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• In February 2018 Vanguard released a set of five actively managed sector ETF’s and one multi-factor ETF. Here we report on the performance of the Momentum Factor ETF (VFMO).
• Shortly after the inception of VFMO we published “Why Not To Invest In Vanguard’s New U.S. Momentum Factor ETF” which demonstrated that Vanguard’s selection criteria for this fund was flawed.
• In the referenced article we stated that it was unlikely that VFMO would show a higher return than the SPDR S&P 500 ETF (SPY) over the year following inception.
• In April 2019 in a follow up article we showed that the actual performance of VFMO since inception was 6.8% lower than that of SPY, confirming the conclusion in the bullet-point above.
• Again, VFMO has underperformed SPY, and we come to the same conclusion for the following year, namely that the one-year return to Feb-2021 will be less than that of SPY.

• For a detailed model description of the system please read the original description and previous update.
• To make this model more user-friendly we will be providing signals for three different version of this model, all updated weekly.
• The models’ holdings alternate between ETF (SPY) and ETF (IEF), being proxies for investments during up- and down stock market periods, repectively.
• The iM-1wk-SuperTimer (SPY-IEF) would have produced an annualized return of 19.9% with a max drawdown of about -10%.
• Appendix 2 shows that a (50%SPY+50%VCIT)-(IEF) strategy reduces drawdowns to -6.2% but would still have achieved an annualized return of 14%.
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• The new Federal Reserve Bank of Chicago Brave-Butters-Kelley Indexes ( BBK ) provide useful input for recession forecasting.
• In the past, low estimates of BBK GDP growth related to the respective recessions, this allow the extraction of a recession warning signal from this growth series.
• We combine two BBK indexes with the Conference Board LEI and iMarketSignals’ Business Cycle Index BCIg to derive our Long Leading Index (iM-LLI) for the US economy.
• Currently neither index signals a recession warning.

• The new Federal Reserve Bank of Chicago Brave-Butters-Kelley Indexes (BBK) provide useful input for recession forecasting.
• We combine two BBK indexes with the Conference Board LEI and our Business Cycle Index BCIg to derive iMarketSignals’ new Long Leading Index (iM-LLI) for the US economy.
• Our analysis shows that the iM-LLI would have provided an average warning signal about eight months before the start of recessions, as observed for the last seven recessions since 1967.
• We are replacing the iM-Composite Index (COMP) with the new iM-LLI.
• Currently this Leading Index is not yet warning of an oncoming recession.

• From November 2019 onward, the Federal Reserve Bank of Chicago is releasing new measures of monthly real GDP growth and its components, the Brave-Butters-Kelley Indexes.
• The data release is for four indicators constructed from a panel of 500 monthly macroeconomic time series and quarterly real gross domestic product growth.
• Our analysis shows that apart from the Leading Index, the other three indicators would have been extremely accurate identifying recessions were it not for the publication time-lag.
• This time-lag makes, on average, these indicators about two month late to signal the start and end of recessions in real-time, as observed for the last seven recessions since 1967.
• Currently none of the Brave-Butters-Kelley Index models are warning of a recession.

• The average of S&P 500 for Dec-2019 was 3166; that is 852 (i.e. 27% of 3166) above the Jan-2020 level of the long-term trend line.
• The Shiller Cyclically Adjusted Price to Earnings Ratio (CAPE) is at a relatively high level of 30.1, and the 35-year moving average (MA35) of the CAPE is at 24.2.
• The CAPE-MA35 ratio is 1.25, forecasting a 10-year annualized real return of 5.9%.
• Investing in equities for the long-haul when the CAPE-MA35 ratio is below 1.30 should produce reasonable returns, as this level of the ratio does not indicate an abnormally overvalued market.

• This strategy exploits the anomaly that Cyclical Sectors and Small Caps perform best from November to April, and Defensive Sectors do better from May to October during most years.
• Three identical models starting 6 months apart are used. Each model holds only one ETF for 18 months selected by a simple ranking system from the cyclical and defensive groups.
• The effect of this is that the combination model always has 66% of the portfolio in the “correct” direction, defensive or cyclical, and 33% in the “wrong” direction.
• The combination model trades only twice a year, switching only one position at the end of April and end of October.
• For the approximately 18.5 year period from end of Apr-2000 to Sep-2019 the backtest showed an annualized return of 12.3% with a maximum drawdown of -24%.

• An interest rate environment in which long-term debt instruments have a lower yield than short-term debt instruments of the same credit quality is considered to be a predictor of recessions.
• Prior to recession it is advisable to exit the stock market and invest in U.S. Treasuries instead; in this strategy using as proxies ETFs (SPY) and (IEF), respectively.
• This model uses the 2-year and 10-year U.S. Treasury yields as measures of short-term and long-term rates, respectively, and calculates the Forward Rate Ratio (FRR2-10) between the two rates.
• FRR2-10 is the ratio of the rate at which one can lock in borrowing for the eight year period starting two years from now and the current ten-year rate itself.
• Currently the FRR2-10 is near 1.0 signifying that US economic activity is near the end of the expansion phase of this business cycle.

• The iM-Bond Market Trader exploits the fact that, generally, when equity returns are good high yield bonds outperform investment grade bonds.
• When equity performs well the model invests in one of the high yield bond ETFs HYG, JNK, or EMB.
• If stock market climate deteriorates the model switches to Treasury Bond ETF IEF.
• Backtesting over the preceding 20 years the model showed a simulated annualized return of 14.6% with a maximum drawdown of -9.6%, versus 5.0% and -9.3% for benchmark ETF BND, respectively.
• Simulations also show that the model’s returns over any calendar year are positive and exceeded those of BND.

This model uses only four fixed income ETFs:
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• Seeking Alpha publishes a dynamic list of 250 popular tickers that haven’t had recent coverage, mainly small-caps. Ranking and periodically selecting 50 of these undercovered stocks should provide good returns.
• A trading strategy, backtested over the preceding three years, showed a simulated annualized return of 48% with a maximum drawdown of -18%..
• Although the portfolio is relatively large, the annual turnover is only 140%.

• Since the launch of IM-Best12(USMV)Qx (x=1,2,3,or 4) in 2014, these models converged to a combined holding of 18 stocks, thus future performance of each of the models is expected to be very similar.
• There is not much to be gained by following four similar models and these are now replaced by the iM Min Volatility(USMV)-Investor.
• This model holds 10 equal weighted stocks and the simulated performance since 1/3/2013 shows an annualized return of 22.0% versus 14.3% for SPY and an annual turnover ratio of 60%
• As from Sunday 7 July we will disseminate to Gold Subscribers any buy/sell signals this model generates.

• The average of S&P 500 for Jun-2019 was 2,890. A 20% decline from this level would bring it to the Jan-2020 level of the long-term trend line.
• The Shiller Cyclically Adjusted Price to Earnings Ratio (CAPE) is at a relatively high level of 28.9, and the CAPE’s 35-year moving average (MA35) is at 23.9.
• The CAPE-MA35 ratio is 1.21, forecasting a 10-year annualized real return of 6.2%. This would indicate that for long-term investors the S&P 500 is currently not overvalued.
• Investing in equities for the long-haul when the CAPE-MA35 ratio is below 1.30 should produce reasonable returns as this level of the ratio does not signifies overvaluation of the market.

• For a detailed model description of the system please read the original description, update No.1 and update No.2
• We have transferred the excel data onto Portfolio 123 and will in future be providing signals and performance for the weekly, monthly and 3-month models running on Portfolio 123, all updated weekly.
• The models’ holdings alternate between ETF (SPY) and ETF (IEF), being proxies for investments during up- and down stock market periods.

• The seasonal effect that equities do better from November through April is well-known. Here we provide a rigorous statistical test of this and a trading strategy to profits from it.
• From 1960 the S&P 500 with dividends returned on average 1.92% for the six months May to October, the “bad-periods”, while the “good-periods”, November to April, returned 8.47% on average.
• Statistics provide a 65% probability that good-periods will produce higher returns than the average of all good- and bad-periods, and a similar probability that the bad-periods will produce lower returns.
• This anomaly can be exploited by tactically shifting from more aggressive “good-period portfolios” to lower risk portfolios at the end of every April, and reversing the process end of October.
• Switching accordingly between the S&P 500 and 10-Year Treasuries would have provided an annualized return of 12.1% from 1960 to 2019 versus 9.4% for buy-and-hold the S&P 500.

• In February 2018 Vanguard released a set of five actively managed sector ETF’s and one multi-factor ETF. Here we report on the performance of the Momentum Factor ETF (VFMO).
• Shortly after the inception of VFMO we published this article “Why Not To Invest In Vanguard’s New U.S. Momentum Factor ETF” which demonstrated that Vanguard’s selection criteria was flawed.
• In the referenced article we stated that it was unlikely that VFMO will show a higher return than the SPDR S&P 500 ETF (SPY) over the year following inception.

• This study analyzes Yale’s Qualified Default Investment Alternative, a retirement plan with a target-date strategy. The findings also apply in principle to target-date strategy models from Vanguard, Fidelity, and others.
• Yale University’s new retirement plan provides a “Glidepath” Target-Date Plus Service and also allows participants to opt out from it to pick their own investments from a few select funds.
• Backtests (1999-2019) show that Yale’s Glidepath strategy would not have performed particularly well; one would have done better selecting one’s own funds, or by following the traditional 60%Stock-40%Bond constant allocation.
• Retirement savings were calculated for a hypothetical individual making contributions to a retirement fund from Jan-2000 onwards using various allocation strategies, including Yale’s Glidepath and also a reverse glide-path strategy.
• Much higher savings with relatively low risks can be obtained by employing a dynamic investment strategy using models which have moderately different allocations for up- and down-market conditions.

• The system uses a composite model consisting of several market timers. It should deliver more reliable signals for profitable investment and saving plans than single market timing models.
• Component timers are allocated a 100% stock holding percentage when the timer signals investment in the stock market, or 0% when the timer it is out of the stock market.
• A weekly Stock Market Confidence Level (SMC level), which can range from 0% to 100%, is obtained by considering the percentage allocated to each component timer and the timer’s weight in the system.
• A backtest of a combination model of 15 iMarketSignals timers signaled avoidance of the stock market for SMC levels <=50%, while SMC levels >50% suggest better stock market investment climates.

• Forward 10-year annualized real returns of the S&P 500 Index can be determined by regression analysis using the ratio of the Shiller CAPE-ratio and its 35-year moving average (CMA-ratio).
• Currently this ratio stands at 1.21 and forecasts a 10-year annualized real return of 6.2%, which would indicate that the market as represented by the S&P 500 is not overvalued.
• Since 1979, when the CMA-ratio was within +/-5% of the current value the 10-year annualized real returns for the S&P500 that followed ranged from 4.7% to 14.6%, averaging 9.8%.
• Investing in equities for the long-haul when the CMA-ratio is at 1.50 or higher produces poor returns, as this level of the ratio signifies overvaluation of the market.

• The Dec-2018 Shiller Cyclically Adjusted Price to Earnings Ratio (CAPE-ratio) stands at 27.9, which is 11.0 above its long-term mean of 16.9, signifying overvaluation of stocks and low forward returns.
• The MA35-CAPE-Ratio methodology references stock market valuation to a 35-year moving-average of the Shiller CAPE-ratio (MA35) instead of the 1881-2018 long-term mean which the standard forecasting method is based on.
• The MA35-CAPE-Ratio method should be superior to the standard CAPE-ratio method as only the percentage difference between the CAPE-ratio and its MA35 is considered, and not the absolute difference.
• The MA35-CAPE-Ratio method and the falling trend of the CAPE-ratio currently signal a forward 10-year annualized real return for stocks of about 5.8%, while the historic long-term trend forecasts 5.0%.
• Only the ratio between the prevailing CAPE-ratio and its 35-year moving average (CAPE-ratio / MA35) is needed to easily obtain the expected 10-year forward returns from the charts in this article.