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• The 34th occurrence (since 1950) of the 50-day moving average of the S&P 500 crossing its 200-day moving average to the downside is imminent.
• The Death Cross is inevitable, and will occur early December.
• The looming Death Cross could indicate the potential for a major selloff.

• The 34^th occurrence (since 1950) of the 50-day moving average of the S&P 500 crossing its 200-day moving average to the downside is imminent.
• Only a 7.9% upturn in the S&P 500 can avoid the “Death Cross”

• Over the last 20 years this Timer provided only two exit periods for the stock market.
• By being out of the stock market during those periods one would have avoided most of the two bear markets and losses of 35% and 43%, respectively.

• Past research suggests that the relative change in the volume of Google searches for financial terms such as “debt” or “stocks” can be used to anticipate stock market trends.
• In this analysis the search term “debt” was used to obtain monthly search volume data from Google Trends.
• The analysis shows, that a decrease in search volume typically preceded price increases of the S&P 500 index, and vice versa.
• Switching between ETF (SPY) and ETF (IEF) based on monthly search volume data from 2005 to 2018, would have made a profit of 634% versus 220% for buy-and-hold SPY.

• The iM-Country Rotation System periodically selects one country ETF from six countries, USA, Canada, Japan, Australia, Germany and Sweden, based on the performance of their respective currency ETFs.
• Backtests from 2009 to 2018 (the bull market period) show that each foreign country ETF under-performed the US stock market over the full backtest period.
• However, when periodically selecting ETFs using a ranking system based on the performance of the countries’ respective currency ETFs, the model significantly out-performed the US stock market.
• Over the period 3/9/2009-7/21/2018 the system showed a simulated annualized return of 29.4% versus 18.7% for the SPDR S&P 500 ETF Trust (SPY), with similar maximum draw-downs of about -19%.

• From 1950 to 2018 the S&P 500 performed best from November to April, and significantly worse from May to October during most years.
• From 1950-2018 the real annualized return for the S&P 500 was 6.71%. Had one only invested from November to April each year the return would have been 6.60%, almost the same.
• Investing in a money-market fund from May to October each year and the remaining time in the S&P 500 would have provided a higher real annualized return of 7.17%.
• For the 32 year period of rising interest rates (1950-1982) the real return of the S&P 500 was only 5.40%, much less than for following 36 years of falling interest rates.

• 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.
• In this analysis only one ETF is periodically selected by a simple ranking system from the cyclical and defensive groups, respectively, and held for six months.
• Out of the 37 six-month periods, 36 periods showed gains ranging from 0.1% to 28.1%, while only one six-month period produced a loss of -9.3%.
• For the approximately 18.5 year period from end of Oct-1999 to May-2018 the backtest showed an annualized return of 19.8% with a maximum drawdown of -30%.
• For an “inverted” switching strategy, when cyclicals ETFs are used for the May-October period and defensive ETFs during November-April period, the annualized return was 3.2% and maximum drawdown was -60%.

• The iM-Best12(USMV)-Trader periodically invests in the 12 highest ranked stocks of USMV which currently holds 208 large-cap stocks.
• This strategy, postulated in 2014, has produced from the end of Jun-2014 to end of Feb-2018 an annualized return of 16.1% versus 11.9% for USMV, and 11.5% for SPY.
• We have now changed the trading rules and ranking system which we believe will provide improved returns with low turnover in the future.

In this 2014 article we showed that better returns than those from the ETF could be obtained by applying a ranking system to the stock holding of USMV (the universe), and investing periodically only in the 12 highest ranked stocks, bought and sold according to certain rules.
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• The iM-Best10(VDIGX)-Trader periodically invests in the ten highest ranked stocks of VDIGX which currently holds 45 large-cap stocks.
• This strategy, postulated in 2014, has produced from end of Jun-2014 to end of Feb-2018 an annualized return of 17.7% versus 9.9% for VDIGX, and 11.5% for SPY.
• We have now changed the trading rules and ranking system which we believe will provide improved returns with low turnover in the future.

• As of Feb-24-2018 VFMO holds 637 Russell 3000 stocks, selected according to a rules-based screen for relatively strong recent performance and liquidity. They show a 1-year average return of 62%.
• Using similar screening criteria we selected a portfolio of 639 stocks on Feb-24-2018 which had a 1-year average return of 71%. It holds 501 stocks in common with VFMO.
• Similar screening rules selected 576 stocks on Feb-24-2017 which showed an average return of 105% over the preceding year, but 0% return over the following 6 months to Aug-24-2018.
• Vanguard’s easily replicated selection process appears to be greatly influenced by survivorship bias. It is unlikely that VFMO will show a higher return than MTUM or SPY in the future.

• Based on its historic trend, the stock market appears to be overvalued.
• The Shiller Cyclically Adjusted Price to Earnings Ratio P/E10 is at high level of 33.5 (and P/E5 of 28.0), and a market correction is possible.
• Similar conditions for the P/E5, and S&P-real’s position relative to the long-time trend, were observed only 3-times in the past: in 1937, 1998 and 2006.
• The historic trend suggests a total probable real loss of about 15% over the next two years.
• Analysts’ long-term forecasts of stock returns made 7 years ago appear to have been unrealistically low.

• The Cyclically Adjusted Price to Earnings Ratio (CAPE ratio) is at 32.1, a very high level which signals overvaluation of stocks and low forward returns, according to Shiller.
• This level was only exceeded twice in the last 136 years, in Sep-1929 and from Jul-1997 to Jul-2001, with market declines of 77% and 45% then recorded.
• The Moving Average CAPE Ratio Methodology used here references stock market valuation to a 35-year moving average of the Shiller CAPE ratio instead of the 1881-2017 long-term average.
• Based on the 35-year moving average methodology, historic market performance points towards continuing up-market conditions, possibly for a number of years.
• To avoid the bear market, exit stocks when the spread between the 5-month and 25-month moving averages of S&P-real becomes negative and simultaneously the CAPE-Cycle-ID score is 0 or -2.

• The founder of Vanguard, Jack Bogle, says that over the next decade a conservative portfolio of bonds will only return about 3% a year and stocks about 4% a year.
• However, returns can be improved with a dynamic asset-allocation strategy that adjusts stock- and bond-fund holdings in a retirement account according to market climate.
• The Vanguard LifeStrategy Moderate Growth Fund (VSMGX) holds static investments of 60% equity and 40% bond funds and is compared to our dynamic strategy model.
• Our iM-DMAC(60:40) model, designed for retirement saving and withdrawal management, holds identical assets as VSMGX in up-market conditions but switches to 100% bond funds during equity down-market periods.
• The result, the iM-DMAC(60:40) vastly outperforms VSMGX.

• The Cyclically Adjusted Price to Earnings Ratio (CAPE ratio) is at 30.2, a very high level which signals overvaluation of stocks and low forward returns, according to Shiller.
• This level was only exceeded twice in the last 136 years, from Aug-1929 to Sep-1929 and from Jun-1997 to Jan-2002, with market declines of 77% and 45% then recorded.
• The Moving Average CAPE Ratio Methodology used here references stock market valuation to a 35-year moving average of the Shiller CAPE ratio instead of the 1881-2017 long-term average.  
• Based on the 35-year moving average methodology, historic market performance points towards continuing up-market conditions, possibly for a number of years.
• To avoid the bear market, exit stocks when the spread between the 5-month and 25-month moving averages of S&P-real becomes negative and simultaneously the CAPE-Cycle-ID score is 0 or -2.

Shiller warns in his recent commentary The Coming Bear Market? :
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• This system holds three ETFs according to stock market climate.
• Typically, during good-equity markets it holds equity- and leveraged-equity ETFs SPY, SSO, and UPRO.
• During bad-equity markets it holds leveraged short equity, short equity, and gold-ETFs SDS, SH, and GLD.
• It never holds fixed income ETFs, so we don’t have to worry about rising rates.

The model was backtested on the on-line simulation platform Portfolio 123 which also provides extended price data for ETFs prior to their inception dates calculated from their proxies. Trading costs, including slippage, were assumed as 0.1% of the trade amounts using closing prices.
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• The “Anti-VIX” ETN ZIV is designed to increase in value when the volatility of the S&P 500 decreases, as measured by the prices of VIX futures contracts.
• The model buys ZIV only during up-markets when the VIX > 17 and rising, otherwise during up-markets it buys either QLD or DDM, or IEF when upmarket conditions are absent.
• A backtest of the model from Jan-2011 to Jul-2017 produced a high 60% annualized return with a maximum drawdown of -16% with only 41realized trades.

• The “Anti-VIX” ETF SVXY is designed to increase in value when the volatility of the S&P 500 decreases, as measured by the prices of VIX futures contracts.
• Extended data of SVXY, the ProShares Short VIX Short-Term Futures ETF, from Jan-2006 to the fund’s inception date was calculated from its proxy, the S&P 500 VIX Short-Term Futures Index.
• SVXY is intended for short-term use. Using the extended price data, a buy-and-hold strategy of the hypothetical SVXY resulted in a huge loss of over 90% from 2007 to 2009.
• The model buys SVXY only during up-markets when the VIX > 17 and rising, otherwise during up-markets it buys either QLD or DDM, or IEF when upmarket conditions are absent.
• A backtest of the model from Jan-2007 to Jul-2017 produced a high 70% annualized return with a maximum drawdown of -27% with only 76 realized trades.

• This Universe holds well capitalized companies with strong market positions, which pay good dividends, have price appreciation potential, and provide a degree of downside protection during bear markets.
• The Universe is reconstituted weekly, and consists of 20 large-cap stocks with Capital Strength type characteristics from the Russell 1000 Index.
• A backtest, without any buy- and sell-rules, from Jan-2000 to end of Jun-2017 showed a 10.0% annualized return with a maximum drawdown of -41.5%.
• A comparison with Vanguard’s large-cap ETFs older than 10 years shows that for periods 1-year and longer the Universe would have produced higher returns than any of the five ETFs.

• This system invests in well capitalized companies with strong market positions, which pay good dividends, have price appreciation potential, and provide a degree of downside protection during bear markets.
• The portfolio is quarterly rebalanced and reconstituted, and consists of six large-cap stocks with Capital Strength type characteristics from the Russell 1000 Index, typically held for at least one year.
• A backtest, from Jan-2000 to end of Jun-2017, showed a 17.7% annualized return with a maximum drawdown of -23.3% and a low average annual turnover of about 70%.
• A comparison with Vanguard’s large-cap ETFs older than 10 years shows that for all listed investment periods the Portfolio would have produced higher returns than any of the five ETFs.

• The Vanguard Dividend Growth Fund-VDIGX is closed to new investors. Want-to-be investors can possibly do better than the fund by investing only in a few positions of the fund’s holdings.
• The iM-Best10(VDIGX)-Trader relies on the expertise of the Vanguard’s advisors to make the primary stock selection. VDIGX currently holds 45 large-cap stocks from which the Trader periodically picks its stocks.
• The Trader invests in the ten highest ranked stocks of VDIGX. This strategy, postulated in 2014, has produced to Jun-2017 a 3-year return of more than double that of VDIGX.
• The 3-year performance of the Trader was 64.1% versus 28.4% for VDIGX, giving an excess return of 35.7%. Trading frequency was low, with positions held on average for 126 days.