◆ Liquidation Cascades Strategy Backtest — Hyperliquid
90-day quantitative backtest of the Liquidation Cascades signal for Hyperliquid (HYPE). Performance metrics, trade statistics, and risk analysis. Last updated: June 17, 2026.
Why Liquidation Cascades on Hyperliquid?
Hyperliquid is a native DEX-perp token whose price dynamics are tightly coupled with platform open interest and liquidity migration patterns. The Liquidation Cascades indicator exploits this by predict and trade cascading liquidation events. Over the 90-day test window, this combination produced a Sharpe ratio of 2.53 with 253 trades — averaging one trade every 8 hours.
The win rate of 60% combined with a 2.33× profit factor means winning trades are significantly larger than losing ones. The maximum drawdown of -28% 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 Liquidation Cascades signal for HYPE
$ curl command:
curl https://algotick.dev/v1/signals/liquidations?coin=HYPE
Endpoint: /v1/signals/liquidations?coin=HYPE
Trade Statistics
| Metric | Value |
|---|---|
| Best Trade | +7.3% |
| Worst Trade | -4.8% |
| Average Trade | +0.23% |
| Win Rate | 60% |
| Profit Factor | 2.33 |
| Total Trades (90d) | 253 |
| Average Holding Period | 6h |
| Max Consecutive Wins | 8 |
| Max Consecutive Losses | 5 |
Methodology
Liquidation Cascades: Liquidation cascade analysis identifies price levels where clusters of leveraged positions would be force-closed. When price approaches these levels, the resulting cascade of liquidations can create violent, predictable price moves. The strategy positions ahead of anticipated cascade zones.
Backtest Parameters:
- Period: 90 days of 1-minute data from Hyperliquid
- Signal: liquidation alerts 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 Liquidation Cascades signal resp = requests.get( f"{BASE}/v1/signals/liquidations", params={"coin": "HYPE"} ) signal = resp.json() print(signal) # Query historical data for backtesting hist = requests.get( f"{BASE}/v3/analytics/query", params={ "metric": "liquidation alerts", "coin": "HYPE", "hours": 2160 # 90 days } ) data = hist.json()
Our server-side Liquidation Cascades signal generated a 2.5 Sharpe on HYPE over the last 90 days
Don't build the infrastructure. Just query the API and focus on your alpha.
Explore API →