DeployQuant200-Day SMA Regime Filter on XLF
Financial Select Sector SPDR Fund: S&P 500 banks, insurers and asset managers. Backtest 2021-01-04 to 2026-10-02, $10,000 starting capital, computed by the same engine that runs live DeployQuant strategies.
Year by year
| Year | 200-day regime filter | buy & hold |
|---|---|---|
| 2021 | −1.1% | 35.8% |
| 2022 | −9.6% | −10.4% |
| 2023 | 2.8% | 11.9% |
| 2024 | 29.9% | 29.9% |
| 2025 | −1.0% | 14.7% |
| 2026 | −4.9% | −1.1% |
Month by month
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021 | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 1.4% | −5.7% | 3.4% |
| 2022 | 0.0% | −1.6% | −1.7% | −1.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 1.5% | −7.0% |
| 2023 | 6.7% | −2.3% | −7.4% | 0.0% | 0.0% | −1.2% | 4.7% | −3.7% | −2.6% | −1.4% | 5.6% | 5.4% |
| 2024 | 2.9% | 4.0% | 4.8% | −4.0% | 3.1% | −0.9% | 6.3% | 4.4% | −0.5% | 2.6% | 10.2% | −5.4% |
| 2025 | 6.4% | 1.4% | −4.1% | −15.5% | 4.3% | 3.1% | 0.0% | 3.1% | 0.1% | −2.7% | 1.8% | 3.0% |
| 2026 | −2.4% | −3.9% | 0.0% | −0.1% | 0.0% | 1.3% | 6.1% | 1.3% | −7.0% | 0.2% | – | – |
Every trade
200-day regime filter on XLF made 19 closed round trips and one position still open at the end of the test, an average hold of 62 days, an average winner of 9.42%, an average loser of −1.55%, a profit factor of 1.49, a longest losing streak of 7. It held a position at the close on 61.3% of trading days.
| Entry | Entry price | Exit | Exit price | Return | Days held |
|---|---|---|---|---|---|
| 2021-10-19 | $36.42 | 2022-02-25 | $35.21 | −3.3% | 129 |
| 2022-02-28 | $35.30 | 2022-03-02 | $34.57 | −2.1% | 2 |
| 2022-03-17 | $35.12 | 2022-04-05 | $35.10 | −0.1% | 19 |
| 2022-11-11 | $33.46 | 2022-12-16 | $31.48 | −5.9% | 35 |
| 2022-12-22 | $31.88 | 2022-12-23 | $31.76 | −0.4% | 1 |
| 2022-12-27 | $32.02 | 2023-03-10 | $31.06 | −3.0% | 73 |
| 2023-06-16 | $31.90 | 2023-06-21 | $31.46 | −1.4% | 5 |
| 2023-06-30 | $31.98 | 2023-08-23 | $32.03 | 0.2% | 54 |
| 2023-08-24 | $32.31 | 2023-08-25 | $32.32 | 0.0% | 1 |
| 2023-08-28 | $32.42 | 2023-09-27 | $31.81 | −1.9% | 30 |
| 2023-10-18 | $32.05 | 2023-10-19 | $31.61 | −1.4% | 1 |
| 2023-11-06 | $32.37 | 2025-04-07 | $41.82 | 29.2% | 518 |
| 2025-04-10 | $45.53 | 2025-04-11 | $44.81 | −1.6% | 1 |
| 2025-04-15 | $46.41 | 2025-04-17 | $45.72 | −1.5% | 2 |
| 2025-04-23 | $47.04 | 2026-02-13 | $50.94 | 8.3% | 296 |
| 2026-02-19 | $51.55 | 2026-02-20 | $51.32 | −0.5% | 1 |
| 2026-04-20 | $52.14 | 2026-04-22 | $52.09 | −0.1% | 2 |
| 2026-06-08 | $51.87 | 2026-06-09 | $51.81 | −0.1% | 1 |
| 2026-06-10 | $51.98 | 2026-06-11 | $51.92 | −0.1% | 1 |
| 2026-06-12 | $52.58 | open | – | 1.7% | – |
Prices are adjusted for splits and dividends, so they sit below the quotes printed at the time. An open position is marked at the last close.
Largest drawdowns
| Peak | Low point | Depth | Days to low | Recovered | Days to recover |
|---|---|---|---|---|---|
| 2022-01-12 | 2023-11-09 | −22.0% | 666 | 2024-07-15 | 249 |
| 2025-02-18 | 2025-04-23 | −20.6% | 64 | not yet | – |
| 2021-10-22 | 2021-12-01 | −7.4% | 40 | 2022-01-04 | 34 |
Buy-and-hold's deepest drawdown ran from 2022-01-12 to 2022-10-12 and reached −25.5%.
With trading costs
The headline run fills at the bar price. These runs charge slippage on every fill.
| Slippage per fill | CAGR | Max drawdown | Final value | Sharpe |
|---|---|---|---|---|
| None (headline) | 2.1% | −22.0% | $11,243 | 0.23 |
| 5 basis points | 1.7% | −22.9% | $11,029 | 0.20 |
| 10 basis points | 1.4% | −23.7% | $10,815 | 0.17 |
Changing the parameters
| Version | CAGR | Max drawdown | Round trips | Win rate | Final value |
|---|---|---|---|---|---|
| Published rules | 2.1% | −22.0% | 19 | 21% | $11,243 |
| 100-day SMA | 2.0% | −18.4% | 35 | 34% | $11,204 |
| 150-day SMA | 4.6% | −21.8% | 23 | 30% | $12,945 |
| 250-day SMA | 0.4% | −26.9% | 21 | 14% | $10,248 |
How XLF behaved
| Measure | XLF |
|---|---|
| Data in this test | 2021-01-04 to 2026-10-02 (1444 sessions) |
| Total return, buy and hold | 102.9% |
| Annualized volatility | 18.4% |
| Deepest drawdown | −25.9% (2022-01-12 to 2022-10-12) |
| Up days | 52.9% |
| Average daily range | 1.40% |
| Average overnight gap | 0.49% |
| Correlation to SPY | 0.77 |
| Correlation to QQQ | 0.59 |
| Correlation to TLT | -0.05 |
| Sessions above the 200-day average | 71.2% |
| Crossings of the 200-day average | 38 |
| Falls of 10% or more from a 20-day high | 10 |
The rules
Own the asset when price closes above its 200-day average; hold cash when it closes below.
- WHEN the market opens · IF not invested AND yesterday's close > SMA(200) · THEN buy with 98% of the sleeve
- WHEN the market opens · IF invested AND yesterday's close < SMA(200) · THEN sell the whole position
One rule and one number. Price above the 200-day moving average has historically coincided with better returns and lower volatility than price below it. This template uses no crossovers and no oscillators, only which side of the long-term average the price is on.
Good for: a first systematic strategy, simple enough to audit every trade.
Watch out: price whips around the 200-day line during volatile bottoms, generating clusters of buy-sell pairs. Some traders add a small buffer band to reduce churn.
Build it from blocks (or type it in English), backtest it on 5.7 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 200-day regime filter beat buy-and-hold on XLF?
Over 2021-01-04 to 2026-10-02, 200-day regime filter on XLF returned 2.1% annualized vs 12.6% for buy-and-hold: it trailed buy-and-hold by 10.5% per year, with a maximum drawdown 3.4 points shallower than holding (22.0% vs 25.5%).
How many trades did it make?
19 completed round trips over 5.7 years (39 fills), with 21% of round trips closing profitably.
Why the 200-day average specifically?
It approximates a year of trading days and has been studied across decades of data. It is not the best window for every asset. The per-ETF backtests here show where it helped and where it didn't.
Related
Backtests are hypothetical, computed by DeployQuant's engine on minute-resolution consolidated US market data (2021-01-04 to 2026-10-02, $10,000 starting capital, no margin, no fees or slippage in the headline run; buy-and-hold puts 98% of the account in at the first open, as the templates do) and do not guarantee future results. Nothing on this page is investment advice. Live trading involves risk of loss.