• This 5-stock trading strategy with the stocks from Invesco QQQ Trust produces much higher returns than the ETF (QQQ).
• The universe from which stocks are selected is the Nasdaq 100 Index which represents all the point-in-time holdings of QQQ.
• The model ranks the stocks of the Nasdaq 100 Index and selects periodically the highest ranked stocks which also satisfy certain yield requirements.
• From 1/2/2009 to 10/30/2020 this strategy would have produced an annualized return (CAGR) of 28.5%, more than the 21.2% CAGR of QQQ over this period.

In a previous article, I discussed the seasonal effect in equities and showed that they perform best from November to April, the “good” period, and that replacing equities with fixed income during the “bad” period of May thru October is a winning strategy over the longer term.

Since future returns from fixed income are uncertain, the strategy proposed here is to always invest in sector equity ETFs. I defined two super-sector groups, classified as aggressive and defensive, each with four sector ETFs which have historically performed best from November to April and relatively well from May to October, respectively.

This simple strategy invests alternately in the aggressive and defensive super sectors during their respective six-month periods, switching from aggressive to defensive at the end of April, and vice versa at the end of October.

• This 5-stock trading strategy with the Consumer Discretionary Sector stocks of the S&P 500 produces much higher returns than the Consumer Discretionary Select Sector SPDR Fund (XLY).
• The universe from which stocks are selected emulates as close as possible the point-in-time holdings of XLY.
• The model ranks the stocks of this custom universe and selects periodically the highest ranked stocks which also satisfy stipulated yield requirements.
• From 1/2/2009 to 10/23/2020 this strategy would have produced an annualized return (CAGR) of 22.7%, more than the 19.3% CAGR of XLY over this period.

• This 5-stock trading strategy with the Materials Sector stocks of the S&P 500 produces much higher returns than the Materials Select Sector SPDR Fund (XLB).
• The universe from which stocks are selected holds point-in-time, the S&P 500 non-energy materials stocks of FactSet’s Reverse Business Industry Classification System.
• The model ranks the stocks of this custom universe and selects periodically the highest ranked stocks which also satisfy stipulated yield requirements.
• From 1/2/2009 to 10/21/2020 this strategy would have produced an annualized return (CAGR) of 19.2%, significantly more than the 11.5% CAGR of XLB over this period.

• This 5-stock trading strategy with the Utility Sector stocks of the S&P 500 produces much higher returns than the Utility Select Sector SPDR Fund (XLU).
• The universe from which stocks are selected holds point-in-time, the S&P 500 utility stocks of FactSet’s Reverse Business Industry Classification System.
• The model ranks the stocks of this custom universe and selects periodically the highest ranked stocks which also satisfy stipulated yield requirements.
• From 1/2/2009 to 10/1/2020 this strategy would have produced an annualized return (CAGR) of 12.7%, versus the 10.2% CAGR of XLU over this period.

• This 5-stock trading strategy with the Industrial Sector stocks of the S&P 500 produces much higher returns than the Industrial Select Sector SPDR Fund (XLI).
• The universe from which stocks are selected holds point-in-time the S&P 500 industrial stocks of FactSet’s Reverse Business Industry Classification System.
• The model ranks the stocks of this custom universe with the Portfolio123 “Greenblatt” ranking system and selects periodically the highest ranked stocks which also satisfy stipulated yield requirements.
• From 1/2/2009 to 10/2/2020 this strategy would have produced an annualized return (CAGR) of 20.6%, significantly more than the 12.7% CAGR of XLI over this period.

• This 5-stock trading strategy with the Healthcare Sector stocks of the S&P 500 produces much higher returns than the Healthcare Select Sector SPDR Fund (XLV).
• The universe from which stocks are selected holds point-in-time, the S&P 500 healthcare stocks of FactSet’s Reverse Business Industry Classification System.
• The model ranks the stocks of this custom universe with the Portfolio123 “Greenblatt” ranking system and selects periodically the highest ranked stocks which also satisfy stipulated industry and yield requirements.
• From 1/2/2009 to 9/28/2020 this strategy would have produced an annualized return (CAGR) of 23.6%, significantly more than the 13.8% CAGR of XLV over this period.

• This 5-stock trading strategy with the Consumer Staples Sector stocks of the S&P 500 produces much higher returns than Consumer Staples Select Sector SPDR Fund (XLP).
• The universe from which stocks are selected holds point-in-time, the S&P 500 consumer non-cyclical stocks of FactSet’s Reverse Business Industry Classification System.
• The model ranks the stocks of this custom universe with a modified “Greenblatt” ranking system and selects periodically the highest ranked stocks which also satisfy stipulated yield requirements.
• From 1/2/2009 to 9/23/2020 this strategy would have produced an annualized return (CAGR) of 25.3%, significantly more than the 11.4% CAGR of XLP over this period.

• This trading strategy with five stocks from those of ETF (XLK), mainly with a dividend yield greater than that of the S&P 500 index, produces much higher returns than XLK.
• The universe from which stocks are selected holds point-in-time, the S&P 500 technology stocks of FactSet’s Reverse Business Industry Classification System and some electronic payments industry stocks, similar to XLK.
• The model ranks the stocks of this custom universe with the Portfolio 123 “Greenblatt” ranking system and selects periodically the highest ranked stocks which also satisfy the stipulated yield requirement.
• From 1/2/2009 to 9/8/2020 this strategy would have produced an annualized return (CAGR) of 31.8%, significantly more than the 20.1% CAGR of XLK over this period.

The analysis was performed on the on-line portfolio simulation platform Portfolio 123.
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• A simulation of this strategy with annual withdrawal rates of up to 10% still showed long-term growth which exceeded that of buy-and-hold the S&P 500 ETF (SPY).
• The backtests use the FactSet stock database and FactSet’s Revere Business Industry Classifications System (RBICS).
• The model holds equal-weight 10 stocks of the Russell 1000 index which are ranked with a simple ranking system to identify shares of the highest “quality” companies.
• The strategy provides a high dividend yield because a minimum yield excess (depending on RBICS sector type) over the yield of SPY is a critirium for stock selection.
• From Jan-2000 to Jun-2020 this strategy without withdrawals would have produced an annualized return (CAGR) of 21.5%, much more than the 5.6% CAGR obtained from SPY over the same period.