="entries"), ], "exits": [ Pipeline([ { "const": [ConstantForecast(value=1.0)], "cross_down": [MACD(fast_period=12, slow_period=26, signal_period=9), BelowThresholdFilter(threshold=0.0)], }, ApplyMask(score_signal="const", filter_signal="cross_down"), Store("macd_exit"), ], name="exits"), ], }, TradeManager(entries="macd_entry", prices="ohlcv"), { "macd_cross_down": [Load("macd_exit"), Exit()], }, Exposure(), EqualWeightSizer(target_leverage=1.0, max_weight=0.2),], name="macd_crossover_crypto")Explore the settings
precomputed · updates instantlyAdjust a setting to see the exact backtested result — including the ones that lost money.
Complete 16-cell public cross-product on explicit resolved universes.
MACD periods
Signal timeframe
Pinned universe
Sharpe
1.87
Return
408.8%
Worst DD
−33.3%
Trades
2,746
At $1,000, these settings' worst historical dip was about $333. You land in the editor with this exact setup. Free account, your own keys.
Compare all 16 settings
| Settings | Sharpe | Return | Worst DD | Trades |
|---|---|---|---|---|
| MACD 8/17/9 · Signal 4h · Pinned top8_launch | 1.36 | 128.4% | −27.3% | 1,020 |
| MACD 8/17/9 · Signal 4h · Pinned top15_launch | 1.92 | 422.3% | −33.5% | 3,227 |
| MACD 8/17/9 · Signal 1d · Pinned top8_launch | 0.41 | 15.7% | −30.1% | 89 |
| MACD 8/17/9 · Signal 1d · Pinned top15_launch | 0.42 | 19.8% | −38.1% | 256 |
| MACD 12/26/9 · Signal 4h · Pinned top8_launch | 1.18 | 103.7% | −27.5% | 798 |
| MACD 12/26/9 · Signal 4h · Pinned top15_launchdefault | 1.87 | 408.8% | −33.3% | 2,746 |
| MACD 12/26/9 · Signal 1d · Pinned top8_launch | 0.22 | 5.3% | −37.4% | 92 |
| MACD 12/26/9 · Signal 1d · Pinned top15_launch | 0.48 | 25.8% | −46.9% | 248 |
| MACD 19/39/9 · Signal 4h · Pinned top8_launch | 1.05 | 89.0% | −32.5% | 698 |
| MACD 19/39/9 · Signal 4h · Pinned top15_launch | 1.61 | 295.7% | −33.7% | 2,314 |
| MACD 19/39/9 · Signal 1d · Pinned top8_launch | 0.52 | 21.1% | −36.2% | 68 |
| MACD 19/39/9 · Signal 1d · Pinned top15_launch | 0.92 | 73.6% | −47.8% | 187 |
| MACD 24/52/18 · Signal 4h · Pinned top8_launch | 0.84 | 64.7% | −29.4% | 536 |
| MACD 24/52/18 · Signal 4h · Pinned top15_launch | 1.17 | 165.3% | −40.4% | 1,848 |
| MACD 24/52/18 · Signal 1d · Pinned top8_launch | 0.42 | 15.8% | −31.1% | 46 |
| MACD 24/52/18 · Signal 1d · Pinned top15_launch | 0.81 | 63.2% | −39.6% | 151 |
The data
Monthly returns
| Month | Return |
|---|---|
| 2024-08 | 0.0% |
| 2024-09 | +14.5% |
| 2024-10 | +6.0% |
| 2024-11 | +72.2% |
| 2024-12 | -9.7% |
| 2025-01 | -1.1% |
| 2025-02 | -5.1% |
| 2025-03 | -9.3% |
| 2025-04 | +11.7% |
| 2025-05 | +3.4% |
| 2025-06 | +1.1% |
| 2025-07 | +6.9% |
| 2025-08 | -1.5% |
| 2025-09 | +29.4% |
| 2025-10 | -3.4% |
| 2025-11 | -2.5% |
| 2025-12 | +3.2% |
| 2026-01 | +30.9% |
| 2026-02 | +10.9% |
| 2026-03 | -0.8% |
| 2026-04 | -4.2% |
| 2026-05 | +26.6% |
| 2026-06 | -12.0% |
| 2026-07 | -6.0% |
| 2026-08 | +20.8% |
| 2026-09 | +17.2% |
Which assets it traded
| Avg allocation | Days held | % of time held | Asset |
|---|---|---|---|
| 0.1573 | 1242 | 26.71 | BTC |
| 0.1532 | 1219 | 26.22 | LINK |
| 0.1677 | 1166 | 25.08 | HYPE |
| 0.1528 | 1158 | 24.9 | ETH |
| 0.1507 | 1096 | 23.57 | SOL |
| 0.1559 | 997 | 21.44 | XRP |
| 0.1493 | 973 | 20.92 | SUI |
| 0.1498 | 966 | 20.77 | DOGE |
| 0.1474 | 930 | 20 | kPEPE |
| 0.1659 | 852 | 18.32 | VVV |
| 0.165 | 626 | 13.46 | ZEC |
| 0.1546 | 605 | 13.01 | PUMP |
| 0.1609 | 444 | 9.55 | LIT |
| 0.1574 | 348 | 7.48 | XPL |
| 0.1268 | 69 | 1.48 | GRAM |
What this is: a historical backtest on real Hyperliquid market data, net of fees, slippage, and funding. Its worst historical drawdown was 33.3% — expect drawdowns of that order or worse. Past performance does not predict future results, and this is not investment advice. Size your account so a full drawdown is survivable.