Strategy 1: ATR Swing Trade Nasdaq/S&P 500

The strategy uses ATR as “bands” but additionally uses two other criteria. The strategy works best on the S&P 500 and Nasdaq.

The strategy was our monthly Trading Edge for August 2021.

Performance from 2000 until spring 2021 in Nasdaq (QQQ):

• No. of trades: 157
• Average gain per trade: 1.8% (2.84% for winners and -2.27% for losers)
• Win ratio: 79%
• Profit factor: 3.61
• CAGR: 13.7%
• Exposure/time in the market: 11%
• Max drawdown: -19.5%

The equity curve (log scale) on QQQ:

Order by clicking here (check for strategy no.1):

Strategy 2: IBS Swing Trade in the S&P 500

The strategy uses the IBS indicator but we made a small twist to it. The strategy performs well on stock indices but yields the best result on the S&P 500.

The strategy was our monthly Trading Edge for October 2021.

Performance from 1993 until spring 2021 in the S&P 500 (SPY):

• No. of trades: 526
• Average gain per trade: 0.8% (1.67% for winners and -1.75% for losers)
• Win ratio: 74%
• Profit factor: 2.73
• CAGR: 15.4%
• Exposure/time in the market: 36%
• Max drawdown: -22%

The equity curve (log scale) in SPY:

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Strategy 3: Williams R% Swing Trade in Nasdaq

The strategy uses the famous and handy Williams %R indicator but we added another indicator to make the strategy more robust and better. The strategy performs well on most stock indices but yields the best result in Nasdaq.

Performance from 2000 until spring 2021 in Nasdaq (QQQ):

• No. of trades: 215
• Average gain per trade: 1.4% (2.35% for winners and -2.2% for losers)
• Win ratio: 79%
• Profit factor: 3.53
• CAGR: 14.6%
• Exposure/time in the market: 14%
• Max drawdown: -20.5%

The equity curve (log scale) in QQQ:

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Strategy 4: IBS + Second Indicator Swing Trade in the S&P 500/Nasdaq

The strategy uses the widely used IBS indicator but we added a second indicator to improve the strategy. The strategy performs well on most stock indices but yields the best result in the S&P 500 and Nasdaq.

Performance from 2000 until spring 2021 in Nasdaq (QQQ):

• No. of trades: 196
• Average gain per trade: 1.36% (2.5% for winners and -2.2% for losers)
• Win ratio: 75%
• Profit factor: 3.15
• CAGR: 12.7%
• Exposure/time in the market: 14%
• Max drawdown: -19.5%

The equity curve (log scale) in QQQ:

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Strategy 5: ADX + Second Indicator Swing Trade in Nasdaq (works on S&P 500 as well)

The strategy uses the often ignored ADX indicator. The indicator is valuable, but not on a stand-alone basis. We have developed an ADX strategy together with another indicator. The strategy performs well on most stock indices but yields the best result in Nasdaq.

Performance from 2000 until spring 2021 in Nasdaq (QQQ):

• No. of trades: 238
• Average gain per trade: 1.1% (2.2% for winners and -2.5% for losers)
• Win ratio: 77%
• Profit factor: 2.83
• CAGR: 12.6%
• Exposure/time in the market: 17%
• Max drawdown: -27.5%

The equity curve (log scale) in QQQ:

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Strategy 6: 23 Candlestick formations

We have Amibroker code for 23 candlestick formations (no Tradestation code yet for candlesticks). Please check out this article where we tested these 23 formations. The formations seem to work on the S&P 500 and Nasdaq.

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Strategy 7: XLP And Treasury Bond Strategy

The ETF XLP tracks consumer stocks like Wal-Mart, Procter&Gamble, etc. Its movements are different than the main stock indices and XLP is an underrated trading vehicle.

We have made a strategy that generates signals in XLP based on the ETF TLT (10-year Treasury Bonds).

This strategy was our monthly Trading Edge for May 2021.

Performance from 2002 until spring 2021 in XLP:

• No. of trades: 416
• Average gain per trade: 0.46% (1.08% for winners and -1.25% for losers)
• Win ratio: 73%
• Profit factor: 2.18
• CAGR: 9.1%
• Exposure/time in the market: 32%
• Max. drawdown: -15%

The equity curve (log scale):

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Strategy 8: XLP Swing Trade

The ETF XLP tracks consumer stocks like Wal-Mart, Procter&Gamble, etc. Its movements are different than the main stock indices and XLP is an underrated trading vehicle.

The strategy is based on two variables but has yet proven efficient.

The strategy was our monthly Trading Edge for April 2021.

Performance from 2002 until spring 2021 in XLP:

• No. of trades: 141
• Average gain per trade: 0.74% (1.26% for winners and -1.8% for losers)
• Win ratio: 83%
• Profit factor: 3.48
• CAGR: 5.1%
• Exposure/time in the market: 10%
• Max. drawdown: -10%

The equity curve (log scale):

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Strategy 9: Overnight Open<Low Edge in Nasdaq

The strategy buys at the close and sells on the next open (no matter what). The strategy is based on two variables but has yet proven efficient.

This strategy was our monthly Trading Edge for March 2021.

Performance from 2000 until spring 2021 in Nasdaq (QQQ):

• No. of trades: 502
• Average gain per trade: 0.24% (0.84% for winners and -0.72% for losers)
• Win ratio: 62%
• Profit factor: 1.79
• CAGR: 5.7%
• Exposure/time in the market: 9.5%
• Max. drawdown: -11%

The equity curve (log scale):

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Strategy 10: End Of Month Overnight Edge In The S&P 500

The strategy buys at the close and sells on the next open (no matter what). The strategy is based on one variable but has yet proven efficient.

This strategy was our monthly Trading Edge for February 2021.

Performance from 1993 until spring 2021 in the S&P 500 (SPY):

• No. of trades: 178
• Average gain per trade: 0.14% (0.41% for winners and -0.35% for losers)
• Win ratio: 65%
• Profit factor: 2.1
• CAGR: 1.2%
• Exposure/time in the market: 3%
• Max. drawdown: -3%

The equity curve (log scale):

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Strategy 11: Friday Bond Trade (TLT)

The strategy is based on seasonality and has additionally two simple criteria based on where the close is in relation to the previous days.

This strategy was our monthly Trading Edge for June 2021.

Performance from 2004 until spring 2021 in ten year Treasury bonds (TLT):

• No. of trades: 221
• Average gain per trade: 0.45% (0.94% for winners and -1.14% for losers)
• Win ratio: 75%
• Profit factor: 2.7
• CAGR: 5.9%
• Exposure/time in the market: 15%
• Max. drawdown: -8.8%

The equity curve (log scale):

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Strategy 12: Overnight Short in Chinese stocks (FXI)

The strategy is based on a weekly seasonality and enters at the close and exits at the open the next day.

This strategy was our monthly Trading Edge for July 2021.

Performance from 2010 until spring 2021 in the ETF with ticker code FXI:

• No. of trades: 151
• Average gain per trade: 0.34% (0.9% for winners and -0.7% for losers)
• Win ratio: 65%
• Profit factor: 2.4
• CAGR: 4.4%
• Exposure/time in the market: 2.6%
• Max. drawdown: -3.6%

The equity curve (log scale):

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Strategy 13: Overnight Long trade in Silver Miners (SIL)

The strategy enters at the close and exits at the open the next day based on two simple criterias.

This strategy was our monthly Trading Edge for September 2021.

Performance from 2010 until September 2021 in the ETF with ticker code SIL:

• No. of trades: 215
• Average gain per trade: 0.63% (1.33% for winners and -0.8% for losers)
• Win ratio: 67%
• Profit factor: 3.3
• CAGR: 12.1%
• Exposure/time in the market: 7%
• Max. drawdown: -4.8%

The equity curve (log scale):

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Strategy 14: Overnight Long trade in DAX-futures (FDAX)

The strategy enters at the close (1730 CET) and exits at the open the next day (0900 CET). There are two buy criteria. The backtest is on the big contract (FDAX).

This strategy was our monthly Trading Edge for November 2021.

Performance from 2000 until summer of 2021 in the FDAX futures contract:

• No. of trades: 209
• Average gain per trade: 0.22% (0.67% for winners and -0.61% for losers)
• Win ratio: 65%
• Profit factor: 2
• CAGR: 2.15% (assuming no leverage)
• Exposure/time in the market: 3.82%
• Max. drawdown: -5.12%

The equity curve (log scale):

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Strategy 15: Short swing trade in TLT/bonds

The strategy has two variables for entry and exits after n days.

This strategy was our monthly Trading Edge for December 2021.

Performance from 2000 until today:

• No. of trades: 184
• Average gain per trade: 0.52% (1.86% for winners and -1.66% for losers)
• Win ratio: 62%
• Profit factor: 1.8
• CAGR: 4.9% (assuming no leverage)
• Exposure/time in the market: 26%
• Max. drawdown: -13%

The equity curve (log scale):

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Strategy 16: Long swing trade in XLU (utilities)

The strategy has two variables for entry and exits after n days.

This strategy was our monthly Trading Edge for January 2022.

Performance from 2000 until today:

• No. of trades: 145
• Average gain per trade: 0.88% (2.22% for winners and -1.44% for losers)
• Win ratio: 63%
• Profit factor: 2.6
• CAGR: 5.75% (assuming no leverage)
• Exposure/time in the market: 15%
• Max. drawdown: -10%

The equity curve (log scale):

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Strategy 17: Long volatility swing trade in SPY (S&P 500)

The strategy has two variables for entry and one for the exit. The strategy is a volatility long strategy and about 65% of the trades enter on a day where the close is higher than the previous close, even high RSI. Thus, it should work well with mean reversion strategies.

This strategy was our monthly Trading Edge for February 2022.

Performance from 1993 until today:

• No. of trades: 365
• Average gain per trade: 0.42% (0.95% for winners and -1.25% for losers)
• Win ratio: 76%
• Profit factor: 2.3
• CAGR: 5.2% (assuming no leverage)
• Exposure/time in the market: 14%
• Max. drawdown: -16%

The equity curve (log scale):

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Strategy 18: Overnight long trade in SPY (S&P 500)

The strategy has three variables for entry and one for exit. Entry is at the close and the exit is at the close the next day.

This strategy was our monthly Trading Edge for March 2022.

Performance from 1993 until today:

• No. of trades: 367
• Average gain per trade: 0.36% (1.37% for winners and -1.2% for losers)
• Win ratio: 61%
• Profit factor: 1.78
• CAGR: 4.4% (assuming no leverage)
• Exposure/time in the market: 5%
• Max. drawdown: -10%

The equity curve (log scale):

You can read more about our best trading strategies here.