- 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%.
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Profiting from Seeking Alpha’s Undercovered Stocks
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The iM Minimum Volatility (USMV) – Investor
- 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.
Is the Stock Market Overvalued? – Update July 2019, and 10-Year Real Forward Return Estimate
- 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.
The iM-SuperTimer – Simulated on Portfolio 123
- 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.
A Winning Strategy to Profit from the Seasonal Effect in Equities
- 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.
Why Not To Invest In Vanguard’s U.S. Momentum Factor ETF (VFMO) – 1-Year On
- 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.
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How Good Are Target-Date Glidepath Savings Programs During the Accumulation Phase Towards Retirement?
- 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 iM-SuperTimer – Update March 2019: Timing the Market with the iM-Stock Market Confidence Level
- 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.
Beyond Buy-and-Hold: Improving Returns on Long-Term Investments Using the Shiller CAPE-MA35 Ratio
- 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.
Estimating Forward 10-Year Stock Market Returns using the Shiller CAPE Ratio and its 35-Year Moving Average. (Update Dec-2018)
- 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.
With reference to Section 202(a)(11)(D) of the Investment Advisers Act:
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