Best MACD settings for crypto perps

You can adjust MACD periods, Signal timeframe, Universe size (top by volume). The config explorer on this page lets you compare every setting we tested — including the ones that underperformed — with the exact backtested result for each.

momentummedium-high risk

MACD Crossover Strategy (Crypto)

Name: MACD Crossover Strategy (Crypto) — backtest results (Hyperliquid, 2024-08-15→2026-07-05)
Creator: Keel

Does a MACD crossover strategy work on crypto? Backtested on real Hyperliquid perps from 2024-08-15 to 2026-07-05, the default settings earned a Sharpe of 1.83 — +274.9% total return with a 31.7% worst drawdown across 5,205 trades, net of fees, slippage, and funding.

By Keel Research · Data as of 2026-07-05 · how this backtest was produced

Sharpe

1.83

default settings

Total return

+274.9%

Worst drawdown

−31.7%

Trades

5,205

2024-08-15 → 2026-07-05 · net of fees, slippage, and funding · price-only Sharpe 1.95 · 5,205 trades — the numbers already include that turnover cost.

Run this live →Fork & customize

At $1,000, this strategy’s worst historical dip was about $317. Free account, your own Hyperliquid keys — Keel only trades.

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 2026-07-05 the default four-hour settings returned +274.9% with a Sharpe of 1.83 and a maximum drawdown of −31.7%, 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 −31.7% maximum. At 5,205 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 assets

Executiontrading

rebalanceEvery Bar

Factories

trend_vs_200factory

Pipeline5 steps

PriceDataLoaderData Loader

timeframe15min

TargetTimeframeResamplerData Transform

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

PositionStateMachinePosition Manager

entry_slotmacd_entryexit_slotmacd_exit

EqualWeightSizerPosition Sizer

target_leverage1max_weight0.2

Globals(target_timeframe="4h")

Universe(mode="top_volume", top_n=15, market="perp", resolved=[], resolved_at="")

Execution(rebalance="every_bar")

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(timeframe="15min"),
    TargetTimeframeResampler(),
    {
        "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"),
        ],
    },
    PositionStateMachine(entry_slot="macd_entry", exit_slot="macd_exit"),
    EqualWeightSizer(target_leverage=1.0, max_weight=0.2),
], name="macd_crossover_crypto")

Globals(target_timeframe="4h")Universe(mode="top_volume", top_n=15, market="perp", resolved=[], resolved_at="")Execution(rebalance="every_bar")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(timeframe="15min"),    TargetTimeframeResampler(),    {        "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"),        ],    },    PositionStateMachine(entry_slot="macd_entry", exit_slot="macd_exit"),    EqualWeightSizer(target_leverage=1.0, max_weight=0.2),], name="macd_crossover_crypto")

Explore the settings

precomputed · updates instantly

Adjust a setting to see the exact backtested result — including the ones that lost money.

MACD periods

Universe size (top by volume)

Sharpe

1.83

Return

274.9%

Worst DD

−31.7%

Trades

5,205

Heads up: high turnover.

Run these settings live →Fork & customize

At $1,000, these settings' worst historical dip was about $317. You land in the editor with this exact setup. Free account, your own keys.

Compare all 5 settings

Settings	Sharpe	Return	Worst DD	Trades
MACD 12/26/9 · tf 4h · Universe 15default	1.83	274.9%	−31.7%	5,205
MACD 8/17/9 · tf 4h · Universe 15	1.65	214.9%	−32.3%	5,168
MACD 12/26/9 · tf 4h · Universe 25	1.20	163.9%	−48.9%	9,500
MACD 12/26/9 · tf 4h · Universe 8	1.05	64.5%	−29.7%	2,889
MACD 12/26/9 · tf 1d · Universe 15	-0.10	-13.1%	−38.9%	438

The data

Monthly returns

Month	Return
2024-08	0.0%
2024-09	+10.6%
2024-10	+5.5%
2024-11	+70.4%
2024-12	-5.7%
2025-01	-3.4%
2025-02	-6.0%
2025-03	-7.2%
2025-04	+9.8%
2025-05	+4.5%
2025-06	+2.8%
2025-07	+7.6%
2025-08	-0.4%
2025-09	+28.7%
2025-10	-3.1%
2025-11	-2.7%
2025-12	+3.3%
2026-01	+29.9%
2026-02	+9.9%
2026-03	-1.3%
2026-04	-6.8%
2026-05	+29.8%
2026-06	-15.7%
2026-07	+4.2%

Which assets it traded

Avg allocation	Days held	% of time held	Asset
0.1766	1001	24.21	HYPE
0.1664	994	24.04	BTC
0.1599	956	23.13	LINK
0.1605	916	22.16	ETH
0.165	859	20.78	XRP
0.1592	795	19.23	DOGE
0.159	784	18.96	SOL
0.1572	747	18.07	SUI
0.1739	698	16.88	VVV
0.1547	663	16.04	kPEPE
0.177	419	10.14	ZEC
0.1617	388	9.39	PUMP
0.1713	239	5.78	XPL
0.1719	185	4.48	LIT
0	0	0	GRAM

What this is: a historical backtest on real Hyperliquid market data, net of fees, slippage, and funding. Its worst historical drawdown was 31.7% — 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.

MACD Crossover Strategy (Crypto)

How it works

How it works

When it works best

When it struggles

How it’s built

Configuration

Factories

Explore the settings

The data

Monthly returns

Which assets it traded

Common questions

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