Stress-test your QuantConnect strategy before the next market shock

Add scenario-driven tail-risk analytics to a US-equity strategy. Estimate drawdown ranges, recovery horizons and historical market-path matches—without turning your model into a short-term prediction system.

50 free compute credits · No card required · 1 compute credit = 1 ticker × 1 forecast

QuantConnect integration

tickers = ["SPY", "AAPL", "MSFT", "JPM"]
response = self.Download(
    "https://blackswan-api.9cstar.com/api/v1/forecast"
    "?tickers=SPY,AAPL,MSFT,JPM"
    "&scenario_id=financial_crisis_2008",
    {"X-API-Key": self.api_key}
)

How it works

1. 1. Send portfolio tickers and a stress scenario
2. 2. Receive drawdown ranges, recovery estimates and persistence signals
3. 3. Use the signals in defensive allocation and backtesting rules

What it costs to validate a strategy

A 3-year monthly validation of a 4-ticker US-equity strategy:

36 monthly forecasts × 4 US-equity tickers
= 144 compute credits

Free tier includes 50 credits/mo; Pro (800 credits/mo) covers validation, iteration and day-to-day operation of one strategy.

Historical results across windows

Backtested across historical stress windows. Historical backtests are not live performance.

• · GFC 2007-2009: defensive tilt reduced drawdown vs buy-and-hold
• · Dotcom 2000-2002: limited the loss to -0.8% while SPY fell 36.9% in this backtest window
• · 2022 weak spot: -11.7% versus SPY +1.1% in this backtest window
• · Bull market sacrifice: long bull windows trail SPY (defensive cost)