SMA-200 Trend + 15% Trailing Stop on AGG
iShares Core U.S. Aggregate Bond ETF — the broad US investment-grade bond market in one fund. Backtest 2021-01-04 → 2026-07-17, $10,000 starting capital, computed by the same engine that runs live DeployQuant strategies.
Year by year
| Year | trend + trailing stop | buy & hold |
|---|---|---|
| 2021 | −0.2% | −1.6% |
| 2022 | −13.8% | −12.7% |
| 2023 | 3.3% | 5.5% |
| 2024 | 1.3% | 1.3% |
| 2025 | 7.3% | 7.3% |
| 2026 | 0.0% | 0.0% |
The rules
Enter when price is above the 200-day average; exit only when a 15% trailing stop is hit.
- WHEN the market opens · IF not invested AND yesterday's close > SMA(200) · THEN buy with 98% of the sleeve
- WHILE invested · a managed trailing stop follows 15% below the position's high-water mark
A hybrid of the regime filter and the trailing stop: the 200-day average decides when to get in, but the exit belongs entirely to a 15% trail from the position's high-water mark. That asymmetry lets winners run far beyond the point where a crossover would have exited, at the cost of giving back 15% from every peak.
Good for: long trends with tolerable pullbacks; the 15% trail is wide enough to survive normal corrections.
Watch out: a 15% giveback from every peak is the tuition this strategy always pays; on choppy assets it re-enters above the 200-day repeatedly after each stop-out.
Build it from blocks (or type it in English), backtest it on 5.5 years of minute data in seconds, tweak any parameter, then paper trade it on live data. No card, no broker needed to start.
Frequently asked questions
Did trend + trailing stop beat buy-and-hold on AGG?
Over 2021-01-04–2026-07-17, trend + trailing stop on AGG returned −0.6% annualized vs −0.3% for buy-and-hold — it trailed buy-and-hold by 0.3% per year, with a maximum drawdown of 18.9% (buy-and-hold: 17.6%).
How many trades did it make?
1 completed round trips over 5.5 years (3 fills), with 0% of round trips closing profitably.
Why 15% rather than 10%?
Wider trails survive routine corrections in exchange for a bigger giveback at the end. Both numbers are one-field edits in DeployQuant — backtest both and compare.
Related
Backtests are hypothetical, computed by DeployQuant's engine on minute-resolution consolidated US market data (2021-01-04 to 2026-07-17, $10,000 starting capital, no margin, fees and slippage not modeled) and do not guarantee future results. Nothing on this page is investment advice. Live trading involves risk of loss.