• 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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• This is a copycat trading strategy based on the quarterly 13F filings of 10 large hedge funds with assets under management (AUM) greater than $3.5-Billion.
• The algorithm looks at the top 20 largest holdings from each of the 10 filers and then picks the 15 most frequently held stocks among all of the filers.
• The model selects 12 of the 15 consensus picks from this hedge fund group with a ranking system based on quality.
• Changes in the holdings occur only every three months, about 45 days after the end of a quarter when 13F filings become public information, February, May, August, and November.
• From Feb-2008 to Aug-2020 this strategy would have produced an annualized return (CAGR) of 27.6%, significantly more than the 10.1% CAGR of the S&P 500 ETF (SPY) over this period.

• 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.

• A truer picture of the employment situation is extracted from the Unemployment Insurance Weekly Claims (UIWC) report.
• Persons receiving some form of unemployment benefit account for 18.6% of the labor force and not 13.3% – the official unemployment rate. 
• Monitoring of the weekly insured unemployed can provide early indication of recovery from the Covid-19 crisis.
• No meaningful economic recovery is identified from the current UIWC report.

• This is a copycat trading strategy based on the quarterly 13F filings of five hedge funds.
• The model holds the top 20 consensus picks from a group of five hedge funds.
• Changes in the holdings occur only every three months when the end-of-the-month 13F filings becomes public information.
• From Jan-2007 to May-2020 this strategy would have produced an annualized return (CAGR) of 27.1%, much more than the 7.8% CAGR of the S&P 500 ETF (SPY).

Rational for a Copycat Strategy

Research from Barclay and Novus published in October 2019 found that a stock selection copycat strategy that combines conviction and consensus of fund managers that have longer-term views outperformed the S&P 500 by 3.80% on average annually from Q1 2004 to Q2 2019.