LearnStrategies › 200-Day SMA Regime Filter

200-Day SMA Regime Filter

Own the asset when price closes above its 200-day average; hold cash when it closes below.

Across 59 ETFs (2021-01-04 → 2026-07-17): median CAGR 1.6%, median max drawdown 22.7%, and it beat buy-and-hold of the same ETF in 27 of 59 cases (46%). Same rules, same engine, every ETF.

The rules

  1. WHEN the market opens · IF not invested AND yesterday's close > SMA(200) · THEN buy with 98% of the sleeve
  2. WHEN the market opens · IF invested AND yesterday's close < SMA(200) · THEN sell the whole position

One rule, one number, and one of the most-studied timing signals in finance: price above the 200-day moving average has historically coincided with better returns and lower volatility than price below it. This template is the purest expression — no crossovers, no oscillators, just which side of the long-term average the price sits on.

Good for: a first systematic strategy — it's simple enough to fully understand and 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.

Run 200-day regime filter yourself — free →

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.

Results on every ETF

ETFCAGRbuy & holdmax DDSharpetradeswin rate
SOXL 31.6% 30.2% −63.6% 0.7519 37%
TQQQ 23.6% 22.3% −36.6% 0.7313 38%
QLD 19.6% 21.6% −28.8% 0.7912 42%
SOXX 17.4% 29.6% −39.2% 0.7319 26%
XLK 14.8% 20.2% −19.6% 0.8911 36%
ROM 13.8% 26.1% −42.2% 0.5618 33%
IAU 13.6% 13.6% −19.9% 0.9021 24%
SSO 12.1% 21.5% −31.2% 0.6817 35%
QQQM 12.0% 15.8% −19.9% 0.8810 20%
QQQ 11.9% 15.8% −20.0% 0.8710 20%
IOO 10.7% 16.4% −16.5% 0.9615 33%
VOOG 9.9% 14.9% −22.7% 0.8017 18%
SPUU 9.8% 22.0% −37.3% 0.5717 24%
VOO 8.0% 14.3% −17.9% 0.8115 40%
VOX 8.0% 9.2% −18.4% 0.6612 33%
SPY 7.9% 14.4% −17.9% 0.8015 40%
VV 7.4% 13.9% −19.9% 0.7513 31%
EEM 6.8% 5.6% −17.7% 0.5515 27%
TECL 5.6% 31.9% −64.5% 0.3620 20%
IWM 5.6% 8.5% −22.2% 0.4617 41%
QQQE 5.1% 9.4% −15.3% 0.4715 33%
VOOV 4.6% 13.2% −18.1% 0.5123 26%
VTV 4.4% 13.9% −23.4% 0.4821 29%
QAI 4.3% 3.9% −6.0% 0.967 29%
SGOV 3.2% 3.2% −0.1% 13.613 67%
TBF 3.1% 11.0% −23.8% 0.3028 39%
XLF 3.0% 14.1% −22.0% 0.3019 16%
USDU 2.6% 5.1% −11.2% 0.5217 29%
ALTY 2.4% 8.7% −12.1% 0.3916 13%
FXE 1.6% −0.7% −6.4% 0.3514 36%
IGIB 1.5% 0.9% −5.4% 0.3823 35%
UDN 1.4% −1.0% −5.4% 0.3217 53%
IEI 1.1% 0.0% −4.6% 0.3818 33%
AGG 0.6% −0.3% −6.1% 0.1723 39%
BND 0.5% −0.3% −6.5% 0.1419 37%
XLP −0.5% 7.0% −21.9% 0.0135 26%
FAS −0.5% 22.9% −54.9% 0.1530 27%
KMLM −0.7% 6.0% −28.6% -0.0221 14%
IEF −1.5% −1.6% −11.6% -0.3231 23%
XLY −1.7% 7.3% −27.3% -0.0525 24%
CTA −1.9% 7.2% −18.6% -0.0823 30%
PSQ −2.4% −13.2% −20.1% -0.0915 20%
RINF −2.6% 6.6% −21.4% -0.2037 32%
SOXS −2.9% −30.5% −55.6% 0.112 0%
SPDN −4.5% −9.7% −29.0% -0.3323 17%
SH −4.7% −9.9% −29.9% -0.3624 17%
EEV −5.8% −14.5% −59.4% -0.1322 14%
UST −6.3% −7.3% −34.4% -0.8334 29%
SDS −7.8% −22.1% −44.3% -0.2617 0%
TLT −7.9% −7.3% −40.4% -1.0648 15%
SQQQ −10.6% −30.9% −63.3% -0.0613 31%
QID −10.8% −28.9% −55.1% -0.2517 18%
TMF −10.9% −30.7% −53.3% -0.7117 0%
TECS −11.4% −21.8% −54.0% -0.1617 18%
VXZ −11.8% −13.9% −53.5% -0.6131 26%
VIXM −12.6% −14.9% −53.6% -0.6130 17%
REW −13.5% −33.6% −61.4% -0.2919 16%
UVXY −29.9% −38.0% −85.9% -0.9112 0%
CLSE −100.0% 20.1% −236327.8% -0.072 0%

Frequently asked questions

What is the 200-day regime filter strategy?

Own the asset when price closes above its 200-day average; hold cash when it closes below. One rule, one number, and one of the most-studied timing signals in finance: price above the 200-day moving average has historically coincided with better returns and lower volatility than price below it. This template is the purest expression — no crossovers, no oscillators, just which side of the long-term average the price sits on.

Does 200-day regime filter beat buy-and-hold?

Across 59 ETFs backtested 2021-01-04–2026-07-17, it beat same-ETF buy-and-hold on 27 of 59 (46%). Median CAGR was 1.6% with a median max drawdown of 22.7%. Per-ETF results vary widely — see the table.

Why the 200-day average specifically?

Convention and evidence: it approximates a year of trading days and has been studied across decades of data. It isn't optimal everywhere — the per-ETF backtests here show where it helped and where it didn't.

Compare with other strategies

200-day regime filter vs RSI mean reversionhead-to-head on 59 ETFs200-day regime filter vs RSI(2) snapbackhead-to-head on 59 ETFs200-day regime filter vs golden crosshead-to-head on 59 ETFs200-day regime filter vs SMA 10/50 trendhead-to-head on 59 ETFs200-day regime filter vs EMA 12/26 trendhead-to-head on 59 ETFs200-day regime filter vs weekly 7% targethead-to-head on 59 ETFs

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.