SMA 10/50 Trend on IEF
iShares 7-10 Year Treasury Bond ETF — intermediate Treasuries, the classic 60/40 diversifier. 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 | SMA 10/50 trend | buy & hold |
|---|---|---|
| 2021 | 2.8% | −3.3% |
| 2022 | −3.0% | −14.8% |
| 2023 | 5.4% | 3.5% |
| 2024 | −0.5% | −0.4% |
| 2025 | 5.5% | 8.0% |
| 2026 | −3.1% | −0.8% |
The rules
A faster moving-average crossover: hold while the 10-day average is above the 50-day.
- WHEN the market opens · IF not invested AND SMA(10) > SMA(50) · THEN buy with 98% of the sleeve
- WHEN the market opens · IF invested AND SMA(10) < SMA(50) · THEN sell the whole position
The golden cross's quicker sibling. Using 10- and 50-day averages catches intermediate trends measured in weeks rather than years — it enters recoveries earlier and exits breakdowns earlier, at the cost of more whipsaw trades in sideways markets. A good template for seeing how signal speed changes a strategy's character.
Good for: trending assets where multi-week swings are worth catching — leveraged index ETFs are a common pairing.
Watch out: several false signals a year is normal; each whipsaw costs a small loss and they add up in flat markets.
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 SMA 10/50 trend beat buy-and-hold on IEF?
Over 2021-01-04–2026-07-17, SMA 10/50 trend on IEF returned 1.2% annualized vs −1.6% for buy-and-hold — it beat buy-and-hold by 2.8% per year, with a maximum drawdown 16.1 points shallower than holding (5.7% vs 21.8%).
How many trades did it make?
14 completed round trips over 5.5 years (28 fills), with 43% of round trips closing profitably.
Why 10 and 50 days?
A common intermediate-trend pairing — fast enough to react within weeks, slow enough to ignore single bad days. Both windows are editable parameters in DeployQuant.
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.