◆ Regime Momentum Strategy Backtest — Hyperliquid
90-day quantitative backtest of the Regime Momentum signal for Hyperliquid (HYPE). Performance metrics, trade statistics, and risk analysis. Last updated: March 12, 2026.
Performance Summary
1.78
Sharpe Ratio
-28%
Max Drawdown
49%
Win Rate
178
Total Trades
1.58
Profit Factor
0.28%
Avg Trade
Current Signal State </> API
# Current Regime Momentum signal for HYPE
$ curl command:
curl -H "X-API-Key: YOUR_KEY" https://algotick.dev/v3/signals/regime?coin=HYPE
Endpoint: /v3/signals/regime?coin=HYPE
# Current Regime Momentum signal for HYPE
$ curl command:
curl -H "X-API-Key: YOUR_KEY" https://algotick.dev/v3/signals/regime?coin=HYPE
Endpoint: /v3/signals/regime?coin=HYPE
Current Value
0.9060
Signal
Mean-Reverting
Indicator
Regime Momentum
Trade Statistics
| Metric | Value |
|---|---|
| Best Trade | +3.8% |
| Worst Trade | -3.3% |
| Average Trade | +0.28% |
| Win Rate | 49% |
| Profit Factor | 1.58 |
| Total Trades (90d) | 178 |
| Average Holding Period | 3h |
| Max Consecutive Wins | 5 |
| Max Consecutive Losses | 5 |
Methodology
Regime Momentum: Regime momentum uses the HMM-based regime classifier to detect transitions between market states (trending, mean-reverting, volatile). When the regime shifts from one state to another, the strategy enters positions aligned with the new regime's expected behavior.
Backtest Parameters:
- Period: 90 days of 1-minute data from Hyperliquid
- Signal: regime_label 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 API_KEY = "YOUR_API_KEY" BASE = "https://algotick.dev" # Get current Regime Momentum signal resp = requests.get( f"{BASE}/v3/signals/regime", params={"coin": "HYPE", "api_key": API_KEY} ) signal = resp.json() print(signal) # Query historical data for backtesting hist = requests.get( f"{BASE}/v3/analytics/query", params={ "api_key": API_KEY, "metric": "regime_label", "coin": "HYPE", "hours": 2160 # 90 days } ) data = hist.json()
Our server-side Regime Momentum signal generated a 1.8 Sharpe on HYPE over the last 90 days
Don't build the infrastructure. Just query the API and focus on your alpha.
Get API Key →