Trading strategies, tested on Orbital

Twice-daily trend long with volatility exits, AI growth 21

At 10:00 and 15:50 ET each session, buy any of 21 AI growth stocks that is above its 20-day average (at 10:00, only if the previous session's close was above it too) and sell any held one that has fallen below it; each buy also gets a target and a stop scaled to the stock's recent volatility, and a time limit of 10 to 40 sessions.

• Trend following
• Momentum
• Single stocks
• AI growth 21

Return

+645.7%

CAGR

+99.05%

Sharpe

1.91

Max DD

−37.6%

Win rate

31.7%

Profit factor

1.80

Hypothetical backtest, costs modeled

Morning trend long/short, broad AI 24

At 09:35 ET, buy any of 24 AI-related stocks trending up over about a month, or short one breaking down on heavy volume, with half the account each, and hold until the trend fails or a stop is hit; shorts also have a target and a three-session limit.

• Trend following
• Momentum
• Long/short
• Single stocks
• Broad AI 24

Return

+275.6%

CAGR

+94.06%

Sharpe

1.67

Max DD

−32.7%

Win rate

32.9%

Profit factor

2.15

Hypothetical backtest, costs modeled

Trend-filtered momentum with failed-bounce shorts, AI growth 21

Hold up to five of 21 AI growth stocks, buying at the next open after a close above the stock's 63-day average and above its close 126 sessions (about six months) earlier, biggest 126-session gainers first, and selling at the next open after a close at or below that average or below that earlier close.

• Momentum
• Trend following
• Single stocks
• AI growth 21

Return

+616.7%

CAGR

+92.77%

Sharpe

1.62

Max DD

−28.9%

Win rate

37.9%

Profit factor

3.13

Hypothetical backtest, costs modeled

Regime-gated overnight long, AI infra 8

At 15:46 ET, buy any of eight AI-infrastructure stocks above today's open but down over the prior five sessions, and sell at 09:35 the next session.

• Overnight
• Mean reversion
• Regime filter
• AI infra 8

Return

+259.8%

CAGR

+57.54%

Sharpe

2.45

Max DD

−13.8%

Win rate

59.0%

Profit factor

1.80

Hypothetical backtest, costs modeled

Forward testing since October 29, 2026, with no live market gate: version 6's date ranges end in April 2026. Backtest numbers are from version 6, one of seven versions tried, in the strategy's 11th run.

20-day trend long with nearest-neighbor exit, AI growth 21

Buy any of 21 AI growth stocks when it closes above its 20-day average, and sell when it closes below that average or when, of the eight past days most like today, at most one rose over the following four sessions.

• Trend following
• Machine learning
• Single stocks
• AI growth 21

Return

+229.9%

CAGR

+54.39%

Sharpe

1.37

Max DD

−31.5%

Win rate

38.3%

Profit factor

1.68

Hypothetical backtest, costs modeled

AI leaders, monthly top three

At the close of each month's first trading day, sell every holding at the next open.

• Momentum
• Themed basket
• AI 12 (AIQ)

Return

+3791.7%

CAGR

+44.54%

Sharpe

1.14

Max DD

−38.0%

Win rate

61.3%

Profit factor

1.88

Hypothetical backtest, costs modeled

AI leaders above the 200-day, checked hourly

Hold each stock while its latest hourly close is above its 200-day simple moving average of daily closes, checked at every hourly close: buy at the next minute's open when it is above and sell when it falls below.

• Trend following
• Themed basket
• AI 12 (AIQ)

Return

+189.6%

CAGR

+42.52%

Sharpe

1.47

Max DD

−24.9%

Win rate

22.6%

Profit factor

4.95

Hypothetical backtest, costs modeled

200-day trend switch, TQQQ

Hold TQQQ while its daily close is above its own 200-day simple moving average, and hold cash while it is below.

• Trend following
• Leveraged ETF
• TQQQ (3x Nasdaq-100)

Return

+3040.8%

CAGR

+42.46%

Sharpe

0.91

Max DD

−47.4%

Win rate

52.2%

Profit factor

5.85

Hypothetical backtest, costs modeled

2016 chip leaders, monthly top three

At the close of each month's first trading day, sell every holding at the next open.

• Momentum
• Themed basket
• 2016 chips 10

Return

+2531.6%

CAGR

+38.96%

Sharpe

0.96

Max DD

−40.0%

Win rate

59.9%

Profit factor

2.34

Hypothetical backtest, costs modeled

Cybersecurity leaders, monthly top three

At the close of each month's first trading day, sell every holding at the next open.

• Momentum
• Themed basket
• Cyber 10 (CIBR)

Return

+2071.2%

CAGR

+36.30%

Sharpe

0.95

Max DD

−51.6%

Win rate

61.8%

Profit factor

1.85

Hypothetical backtest, costs modeled

Momentum-ranked ten-day trend hold, big tech 7

At each day's close it checks each of seven big tech stocks it does not hold, buys at the next open each one that closed above its 20-day average without unusually wide daily swings, and sells it at the open ten trading sessions later.

• Trend following
• Momentum
• Single stocks
• Big tech 7

Return

+601.6%

CAGR

+33.91%

Sharpe

1.10

Max DD

−38.4%

Win rate

55.8%

Profit factor

1.61

Hypothetical backtest, costs modeled

TQQQ and UPRO above the 200-day, checked hourly

Hold the fund while its latest hourly close is above its 200-day simple moving average of daily closes, checked at every hourly close: buy at the next minute's open when it is above and sell when it falls below.

• Trend following
• Leveraged ETF
• TQQQ · UPRO (3x)

Return

+139.8%

CAGR

+33.85%

Sharpe

0.82

Max DD

−34.8%

Win rate

26.5%

Profit factor

3.27

Hypothetical backtest, costs modeled

Software leaders, monthly top three

At the close of each month's first trading day, sell every holding at the next open.

• Momentum
• Themed basket
• Software 12 (IGV)

Return

+1602.0%

CAGR

+33.00%

Sharpe

0.88

Max DD

−42.1%

Win rate

60.7%

Profit factor

1.78

Hypothetical backtest, costs modeled

AI leaders above the 200-day

Hold each of the twelve stocks while its daily close is above its 200-day simple moving average.

• Trend following
• Themed basket
• AI 12 (AIQ)

Return

+1226.7%

CAGR

+29.71%

Sharpe

1.11

Max DD

−27.1%

Win rate

29.6%

Profit factor

4.85

Hypothetical backtest, costs modeled

2016 chip leaders above the 200-day

Hold each of the ten stocks while its daily close is above its 200-day simple moving average.

• Trend following
• Themed basket
• 2016 chips 10

Return

+1134.8%

CAGR

+28.78%

Sharpe

0.90

Max DD

−30.8%

Win rate

27.1%

Profit factor

3.58

Hypothetical backtest, costs modeled

AI leaders, new-high trend

Buy at the next minute's open after an hourly close reaches the stock's record, its highest session close on file, and sell at the next open after an hourly close falls below a trailing stop.

• Trend following
• Breakout
• Themed basket
• AI 12 (AIQ)

Return

+92.6%

CAGR

+24.42%

Sharpe

1.00

Max DD

−24.1%

Win rate

68.2%

Profit factor

5.66

Hypothetical backtest, costs modeled

Software leaders above the 200-day

Hold each of the twelve stocks while its daily close is above its 200-day simple moving average.

• Trend following
• Themed basket
• Software 12 (IGV)

Return

+776.0%

CAGR

+24.40%

Sharpe

0.88

Max DD

−42.8%

Win rate

27.8%

Profit factor

3.18

Hypothetical backtest, costs modeled

QQQ above the 200-day, checked hourly

Hold the fund while its latest hourly close is above its 200-day simple moving average of daily closes, checked at every hourly close: buy at the next minute's open when it is above and sell when it falls below.

• Trend following
• QQQ

Return

+79.3%

CAGR

+21.48%

Sharpe

0.99

Max DD

−15.3%

Win rate

28.6%

Profit factor

10.19

Hypothetical backtest, costs modeled

AI leaders, Keltner-Donchian trend

Buy at the next minute's open after an hourly close reaches the upper band: the lower of the highest of the last 20 session closes and their 20-session average plus 2.8 times their mean daily change.

• Trend following
• Breakout
• Themed basket
• AI 12 (AIQ)

Return

+77.3%

CAGR

+21.03%

Sharpe

0.98

Max DD

−15.5%

Win rate

40.1%

Profit factor

1.98

Hypothetical backtest, costs modeled

Cybersecurity leaders above the 200-day

Hold each of the ten stocks while its daily close is above its 200-day simple moving average.

• Trend following
• Themed basket
• Cyber 10 (CIBR)

Return

+466.8%

CAGR

+19.07%

Sharpe

0.74

Max DD

−28.1%

Win rate

28.2%

Profit factor

2.34

Hypothetical backtest, costs modeled

One-Week Reversal in Large Stocks

Buys up to 20 of the past week's biggest losers among heavily traded US stocks and sells each within five trading days.

• Mean reversion
• Single stocks
• 20 weekly losers

Return

+422.2%

CAGR

+18.65%

Sharpe

0.54

Max DD

−61.5%

Win rate

54.9%

Profit factor

1.16

Hypothetical backtest, costs modeled

AI leaders, 20-day close hold

Once a session, at 15:58 (12:58 on a half day), buy a stock whose price is above its 20-day average, that price and the previous 19 official closes, and sell one that has fallen below it; orders fill at 15:59 or the closing print.

• Trend following
• Overnight
• Themed basket
• AI 12 (AIQ)

Return

+63.1%

CAGR

+17.71%

Sharpe

0.92

Max DD

−16.6%

Win rate

30.3%

Profit factor

1.60

Hypothetical backtest, costs modeled

Nasdaq-100 (Oct 2023) above the 200-day, checked hourly

Hold each stock while its latest hourly close is above its 200-day simple moving average of daily closes, checked at every hourly close: buy at the next minute's open when it is above and sell when it falls below.

• Trend following
• Single stocks
• Nasdaq-100 2023 (93)

Return

+49.6%

CAGR

+14.36%

Sharpe

0.73

Max DD

−12.6%

Win rate

13.3%

Profit factor

1.27

Hypothetical backtest, costs modeled

AI leaders, RSI(2) pullbacks

Buy a stock at the next open when its two-day RSI (Wilder's) closes below 10 while its close is above its 200-day simple moving average; sell at the next open after a close above its 5-day average.

• Mean reversion
• Themed basket
• AI 12 (AIQ)

Return

+226.2%

CAGR

+12.63%

Sharpe

0.64

Max DD

−23.6%

Win rate

67.6%

Profit factor

1.99

Hypothetical backtest, costs modeled

52-Week-High Momentum

Buys the liquid US stocks closest to their 52-week high, two a day up to 30, and holds each for six months.

• Momentum
• Single stocks
• 30 stocks near highs

Return

+209.1%

CAGR

+12.39%

Sharpe

0.43

Max DD

−35.8%

Win rate

62.2%

Profit factor

1.74

Hypothetical backtest, costs modeled

AI leaders, Turtle System 2

Buy at the next minute's open after an hourly close tops the highest high of the last 55 completed sessions, with a stop 2N below the decision close, where N is the 20-session Wilder average of the day's true range.

• Trend following
• Breakout
• Themed basket
• AI 12 (AIQ)

Return

+38.0%

CAGR

+11.32%

Sharpe

0.63

Max DD

−10.2%

Win rate

43.8%

Profit factor

2.16

Hypothetical backtest, costs modeled

Nasdaq-100 (Oct 2023), Keltner-Donchian trend

Buy at the next minute's open after an hourly close reaches the upper band: the lower of the highest of the last 20 session closes and their 20-session average plus 2.8 times their mean daily change.

• Trend following
• Breakout
• Single stocks
• Nasdaq-100 2023 (93)

Return

+34.3%

CAGR

+10.32%

Sharpe

0.58

Max DD

−10.6%

Win rate

33.9%

Profit factor

1.39

Hypothetical backtest, costs modeled

Monthly Rotation Orders

On the first trading day of each month, rank the eight ETFs by 126-day return and hold the top three in equal dollar amounts, selling any that drop out.

• Momentum
• 8 multi-asset ETFs

Return

+139.7%

CAGR

+9.14%

Sharpe

0.44

Max DD

−18.8%

Win rate

59.1%

Profit factor

1.63

Hypothetical backtest, costs modeled

Originally published (2007-2025): +380.5% return, Sharpe 0.53, max DD −28.2%

Weekly RSI Reversion

Enter a sector ETF when RSI(14) is below 35; stay in until RSI(14) is above 60.

• Mean reversion
• 9 sector ETFs

Return

+134.8%

CAGR

+8.91%

Sharpe

0.38

Max DD

−33.6%

Win rate

79.3%

Profit factor

4.85

Hypothetical backtest, costs modeled

Originally published (2000-2025): +372.5% return, Sharpe 0.34, max DD −49.2%

2016 chip leaders, RSI(2) pullbacks

Buy a stock at the next open when its two-day RSI (Wilder's) closes below 10 while its close is above its 200-day simple moving average; sell at the next open after a close above its 5-day average.

• Mean reversion
• Themed basket
• 2016 chips 10

Return

+129.3%

CAGR

+8.71%

Sharpe

0.38

Max DD

−21.9%

Win rate

66.8%

Profit factor

1.59

Hypothetical backtest, costs modeled

Low-Volatility Stocks

Buys the 30 liquid US stocks with the smallest past-month daily price ranges of at least 0.8%, and holds each a month.

• Low volatility
• Single stocks
• 30 calm stocks

Return

+107.6%

CAGR

+7.85%

Sharpe

0.36

Max DD

−31.2%

Win rate

58.9%

Profit factor

1.23

Hypothetical backtest, costs modeled

MACD Trend

Hold each sector ETF while its MACD (12, 26) is above its 9-day signal line.

• Trend following
• 9 sector ETFs

Return

+111.6%

CAGR

+7.83%

Sharpe

0.42

Max DD

−11.3%

Win rate

43.7%

Profit factor

1.56

Hypothetical backtest, costs modeled

Originally published (2000-2025): +186.3% return, Sharpe 0.22, max DD −35.6%

Bollinger Reversion

Buy a sector ETF when it closes below its lower Bollinger Band (20-day SMA minus 2 standard deviations); sell when it closes back above the 20-day SMA.

• Mean reversion
• 9 sector ETFs

Return

+109.9%

CAGR

+7.70%

Sharpe

0.29

Max DD

−39.9%

Win rate

74.5%

Profit factor

2.11

Hypothetical backtest, costs modeled

Originally published (2000-2025): +486.5% return, Sharpe 0.42, max DD −35.2%

Nasdaq-100 (Oct 2023), new-high trend

Buy at the next minute's open after an hourly close reaches the stock's record, its highest session close on file, and sell at the next open after an hourly close falls below a trailing stop.

• Trend following
• Breakout
• Single stocks
• Nasdaq-100 2023 (93)

Return

+24.9%

CAGR

+7.70%

Sharpe

0.37

Max DD

−9.2%

Win rate

48.3%

Profit factor

1.51

Hypothetical backtest, costs modeled

Software leaders, RSI(2) pullbacks

Buy a stock at the next open when its two-day RSI (Wilder's) closes below 10 while its close is above its 200-day simple moving average; sell at the next open after a close above its 5-day average.

• Mean reversion
• Themed basket
• Software 12 (IGV)

Return

+104.6%

CAGR

+7.47%

Sharpe

0.30

Max DD

−15.8%

Win rate

65.6%

Profit factor

1.60

Hypothetical backtest, costs modeled

Halloween Effect

Holds SPY from November through April and a T-bill ETF (BIL) from May through October.

• Calendar
• SPY · BIL

Return

+103.7%

CAGR

+7.38%

Sharpe

0.28

Max DD

−32.6%

Win rate

73.7%

Profit factor

3.79

Hypothetical backtest, costs modeled

Cybersecurity leaders, RSI(2) pullbacks

Buy a stock at the next open when its two-day RSI (Wilder's) closes below 10 while its close is above its 200-day simple moving average; sell at the next open after a close above its 5-day average.

• Mean reversion
• Themed basket
• Cyber 10 (CIBR)

Return

+93.5%

CAGR

+6.87%

Sharpe

0.25

Max DD

−23.4%

Win rate

65.3%

Profit factor

1.58

Hypothetical backtest, costs modeled

Daily SMA Trend

Hold each sector ETF while its 50-day SMA is above its 200-day SMA.

• Trend following
• 9 sector ETFs

Return

+89.0%

CAGR

+6.62%

Sharpe

0.24

Max DD

−28.6%

Win rate

54.4%

Profit factor

2.36

Hypothetical backtest, costs modeled

Originally published (2000-2025): +537.0% return, Sharpe 0.45, max DD −34.7%

Nasdaq-100 (Oct 2023), 20-day close hold

Once a session, at 15:58 (12:58 on a half day), buy a stock whose price is above its 20-day average, that price and the previous 19 official closes, and sell one that has fallen below it; orders fill at 15:59 or the closing print.

• Trend following
• Overnight
• Single stocks
• Nasdaq-100 2023 (93)

Return

+20.0%

CAGR

+6.25%

Sharpe

0.25

Max DD

−11.5%

Win rate

25.7%

Profit factor

1.21

Hypothetical backtest, costs modeled

Monthly Drift ETF

Hold each ETF while its 50-day SMA is above its 200-day SMA; rebalance at month-end or when a weight drifts 5% from target.

• Trend following
• 8 multi-asset ETFs

Return

+66.1%

CAGR

+5.24%

Sharpe

0.15

Max DD

−16.9%

Win rate

44.8%

Profit factor

2.02

Hypothetical backtest, costs modeled

Originally published (2007-2025): +137.7% return, Sharpe 0.31, max DD −19.4%

Turn of the Month

Holds SPY over each month's last four and first three trading days, and cash otherwise.

• Calendar
• SPY

Return

+57.3%

CAGR

+4.64%

Sharpe

0.08

Max DD

−16.3%

Win rate

63.0%

Profit factor

1.78

Hypothetical backtest, costs modeled

Market SMA Cross

Buy when the 20-day SMA crosses above the 50-day SMA. Sell when it crosses back below.

• Trend following
• SPY · QQQ · IWM

Return

+54.5%

CAGR

+4.45%

Sharpe

0.05

Max DD

−15.7%

Win rate

55.7%

Profit factor

2.65

Hypothetical backtest, costs modeled

Originally published (2001-2025): +126.7% return, Sharpe 0.21, max DD −16.4%

Signal Change Rotation Orders

Buy on a flat-to-long SMA(20/50) flip and sell on a long-to-flat flip; do nothing in between. Functionally the same rule as O01.

• Trend following
• SPY · QQQ · IWM

Return

+54.5%

CAGR

+4.45%

Sharpe

0.05

Max DD

−15.7%

Win rate

55.7%

Profit factor

2.65

Hypothetical backtest, costs modeled

Originally published (2001-2025): +129.8% return, Sharpe 0.22, max DD −16.3%

Quarterly Dual Momentum

At each quarter-end, rank the ETFs by 12-month return and hold the top two, but only those with a positive return.

• Momentum
• 8 multi-asset ETFs

Return

+52.4%

CAGR

+4.45%

Sharpe

0.09

Max DD

−42.5%

Win rate

64.9%

Profit factor

1.46

Hypothetical backtest, costs modeled

Originally published (2007-2025): +64.6% return, Sharpe 0.12, max DD −42.8%

Limit RSI Dip

When RSI(14) is below 40, place a buy limit 1.5% below the close (good for 3 bars).

• Mean reversion
• SPY · QQQ · IWM

Return

+35.0%

CAGR

+3.05%

Sharpe

−0.17

Max DD

−12.0%

Win rate

100.0%

Profit factor

∞

Hypothetical backtest, costs modeled

Originally published (2001-2025): +94.7% return, Sharpe 0.14, max DD −19.1%

Intraday SMA Trend 1h

On hourly bars, hold each ETF while its 10-bar SMA is above its 30-bar SMA.

• Trend following
• Intraday
• SPY · QQQ · IWM

Return

+8.4%

CAGR

+2.71%

Sharpe

−0.15

Max DD

−12.6%

Win rate

37.9%

Profit factor

1.23

Hypothetical backtest, costs modeled

Originally published (9 weeks): +1.5% return, Sharpe —, max DD −3.5%

Limit Trend Pullback

When the close is above the 50-day SMA, place a buy limit 1% below the close (good for 2 bars).

• Trend following
• SPY · QQQ · IWM

Return

+26.9%

CAGR

+2.41%

Sharpe

−0.53

Max DD

−5.7%

Win rate

49.6%

Profit factor

1.50

Hypothetical backtest, costs modeled

Originally published (2001-2025): +56.8% return, Sharpe −0.04, max DD −6.8%

Nasdaq-100 (Oct 2023), Turtle System 2

Buy at the next minute's open after an hourly close tops the highest high of the last 55 completed sessions, with a stop 2N below the decision close, where N is the 20-session Wilder average of the day's true range.

• Trend following
• Breakout
• Single stocks
• Nasdaq-100 2023 (93)

Return

+7.0%

CAGR

+2.28%

Sharpe

−0.30

Max DD

−6.3%

Win rate

31.0%

Profit factor

1.22

Hypothetical backtest, costs modeled

Intraday RSI 15m

On 15-minute bars, enter when RSI(14) is below 35 and stay in until RSI(14) is above 55.

• Mean reversion
• Intraday
• SPY · QQQ · IWM

Return

+6.9%

CAGR

+2.24%

Sharpe

−0.26

Max DD

−15.5%

Win rate

63.1%

Profit factor

1.50

Hypothetical backtest, costs modeled

Originally published (3 weeks): +2.6% return, Sharpe —, max DD −1.1%

Stop Breakout Entry

Place a buy-stop 0.2% above the highest close of the prior 20 days (good for 5 bars). Exit at market after 10 bars.

• Breakout
• SPY · QQQ · IWM

Return

+24.1%

CAGR

+2.18%

Sharpe

−0.83

Max DD

−3.0%

Win rate

63.9%

Profit factor

2.00

Hypothetical backtest, costs modeled

Originally published (2001-2025): +41.4% return, Sharpe −0.19, max DD −10.5%

Stop Limit Breakout

Buy-stop 0.2% above the prior 20-day high close, with a limit 0.4% above the stop so it never chases (good for 5 bars). Exit at market after 12 bars.

• Breakout
• SPY · QQQ · IWM

Return

+23.4%

CAGR

+2.12%

Sharpe

−0.77

Max DD

−3.2%

Win rate

67.9%

Profit factor

1.91

Hypothetical backtest, costs modeled

Originally published (2001-2025): +56.2% return, Sharpe −0.05, max DD −6.4%

OCO Dip Or Breakout

Every fifth bar while flat, place two competing buys: a limit 2% below the close and a stop 2% above it (good for 5 bars); whichever fills cancels the other.

• Breakout
• Mean reversion
• SPY · QQQ · IWM

Return

+21.6%

CAGR

+1.97%

Sharpe

−0.58

Max DD

−6.9%

Win rate

62.5%

Profit factor

1.49

Hypothetical backtest, costs modeled

Originally published (2001-2025): +45.5% return, Sharpe −0.08, max DD −13.2%

Trailing Stop Trend

Buy on the SMA(20/50) cross up; a 4% trailing stop manages the exit; also sell on the cross down.

• Trend following
• SPY · QQQ · IWM

Return

+20.0%

CAGR

+1.84%

Sharpe

−0.92

Max DD

−6.6%

Win rate

56.9%

Profit factor

2.50

Hypothetical backtest, costs modeled

Originally published (2001-2025): +30.0% return, Sharpe −0.33, max DD −7.0%

Trailing Stop Limit

Buy on the SMA(20/50) cross up; a trailing stop 4% of price below the high converts to a limit 0.5% lower; sell on the cross down.

• Trend following
• SPY · QQQ · IWM

Return

+20.0%

CAGR

+1.84%

Sharpe

−0.92

Max DD

−6.6%

Win rate

56.9%

Profit factor

2.50

Hypothetical backtest, costs modeled

Originally published (2001-2025): +28.1% return, Sharpe −0.38, max DD −6.2%

Protective Stop Loss

Buy on the SMA(20/50) cross up, attach a stop 5% below entry, and sell on the cross down.

• Trend following
• SPY · QQQ · IWM

Return

+19.0%

CAGR

+1.76%

Sharpe

−0.49

Max DD

−16.0%

Win rate

47.1%

Profit factor

1.59

Hypothetical backtest, costs modeled

Originally published (2001-2025): +60.1% return, Sharpe 0.00, max DD −16.2%

Market RSI Reversion

Buy when RSI(14) is below 35. Sell when RSI(14) rises above 60.

• Mean reversion
• SPY · QQQ · IWM

Return

+17.4%

CAGR

+1.62%

Sharpe

−0.51

Max DD

−10.9%

Win rate

69.6%

Profit factor

2.70

Hypothetical backtest, costs modeled

Originally published (2001-2025): +29.1% return, Sharpe −0.17, max DD −16.0%

Bracket Trend

Buy on the SMA(20/50) cross up with a +6% take-profit and a -3% stop; sell on the cross down.

• Trend following
• SPY · QQQ · IWM

Return

+15.9%

CAGR

+1.48%

Sharpe

−1.17

Max DD

−6.8%

Win rate

50.0%

Profit factor

1.88

Hypothetical backtest, costs modeled

Originally published (2001-2025): +29.4% return, Sharpe −0.38, max DD −6.8%

Stop Limit Protection

Buy on the SMA(20/50) cross up; protect with a stop-limit sell (stop 4% below entry, limit 4.5% below). Sell on the cross down.

• Trend following
• SPY · QQQ · IWM

Return

+15.3%

CAGR

+1.44%

Sharpe

−0.62

Max DD

−14.3%

Win rate

42.3%

Profit factor

1.48

Hypothetical backtest, costs modeled

Originally published (2001-2025): +63.6% return, Sharpe 0.02, max DD −14.2%

Trailing Stop RSI

Buy when RSI(14) is below 38; a 5% trailing stop manages risk; sell at market when RSI(14) rises above 65.

• Mean reversion
• SPY · QQQ · IWM

Return

+15.2%

CAGR

+1.43%

Sharpe

−0.52

Max DD

−10.6%

Win rate

42.1%

Profit factor

1.29

Hypothetical backtest, costs modeled

Originally published (2001-2025): −12.2% return, Sharpe −0.41, max DD −39.0%

Bracket RSI Reversion

Buy when RSI(14) is below 35 with a +4% take-profit and a -2% stop; sell at market if RSI(14) rises above 70.

• Mean reversion
• SPY · QQQ · IWM

Return

+7.5%

CAGR

+0.73%

Sharpe

−1.11

Max DD

−8.3%

Win rate

38.0%

Profit factor

1.23

Hypothetical backtest, costs modeled

Originally published (2001-2025): +8.5% return, Sharpe −0.43, max DD −11.6%

High-Volume Return Premium

Buys the 30 stocks with the biggest volume spikes, at least twice usual, and no big price move, for 20 trading days.

• Volume
• Single stocks
• 30 volume spikes

Return

+1.4%

CAGR

+0.14%

Sharpe

−0.06

Max DD

−47.1%

Win rate

52.0%

Profit factor

0.99

Hypothetical backtest, costs modeled

Pre-FOMC Drift

Holds SPY from 14:00 the day before each scheduled Fed announcement until 13:45 on the day.

• Calendar
• SPY

Return

−0.9%

CAGR

−0.29%

Sharpe

−2.94

Max DD

−3.9%

Win rate

52.0%

Profit factor

1.34

Hypothetical backtest, costs modeled

Big-Move Late-Day Momentum

Buys SPY at 14:45 when it is 2% or more above its prior close, sells it short when 2% or more below, and exits at the close.

• Momentum
• Intraday
• SPY

Return

−0.9%

CAGR

−0.30%

Sharpe

−2.76

Max DD

−3.6%

Win rate

47.8%

Profit factor

1.33

Hypothetical backtest, costs modeled

Buy on Gap

Buys Nasdaq-100 stocks opening well below the prior day's low while above their 20-day average, and sells just before the close.

• Mean reversion
• Single stocks
• Intraday
• Nasdaq 100

Return

−1.0%

CAGR

−0.33%

Sharpe

−1.96

Max DD

−4.5%

Win rate

50.9%

Profit factor

1.00

Hypothetical backtest, costs modeled

Extreme-Drop Rebound

Buys Nasdaq-100 stocks after an extreme drop within an hour, and sells an hour later.

• Mean reversion
• Single stocks
• Intraday
• Nasdaq 100

Return

−7.7%

CAGR

−2.63%

Sharpe

−2.82

Max DD

−9.0%

Win rate

43.9%

Profit factor

0.81

Hypothetical backtest, costs modeled

Intraday Stop Breakout 30m

On 30-minute bars, buy-stop 0.1% above the prior 12-bar high (good for 3 bars). Exit at market after 8 bars.

• Breakout
• Intraday
• SPY · QQQ · IWM

Return

−10.3%

CAGR

−3.57%

Sharpe

−1.82

Max DD

−15.2%

Win rate

47.4%

Profit factor

1.14

Hypothetical backtest, costs modeled

Originally published (8 weeks): −13.9% return, Sharpe —, max DD −14.8%

Nasdaq-100 (Oct 2023), overnight-gap reversal

At each session's first minute, test whether the overnight gap from the previous official close is a jump: the gap joins the previous session's one-minute returns, and Barndorff-Nielsen and Shephard's ratio test of realized against bipower variation, scaled by the tripower quarticity, must exceed 3.09, with the gap also the largest move in the sample.

• Intraday
• Mean reversion
• Single stocks
• Nasdaq-100 2023 (93)

Return

−17.5%

CAGR

−6.20%

Sharpe

−2.65

Max DD

−17.8%

Win rate

48.1%

Profit factor

1.04

Hypothetical backtest, costs modeled

Intraday Bracket Reversion 5m

On 5-minute bars, buy when RSI(14) is below 30 with a +0.6% take-profit and a -0.4% stop.

• Mean reversion
• Intraday
• SPY · QQQ · IWM

Return

−21.9%

CAGR

−7.90%

Sharpe

−2.40

Max DD

−24.3%

Win rate

37.8%

Profit factor

1.12

Hypothetical backtest, costs modeled

Originally published (4 weeks): +1.1% return, Sharpe —, max DD −1.3%

Six-Month Stock Momentum

Buys the liquid US stocks with the biggest six-month gains, two a day up to 30, and holds each for six months.

• Momentum
• Single stocks
• 30 six-month winners

Return

−56.6%

CAGR

−8.27%

Sharpe

−0.02

Max DD

−84.5%

Win rate

39.6%

Profit factor

0.92

Hypothetical backtest, costs modeled

Overnight Hold

Holds SPY from each close to the next open, and cash during the day.

• Overnight
• Calendar
• SPY

Return

−24.6%

CAGR

−9.00%

Sharpe

−1.44

Max DD

−26.9%

Win rate

48.7%

Profit factor

1.34

Hypothetical backtest, costs modeled

Opening-Gap Fill

Buys SPY when it opens below the prior close and sells it short when it opens above, aiming for that close before the day ends.

• Mean reversion
• Intraday
• SPY

Return

−33.8%

CAGR

−12.83%

Sharpe

−2.18

Max DD

−34.4%

Win rate

57.3%

Profit factor

1.07

Hypothetical backtest, costs modeled

Noise-Area Momentum

Buys SPY, or sells it short, when it breaks out of its usual range at a half-hour check, and is flat by the close.

• Momentum
• Breakout
• Intraday
• SPY

Return

−46.3%

CAGR

−18.70%

Sharpe

−4.38

Max DD

−46.7%

Win rate

24.2%

Profit factor

1.09

Hypothetical backtest, costs modeled

Opening Range Breakout

Buys QQQ if its first five minutes rose and sells it short if they fell, with a stop at the far side of that range.

• Breakout
• Intraday
• QQQ

Return

−47.4%

CAGR

−19.27%

Sharpe

−3.24

Max DD

−47.7%

Win rate

23.0%

Profit factor

1.07

Hypothetical backtest, costs modeled

First Half-Hour Momentum

Buys SPY for the last half-hour if it is above the prior close at 10:00, and sells it short if not.

• Momentum
• Intraday
• SPY

Return

−51.5%

CAGR

−21.44%

Sharpe

−8.63

Max DD

−51.6%

Win rate

25.6%

Profit factor

1.00

Hypothetical backtest, costs modeled

Intraday EMA Scalp 1m

On 1-minute bars, hold each ETF while its 9-bar EMA is above its 21-bar EMA.

• Trend following
• Intraday
• SPY · QQQ · IWM

Return

−98.8%

CAGR

−77.18%

Sharpe

−12.61

Max DD

−98.8%

Win rate

17.3%

Profit factor

1.15

Hypothetical backtest, costs modeled

Originally published (6 days): −0.2% return, Sharpe —, max DD −0.2%

VWAP Trend

Owns QQQ while it trades above the day's volume-weighted average price, sells it short below, and is flat by the close.

• Trend following
• Intraday
• QQQ

Return

−99.4%

CAGR

−82.11%

Sharpe

−9.04

Max DD

−99.4%

Win rate

10.7%

Profit factor

1.01

Hypothetical backtest, costs modeled

FX Momentum Lots

Trade each pair in the direction of its 126-day move, sized in whole standard lots by ATR risk.

• Momentum
• FX
• FX majors

Spot FX. Orbital's backtester covers US stocks and ETFs.

Originally published (2010-2025): −14.2% return, Sharpe −0.71, max DD −15.3%

The prompt builds the closest version Orbital can run.

Futures Donchian Contracts

55-day Donchian breakout, long or short, in whole contracts sized by ATR and margin.

• Breakout
• Trend following
• Futures
• Futures

Futures. Orbital's backtester covers US stocks and ETFs.

Originally published (2019-2025): +35.5% return, Sharpe 0.30, max DD −16.7%

The prompt builds the closest version Orbital can run.

Monthly Inverse Vol

Always hold all eight ETFs, weighted by the inverse of their 63-day volatility.

• Risk-based sizing
• 8 multi-asset ETFs

Its weights depend on every ETF's volatility at once. Orbital sizes each position from that ETF's own data, so it cannot normalise weights across the basket.

Originally published (2007-2025): +174.2% return, Sharpe 0.45, max DD −20.4%

The prompt builds the closest version Orbital can run.

Signal Change Defensive

If SPY closes above its 200-day SMA, hold SPY, EFA, EEM, DBC and VNQ; otherwise hold TLT, IEF and GLD. Trade only when the regime flips.

• Trend following
• 8 multi-asset ETFs

Its signal is SPY's trend, applied to other ETFs. An Orbital strategy decides each symbol on that symbol's own bars.

Originally published (2007-2025): +132.2% return, Sharpe 0.26, max DD −24.6%

The prompt builds the closest version Orbital can run.

Monthly Circuit Breaker

SMA(50/200) trend on the multi-asset basket, rebalanced monthly; if the account falls 15% from its peak, go to cash for 10 days.

• Trend following
• Risk-based sizing
• 8 multi-asset ETFs

Its circuit breaker reads the account's drawdown, which an Orbital strategy cannot see.

Originally published (2007-2025): +14.2% return, Sharpe −0.45, max DD −10.6%

The prompt builds the closest version Orbital can run.

Quarterly TE Cost Gate

Hold the top three ETFs by 126-day return, rebalanced quarterly, earlier if tracking error versus SPY exceeds 6%, within an annual turnover budget of 4x.

• Momentum
• 8 multi-asset ETFs

It rebalances on tracking error against SPY within a turnover budget, which needs the whole portfolio and SPY in one decision.

Originally published (2007-2025): +266.0% return, Sharpe 0.44, max DD −25.5%

The prompt builds the closest version Orbital can run.

Daily Partial Drift

Weight each sector ETF by its positive 63-day return (zero if negative); only trade positions that drift more than 10 points from target.

• Momentum
• 9 sector ETFs

Its weights are each ETF's momentum as a share of the basket's, which Orbital cannot normalise across symbols.

Originally published (2000-2025): +268.9% return, Sharpe 0.30, max DD −36.8%

The prompt builds the closest version Orbital can run.

Pairs Ratio Z Score

Z-score of log(KO) minus log(PEP) over 60 days: above +2 short KO and buy PEP, below -2 the reverse; close when the z-score is back inside 0.5.

• Mean reversion
• Market neutral
• KO / PEP

A pairs trade needs both prices in one decision. An Orbital strategy decides each symbol on its own bars.

Originally published (2000-2025): +48.8% return, Sharpe −0.05, max DD −23.6%

The prompt builds the closest version Orbital can run.

Pairs Hedge Ratio

Spread of log(EWA) minus a rolling 60-day hedge ratio times log(EWC); trade its 60-day z-score at ±2, exit inside 0.5.

• Mean reversion
• Market neutral
• EWA / EWC

A pairs trade needs both prices in one decision. An Orbital strategy decides each symbol on its own bars.

Originally published (2000-2025): +12.4% return, Sharpe −0.30, max DD −14.3%

The prompt builds the closest version Orbital can run.

Cross Sectional Momentum

Each month-end, buy the three sector ETFs with the best 12-month return and short the three with the worst.

• Momentum
• Market neutral
• 9 sector ETFs

It buys the top three and shorts the bottom three of one ranking. Orbital ranks entries best first and cannot take both ends at once.

Originally published (2000-2025): +1.3% return, Sharpe −0.24, max DD −25.4%

The prompt builds the closest version Orbital can run.

Cross Sectional Reversal

Each Friday, buy the three sector ETFs with the worst 1-month return and short the three with the best.

• Mean reversion
• Market neutral
• 9 sector ETFs

It buys the bottom three and shorts the top three of one ranking. Orbital ranks entries best first and cannot take both ends at once.

Originally published (2000-2025): −1.7% return, Sharpe −0.24, max DD −33.7%

The prompt builds the closest version Orbital can run.

Vol Target Trend

SMA(50/200) trend basket, scaled so the portfolio targets 10% annualized volatility (63-day estimate, up to 1.5x leverage).

• Trend following
• Risk-based sizing
• 8 multi-asset ETFs

It scales the whole portfolio to a volatility target with up to 1.5x leverage. Orbital sizes each position once, at entry, from that symbol's own data.

Originally published (2007-2025): +169.0% return, Sharpe 0.36, max DD −28.9%

The prompt builds the closest version Orbital can run.

Vol Target Momentum

Hold up to three ETFs with the best positive 6-month return, scaled to a 15% volatility target (42-day estimate, up to 2x leverage).

• Momentum
• Risk-based sizing
• 8 multi-asset ETFs

It scales the whole portfolio to a volatility target with up to 2x leverage. Orbital sizes each position once, at entry, from that symbol's own data.

Originally published (2007-2025): +621.2% return, Sharpe 0.57, max DD −41.2%

The prompt builds the closest version Orbital can run.

Risk Parity Multi Asset

Hold all eight ETFs with weights set so each contributes equal risk, from a 63-day covariance estimate.

• Risk-based sizing
• 8 multi-asset ETFs

Equal risk contribution needs the covariance of all eight ETFs at once. Orbital sizes each position from that symbol's own data.

Originally published (2007-2025): +84.5% return, Sharpe 0.16, max DD −35.6%

The prompt builds the closest version Orbital can run.

Risk Parity Capped

Equal-risk-contribution weights across the sector ETFs from a 126-day covariance, capped at 25% each.

• Risk-based sizing
• 9 sector ETFs

Equal risk contribution needs the covariance of all nine ETFs at once. Orbital sizes each position from that symbol's own data.

Originally published (2000-2025): +677.2% return, Sharpe 0.45, max DD −47.9%

The prompt builds the closest version Orbital can run.

FX Time Series Momentum

Trade each pair in the direction of its six-month move, inverse-volatility weighted.

• Momentum
• FX
• FX majors

Spot FX. Orbital's backtester covers US stocks and ETFs.

Originally published (2010-2025): −27.3% return, Sharpe −0.59, max DD −29.4%

The prompt builds the closest version Orbital can run.

FX Cross Sectional Momentum

Long the strongest pair and short the weakest by three-month return.

• Momentum
• Market neutral
• FX
• FX majors

Spot FX. Orbital's backtester covers US stocks and ETFs.

Originally published (2010-2025): −34.1% return, Sharpe −1.00, max DD −41.4%

The prompt builds the closest version Orbital can run.

Continuous Futures Trend

Diversified long/short trend across index, rates, energy, metals and grains, inverse-volatility weighted.

• Trend following
• Futures
• Futures

Futures. Orbital's backtester covers US stocks and ETFs.

Originally published (2019-2025): +46.3% return, Sharpe 0.62, max DD −9.7%

The prompt builds the closest version Orbital can run.

Rolling Walk-Forward Validation

Re-checks the SMA(50/200) sector rule (W01) on sliding train/test windows.

• Walk-forward
• 9 sector ETFs

A validation workflow around W01's rule rather than a strategy of its own. Orbital covers part of the same ground for every strategy: its Backtesting list discounts the Sharpe for every configuration tried, and each report resamples the trades 1,000 times.

The prompt builds the closest version Orbital can run.

Expanding Walk-Forward Validation

Re-checks the SMA(50/200) sector rule (W01) with an expanding training window.

• Walk-forward
• 9 sector ETFs

A validation workflow around W01's rule rather than a strategy of its own. Orbital covers part of the same ground for every strategy: its Backtesting list discounts the Sharpe for every configuration tried, and each report resamples the trades 1,000 times.

The prompt builds the closest version Orbital can run.

Anchored Walk-Forward With Pre-OOS Purging

Re-checks the weekly RSI rule (W03) with purged, anchored windows.

• Walk-forward
• 9 sector ETFs

A validation workflow around W03's rule rather than a strategy of its own. Orbital covers part of the same ground for every strategy: its Backtesting list discounts the Sharpe for every configuration tried, and each report resamples the trades 1,000 times.

The prompt builds the closest version Orbital can run.

Grid Search Parameter Optimization

Searches nine SMA fast/slow pairs for the sector rule; best was SMA(20/200).

• Walk-forward
• 9 sector ETFs

A validation workflow around W01's rule rather than a strategy of its own. Orbital covers part of the same ground for every strategy: its Backtesting list discounts the Sharpe for every configuration tried, and each report resamples the trades 1,000 times.

The prompt builds the closest version Orbital can run.

Optuna TPE Optimization + Walk-Forward

Searches SMA windows with Optuna; best was SMA(23/206).

• Walk-forward
• 9 sector ETFs

A validation workflow around W01's rule rather than a strategy of its own. Orbital covers part of the same ground for every strategy: its Backtesting list discounts the Sharpe for every configuration tried, and each report resamples the trades 1,000 times.

The prompt builds the closest version Orbital can run.