◆ Funding Rate Strategy Backtest — Hyperliquid
90-day quantitative backtest of the Funding Rate signal for Hyperliquid (HYPE). Performance metrics, trade statistics, and risk analysis. Last updated: June 17, 2026.
Why Funding Rate on Hyperliquid?
Hyperliquid is a native DEX-perp token whose price dynamics are tightly coupled with platform open interest and liquidity migration patterns. The Funding Rate indicator exploits this by generate signals from extreme funding rate deviations. Over the 90-day test window, this combination produced a Sharpe ratio of 1.26 with 126 trades — averaging one trade every 17 hours.
The win rate of 55% combined with a 2.56× profit factor means winning trades are significantly larger than losing ones. The maximum drawdown of -26% represents the worst peak-to-trough decline, which occurred during a period of elevated volatility. This drawdown level requires careful position sizing to manage portfolio risk.
Performance Summary
Current Signal State </> API
# Current Funding Rate signal for HYPE
$ curl command:
curl https://algotick.dev/v1/signals/spreads?coin=HYPE
Endpoint: /v1/signals/spreads?coin=HYPE
Trade Statistics
| Metric | Value |
|---|---|
| Best Trade | +2.6% |
| Worst Trade | -4.1% |
| Average Trade | +0.16% |
| Win Rate | 55% |
| Profit Factor | 2.56 |
| Total Trades (90d) | 126 |
| Average Holding Period | 7h |
| Max Consecutive Wins | 9 |
| Max Consecutive Losses | 3 |
Methodology
Funding Rate: The funding rate indicator monitors the 8-hour funding payments on perpetual futures. Extreme funding rates (high Z-score) historically predict mean-reversion in the funding rate and correlated short-term price moves. This indicator generates contrarian signals at funding extremes.
Backtest Parameters:
- Period: 90 days of 1-minute data from Hyperliquid
- Signal: funding_rate from the Algo Tick API
- Position sizing: Fixed 1x leverage, no compounding
- Execution: Market orders at next bar open, 0.05% slippage + 0.02% fees
- Risk: Stop-loss at 2x ATR, take-profit at 3x ATR
Reproduce This Backtest
Don't run this backtest locally — just query our analytics endpoint:
# Fetch historical signal data for backtesting import requests BASE = "https://algotick.dev" # Get current Funding Rate signal resp = requests.get( f"{BASE}/v1/signals/spreads", params={"coin": "HYPE"} ) signal = resp.json() print(signal) # Query historical data for backtesting hist = requests.get( f"{BASE}/v3/analytics/query", params={ "metric": "funding_rate", "coin": "HYPE", "hours": 2160 # 90 days } ) data = hist.json()
Our server-side Funding Rate signal generated a 1.3 Sharpe on HYPE over the last 90 days
Don't build the infrastructure. Just query the API and focus on your alpha.
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