• The Yield Curve / Federal Funds Rate Timer signals the switches from stocks to gold and vice versa near or during recession periods.
• Only three parameters are needed; the Effective Federal Funds Rate and the 2-year and 10-year U.S. Treasury yields to determine the periods when the yield curve is inverted.
• The timing rules are based on the state of yield curve and on the trend of the Effective Federal Funds Rate.

This timer signals switches from stocks (S&P500 Total Return) to gold and vice versa near or during recession periods.
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• This strategy exploits the anomaly that equities perform best from November to April, and less so from May to October during most years.
• ETFs (XLV, XLI, XLY, XLB) have historically performed best from November to April, and ETFs (XLK, XLP, XLU, QQQ) have done better than the first group from May to October.
• The super-sector models termed “aggressive” and “defensive” combine, respectively, the Top5(Sector)Select models for ETFs (XLV, XLI, XLY, XLB) and ETFs (XLK, XLP, XLU, QQQ), all previously published on Seeking Alpha.
• This strategy invests alternatingly in the aggressive- and defensive super-sector models during their respective “good” 6-month periods.
• From Jan-2000 to Nov-2020 a backtest shows that this strategy would have outperformed the SPDR S&P 500 ETF Trust (SPY), producing an annualized return of 23.3% versus 6.1% for SPY.
• NOTE: Elsewhere we refer to the “aggressive” season as the winter season, and conversely the “defensive” as the summer season. This model switches all holdings bi-annually end of April and end of October.

• 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.