Ξ Whale Flow Strategy Backtest — Ethereum
90-day quantitative backtest of the Whale Flow signal for Ethereum (ETH). Performance metrics, trade statistics, and risk analysis. Last updated: March 14, 2026.
Performance Summary
2.02
Sharpe Ratio
-27%
Max Drawdown
47%
Win Rate
202
Total Trades
1.82
Profit Factor
0.12%
Avg Trade
Current Signal State </> API
# Current Whale Flow signal for ETH
$ curl command:
curl -H "X-API-Key: YOUR_KEY" https://algotick.dev/v1/signals/whale-flow?coin=ETH
Endpoint: /v1/signals/whale-flow?coin=ETH
# Current Whale Flow signal for ETH
$ curl command:
curl -H "X-API-Key: YOUR_KEY" https://algotick.dev/v1/signals/whale-flow?coin=ETH
Endpoint: /v1/signals/whale-flow?coin=ETH
Current Value
0.4694
Signal
buying
Indicator
Whale Flow
Trade Statistics
| Metric | Value |
|---|---|
| Best Trade | +2.2% |
| Worst Trade | -5.7% |
| Average Trade | +0.12% |
| Win Rate | 47% |
| Profit Factor | 1.82 |
| Total Trades (90d) | 202 |
| Average Holding Period | 3h |
| Max Consecutive Wins | 5 |
| Max Consecutive Losses | 4 |
Methodology
Whale Flow: Whale flow analysis tracks unusually large orders (>$100K notional) on the order book. When smart money accumulates on one side of the book, it often precedes directional moves. The indicator computes a whale imbalance score from -1 (all selling) to +1 (all buying).
Backtest Parameters:
- Period: 90 days of 1-minute data from Hyperliquid
- Signal: whale_imbalance 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 Whale Flow signal resp = requests.get( f"{BASE}/v1/signals/whale-flow", params={"coin": "ETH", "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": "whale_imbalance", "coin": "ETH", "hours": 2160 # 90 days } ) data = hist.json()
Our server-side Whale Flow signal generated a 2.0 Sharpe on ETH over the last 90 days
Don't build the infrastructure. Just query the API and focus on your alpha.
Get API Key →