Run any S&P 500 name through a real, rule-based strategy and see how it would have behaved over the last decade — including the drawdowns. The point isn't to beat buy & hold; it's to see how the rules manage risk.
⬡ Backtests run through 2024-12-31 (recent data is held out so results can't be cherry-picked). Trading frictions and gap-stops are modeled.
Illustrative sample — not actual trading. Read it right: similar return, far smaller drawdown — the rules sat in cash through the worst of the crashes. That downside protection is the point, not a bigger number.
Same stock, same costs — AEGIS's full rule stack vs. the raw rules vs. the benchmarks. This is the part most tools never show you.
| Strategy | Return | Max DD | Sharpe | Calmar | Time in mkt |
|---|---|---|---|---|---|
| AEGIS Trend (full stack) | +118% | −14% | 0.71 | 0.39 | 41% |
| Naked Donchian breakout | +88% | −33% | 0.44 | 0.16 | 72% |
| Naked RSI mean-reversion | +52% | −29% | 0.38 | 0.14 | 55% |
| Buy & Hold (SPY) | +142% | −34% | 0.62 | 0.21 | 100% |
| 60 / 40 portfolio | +71% | −21% | 0.59 | 0.20 | 100% |
Illustrative sample. The full rule stack trades less, sits in cash more, and takes much smaller drawdowns per unit of return (higher Calmar) — that's the risk-management profile it's designed for.
Backtested results are hypothetical, illustrative samples and do not reflect actual trading. Past performance — real or simulated — does not guarantee future results. AEGIS Cloud is market-data & analytics software — not investment advice, not a trading-signal service, and not a broker-dealer or investment adviser. "Strategy" here means rule-based logic (Donchian/RSI/ATR), not a machine-learning model.