Portfolio Stress Testing API for US Equities

Run historical shock scenarios, estimate ticker-level drawdown ranges and add tail-risk signals to Python or QuantConnect workflows.

12 preset stress scenarios · Batch forecasts · Custom scenarios · Portfolio backtesting · 50 free credits · No card required

What you can do

• · Stress-test a portfolio against historical market shocks
• · Estimate drawdown and recovery ranges by ticker
• · Compare current market paths with historical events
• · Integrate results into Python and QuantConnect

A real call

curl -X POST https://blackswan-api.9cstar.com/api/v1/portfolio/forecast \
  -H "Content-Type: application/json" \
  -H "X-API-Key: YOUR_KEY" \
  -d '{
    "tickers": ["SPY", "AAPL", "MSFT", "JPM"],
    "scenario_id": "financial_crisis_2008"
  }'

{
  "portfolio": {
    "portfolio_max_drawdown": -0.29,
    "portfolio_drawdown_lower": -0.35,
    "portfolio_drawdown_upper": -0.22,
    "most_vulnerable": [
      {
        "ticker": "JPM",
        "weight": 0.25,
        "predicted_drawdown": -0.35,
        "confidence_level": "high"
      }
    ],
    "most_resilient": [],
    "stability": 0.08
  },
  "results": {},
  "usage": {},
  "disclaimer": "Historical data does not guarantee future results"
}

Example US-equity workflows

Works with common US equities and ETFs — for example SPY · AAPL · MSFT · JPM · NVDA · XOM.

Transparent metering

1 compute credit = 1 ticker × 1 forecast

• · Free: 50 credits/month
• · Pro: 800 credits/month — one-strategy validation and operation
• · Scale: 3,000 credits/month — multi-strategy research