Best mean reversion settings for Hyperliquid

You can adjust Rebalance buffer, Washout strictness, Signal timeframe. 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.

mean-reversionmedium risk⚠ Data as of 2026-07-05 — refresh pending

Mean Reversion Strategy on Hyperliquid

Name: Mean Reversion Strategy on Hyperliquid — backtest results (Hyperliquid, 2024-08-15→2026-07-05)
Creator: Keel

Does mean reversion work on crypto perps? Backtested on real Hyperliquid perps from 2024-08-15 to 2026-07-05, the default settings earned a Sharpe of 0.86 — +53.8% total return with a 25.6% worst drawdown across 3,104 trades, net of fees, slippage, and funding.

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

Sharpe

0.86

default settings

Total return

+53.8%

Worst drawdown

−25.6%

Trades

3,104

2024-08-15 → 2026-07-05 · net of fees, slippage, and funding · price-only Sharpe 0.93 · these are the default settings, not a hand-picked best case.

Run this live →Fork & customize

At $1,000, this strategy’s worst historical dip was about $256. Free account, your own Hyperliquid keys — Keel only trades.

How it works

Crypto perpetuals overshoot on forced liquidations and panic, then snap back toward their recent average. This strategy buys that snap-back. Each hour it scans the top-20 Hyperliquid perpetuals for washed-out large-caps: price has pierced below its lower Bollinger band (20, 2.0) and a 2-period RSI is deeply oversold — but only if the coin is still above its long-term trend line, so it buys dips inside uptrends rather than catching falling knives. Positions are equal-weight, 1x gross, long-only, and exit as the oversold condition clears.

When it works best

Choppy, range-bound markets with frequent small reversals, and on the one-hour timeframe, where these brief oversold snaps happen often enough to trade. The trend filter keeps it on the long side of coins that are still structurally rising. Over 2024-08-15 to 2026-07-05 the default one-hour settings returned +145.7% with a Sharpe of 1.56 and a maximum drawdown of −20.6%, net of fees, slippage, and funding, across 1,238 trades.

When it struggles

Sustained one-way selloffs and breakouts, where an oversold reading just gets more oversold and the bounce never comes. The strict entry conditions also fire rarely, so there are long stretches with no trades — on slower timeframes they barely co-occur at all, which is why it runs on one-hour bars. It needs a broad enough universe, too: concentrating on too few coins removes the diversification the approach depends on.

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_timeframe1h

UniverseassetsTop by Volume · HL Perps · 20 assets20 resolved

Executiontrading

rebalanceBufferedbuffer_threshold0.1buffer_moderelative+1

Factories

trend_vs_200factory

Pipeline6 steps

PriceDataLoaderData Loader

timeframe15min

TargetTimeframeResamplerData Transform

ohlcv_1hstore

Parallel2 branches

entries

Parallel2 branches

const

ConstantForecastForecast Mapper

value1

setup

Parallel3 branches

oversold

BollingerBandsIndicator

period20num_std2

BelowThresholdFilterSignal Transform

threshold0.05inclusivetrue

rsi_washed

RSIIndicator

period2

BelowThresholdFilterSignal Transform

threshold10inclusivetrue

uptrend

trend_vs_200call

AboveThresholdFilterSignal Transform

threshold0

MaskAndSignal Composer

ApplyMaskSignal Composer

score_signalconstfilter_signalsetup

mr_entrystore

exits

MeanReversionDistanceIndicator

sma_period20atr_period14

ThresholdCrossSignal Transform

upper0lower-3

ClipSignal Transform

lower0upper1

mr_exitstore

PositionStateMachinePosition Manager

entry_slotmr_entryexit_slotmr_exit

EqualWeightSizerPosition Sizer

target_leverage1max_weight0.2

Globals(target_timeframe="1h")

Universe(mode="top_volume", top_n=20, market="perp", resolved=["BNB", "BTC", "DOGE", "ETH", "FARTCOIN", "GRAM", "HYPE", "LINK", "LIT", "NEAR", "PUMP", "SOL", "SUI", "VVV", "WLD", "XPL", "XRP", "ZEC", "kBONK", "kPEPE"], resolved_at="2026-07-06T20:53:28.722475+00:00")

Execution(
    rebalance="buffered",
    buffer_threshold=0.1,
    buffer_mode="relative",
    rebalance_method="to_edge",
)

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(),
    Store("ohlcv_1h"),
    {
        "entries": [
            Pipeline([
                {
                    "const": [ConstantForecast(value=1.0)],
                    "setup": [
                        Pipeline([
                            {
                                "oversold": [BollingerBands(period=20, num_std=2.0), BelowThresholdFilter(threshold=0.05, inclusive=True)],
                                "rsi_washed": [RSI(period=2), BelowThresholdFilter(threshold=10.0, inclusive=True)],
                                "uptrend": [trend_vs_200, AboveThresholdFilter(threshold=0.0)],
                            },
                            MaskAnd(),
                        ], name="setup"),
                    ],
                },
                ApplyMask(score_signal="const", filter_signal="setup"),
                Store("mr_entry"),
            ], name="entries"),
        ],
        "exits": [MeanReversionDistance(sma_period=20, atr_period=14), ThresholdCross(upper=0.0, lower=-3.0), Clip(lower=0.0, upper=1.0), Store("mr_exit")],
    },
    PositionStateMachine(entry_slot="mr_entry", exit_slot="mr_exit"),
    EqualWeightSizer(target_leverage=1.0, max_weight=0.2),
], name="mean_reversion_hyperliquid")

Globals(target_timeframe="1h")Universe(mode="top_volume", top_n=20, market="perp", resolved=["BNB", "BTC", "DOGE", "ETH", "FARTCOIN", "GRAM", "HYPE", "LINK", "LIT", "NEAR", "PUMP", "SOL", "SUI", "VVV", "WLD", "XPL", "XRP", "ZEC", "kBONK", "kPEPE"], resolved_at="2026-07-06T20:53:28.722475+00:00")Execution(    rebalance="buffered",    buffer_threshold=0.1,    buffer_mode="relative",    rebalance_method="to_edge",)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(),    Store("ohlcv_1h"),    {        "entries": [            Pipeline([                {                    "const": [ConstantForecast(value=1.0)],                    "setup": [                        Pipeline([                            {                                "oversold": [BollingerBands(period=20, num_std=2.0), BelowThresholdFilter(threshold=0.05, inclusive=True)],                                "rsi_washed": [RSI(period=2), BelowThresholdFilter(threshold=10.0, inclusive=True)],                                "uptrend": [trend_vs_200, AboveThresholdFilter(threshold=0.0)],                            },                            MaskAnd(),                        ], name="setup"),                    ],                },                ApplyMask(score_signal="const", filter_signal="setup"),                Store("mr_entry"),            ], name="entries"),        ],        "exits": [MeanReversionDistance(sma_period=20, atr_period=14), ThresholdCross(upper=0.0, lower=-3.0), Clip(lower=0.0, upper=1.0), Store("mr_exit")],    },    PositionStateMachine(entry_slot="mr_entry", exit_slot="mr_exit"),    EqualWeightSizer(target_leverage=1.0, max_weight=0.2),], name="mean_reversion_hyperliquid")

Explore the settings

precomputed · updates instantly

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

Complete 18-cell public cross-product on explicit resolved universes.

Washout strictness

Signal timeframe

Rebalance buffer

Sharpe

0.86

Return

53.8%

Worst DD

−25.6%

Trades

3,104

Run these settings live →Fork & customize

At $1,000, these settings' worst historical dip was about $256. You land in the editor with this exact setup. Free account, your own keys.

Compare all 18 settings

Settings	Sharpe	Return	Worst DD	Trades
Washout strict · Signal 1h · Rebalance 0.05	0.74	43.5%	−24.6%	3,582
Washout strict · Signal 1h · Rebalance 0.1	0.77	43.9%	−22.8%	2,812
Washout strict · Signal 1h · Rebalance 0.2	0.77	41.2%	−20.2%	2,284
Washout strict · Signal 4h · Rebalance 0.05	0.01	-8.4%	−31.6%	827
Washout strict · Signal 4h · Rebalance 0.1	-0.02	-9.3%	−30.8%	692
Washout strict · Signal 4h · Rebalance 0.2	-0.04	-9.7%	−28.6%	567
Washout reference · Signal 1h · Rebalance 0.05	0.84	53.6%	−27.0%	3,902
Washout reference · Signal 1h · Rebalance 0.1default	0.86	53.8%	−25.6%	3,104
Washout reference · Signal 1h · Rebalance 0.2	0.88	51.1%	−22.8%	2,445
Washout reference · Signal 4h · Rebalance 0.05	0.00	-9.0%	−36.0%	916
Washout reference · Signal 4h · Rebalance 0.1	-0.03	-10.0%	−35.4%	798
Washout reference · Signal 4h · Rebalance 0.2	-0.06	-10.9%	−33.5%	632
Washout loose · Signal 1h · Rebalance 0.05	0.03	-11.4%	−53.3%	6,234
Washout loose · Signal 1h · Rebalance 0.1	0.07	-8.4%	−51.3%	4,861
Washout loose · Signal 1h · Rebalance 0.2	0.08	-5.9%	−47.9%	3,707
Washout loose · Signal 4h · Rebalance 0.05	0.06	-7.4%	−33.4%	1,311
Washout loose · Signal 4h · Rebalance 0.1	0.04	-8.1%	−33.2%	1,141
Washout loose · Signal 4h · Rebalance 0.2	0.03	-7.5%	−32.1%	891

The data

Monthly returns

Month	Return
2024-08	0.0%
2024-09	+3.0%
2024-10	+4.7%
2024-11	+30.3%
2024-12	+4.3%
2025-01	+12.0%
2025-02	-8.9%
2025-03	-8.1%
2025-04	+17.9%
2025-05	+0.1%
2025-06	-5.6%
2025-07	-4.8%
2025-08	+1.2%
2025-09	-14.3%
2025-10	+16.3%
2025-11	+1.9%
2025-12	-3.2%
2026-01	-2.0%
2026-02	-1.3%
2026-03	-5.9%
2026-04	+7.0%
2026-05	+15.0%
2026-06	-2.1%
2026-07	+1.6%

Which assets it traded

Avg allocation	Days held	% of time held	Asset
0.1881	3887	23.51	HYPE
0.1572	1761	10.65	BTC
0.1668	1683	10.18	BNB
0.1519	1662	10.05	LINK
0.1569	1569	9.49	SOL
0.1489	1488	9	kPEPE
0.1468	1410	8.53	DOGE
0.1468	1371	8.29	NEAR
0.1474	1350	8.16	WLD
0.1538	1347	8.15	SUI
0.1563	1333	8.06	XRP
0.1579	1308	7.91	ETH
0.1464	1210	7.32	kBONK
0.1776	964	5.83	VVV
0.1556	961	5.81	FARTCOIN
0.1763	682	4.12	ZEC
0.1484	566	3.42	PUMP
0.1657	377	2.28	XPL
0.1667	207	1.25	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 25.6% — 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.

Mean Reversion Strategy on Hyperliquid

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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