The backtest reported in this article showed that ranking the holdings of USMV, the iShares MSCI USA Minimum Volatility ETF, and selecting a portfolio of the 12 top ranked stocks, provided higher returns for the buy&hold portfolio than for the underlying ETF. To test these findings out-of-sample we launched the Best12(USMV)-July-2014on Jun-30-2014 and the first sister model Best12(USMV)-Oct-2014 on Sep-29-2014. Holdings and performance have been published weekly on our website since then. So far to Dec-15-2014 these portfolios have gained 19.2% (6.8%) and 10.5% (5.3%), respectively. (USMV gains are in brackets.) The test will be expanded by the launch on Jan-5-2015 of the second of the three sister models quarterly displaced, the Best12(USMV)-Jan-2015, which again will consist of the 12 highest ranked stocks of the then point-in-time holdings of USMV.
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We have shown that higher retirement savings are possible with our iM(MAC-Vang) and iM(MAC-CREF) models that dynamically adjust bond/stock asset allocation using Vanguard or TIAA-CREF Funds respectively. We make use of the MAC-system to determine the allocation switch points depending on market trends. The backtest of the MAC-system stretches back almost 65 years. We are also proponents that market models should have a minimum number of variables to avoid over-optimization and possible future model breakdown. The MAC-system is such a minimized system and its robustness has been confirmed by an independent party.
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Trading the Dividend Growth Stocks of the Vanguard Dividend Growth Fund: Simulated Performance of iM’s Best10(VDIGX)
Ranking the holdings of the Vanguard Dividend Growth Fund VDIGX and selecting a portfolio of the highest ten ranked stocks provided much higher returns for the portfolio than for the underlying fund. A simulation over the time period (6/30/14 to 12/8/14) which selects periodically the 10 highest ranked stocks shows a 15.3% return while VDIGX gained 7.0%.
A previous study found that a dynamic asset allocation strategy with Vanguard index funds produced better returns than models with static asset allocations. Changing asset allocation according to stock-market climate produced much higher returns with less risk. TIAA-CREF’s variable annuity accounts can similarly be used to improve returns for participants. Results for three models with dynamic asset allocation are provided whose performance and risk measurements are all better than those of the variable annuity accounts alone, or static combinations of those accounts.
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For what is considered to be a lagging indicator of the economy, the unemployment rate provides surprisingly good signals for the beginnings and ends of recessions. We have developed a model that uses unemployment figures to produce these signals and to determine the probability of when a recession may start. We conclude, based on the historic evidence of our unemployment-derived indicators, that there will be no recession in the near future.
Since end of June 2014 we provided updates of our Best12(USMV) at iM, a tax efficient model which holds positions normally for at least one year. Concurrently we were testing the Best12(USMV)-Trader model. The only difference between the two models is that the Trader is not restricted to hold stocks for a 1-year minimum period and has an additional sell rule based on rank. We backtested the Trader for various periods and found its returns to be to be marginally higher than that of the tax efficient Best12(USMV) model. However, returns were more consistent.
Three months ago we introduced the iM-Best12(USMV) model, which still holds the then twelve best ranked stocks selected from the holdings of USMV, the iShares MSCI USA Minimum Volatility ETF. So far this portfolio has gained 8.2%, while USMV is up a mere 2.2%, confirming the results of the backtest performed over a relative short period. The out-of-sample test will be expanded by the launch of the second of three sister models quarterly displaced, the Best12(USMV)-Oct-2014, which again will consist of the 12 highest ranked stocks of the then point-in-time holdings of USMV.
Vanguard Funds With Dynamic Asset Allocation: Which is the Asset Allocation “that’s right for your situation”?
Performance and risk measures are given for six iM(MAC-Vang) models with various asset allocations which use a combination of Vanguard bond- and stock-funds, and switch assets according to stock-market climate.
In continuation of our previous article “How Good are Vanguard’s LifeStrategy Funds? Much Better Returns From Vanguard Funds with iM’s (MAC-Vang)20/80” we show that exceptionally high returns can be obtained from Vanguard funds, when a dynamic asset allocation strategy is employed, and actively managed funds instead of index funds are used. Using a combination of bond-, stock-, and sector-funds in the model, and switching asset allocation according to stock-market climate, provided an annualized average return of over 15% for the backtest period Jan-2000 to Jul-2014.
How Good are Vanguard’s LifeStrategy Funds? Much Better Returns From Vanguard Funds with iM’s (MAC-Vang)20/80
“Studies have shown that your asset allocation has a bigger impact on your long-term returns than any specific fund you pick. So why not pick a Vanguard LifeStrategy Fund that has asset allocation built in?” This is the opening statement on a Vanguard web-page, which also lists other potential benefits of investing in such a fund. The historic performance of the LifeStrategy Moderate Growth Fund was analyzed from Jan-2000 onward, and it is very clear from the analysis that this was a high risk investment with low returns. An alternative investment model with Vanguard funds is proposed which would have produced much higher returns with less risk.
iM’s Improved Floor-Leverage Rule with Put Option Insurance: A Low-Risk Investment Strategy with a 5.7% Safe Withdrawal Rate
iM’s Improved Floor-Leverage Rule, a low-risk investment strategy for retirement with a high 5.7% withdrawal rate, uses market timing to avoid large losses of the Surplus Portfolio, and additionally uses a strategy to guard the Surplus Portfolio against black swan events, e.g. the 1987 stock market crash, by buying put options.
The original Floor-Leverage Rule for Retirement, as proposed by Scott and Watson, calls for two parallel investments. The first one is to establish a low risk Spending Floor Portfolio with 85% of one’s funds. The second, the Surplus Portfolio, is an investment of the remaining 15% in equities with 3× leverage. If the Surplus Portfolio exceeds 15% of the total portfolio value at annual rebalancing when withdrawals are made, it is adjusted to 15% of the total portfolio value with the excess being transferred to the Spending Floor Portfolio. The problem is that 3× leveraged stock portfolios can lose most of their value. For example, they lost 94% from 2000 to 2008, which would have wiped out almost 15% of retirement capital if one had followed the Original Floor-Leverage Rule. A better approach, and one that could avoid such losses, is to time one’s exposure to equities as put forward by our Improved Floor-Leverage Rule, which is a low-risk spending and investment strategy for retirees.
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About two years ago evidence was presented that a major bull market may have commenced in 2009. Additionally, a statistical analysis of the historic data of the S&P Composite presented in an Aug-2012 article and Jan-2014 update thereto supported this finding. Since August 2012 the S&P500 has now gained a real 40% to the end of June 2014. So what further gains can we expect, if any?
Minimum volatility ETFs should provide exposure to stocks with potentially less risk. They track indexes that try to capture the broad equity market with a reduced amount of volatility, seeking to benefit from what is known as low-volatility anomaly. Consequently they should show reduced losses during declining markets, but also reduced gains during rising markets. However, better returns with simultaneous tax efficiency can be obtained also during rising markets by selecting a number of the highest ranked stocks of a minimum volatility ETF and holding those positions for at least one year before new trades are initiated.
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Most of us entrust our savings to financial organizations in the belief that this will provide us with better investment results than we could have achieved ourselves. These companies advocate a buy-and-hold strategy of bond- and stock funds, charge fees, and usually perform poorly. A convenient way to improve on buy-and-hold and to do better than financial organizations is to periodically switch one’s investment from stocks to bonds and vice versa as indicated by the Moving Average Crossover MAC-system.
Demonstrating the effect of hedging by using various percentages of the long portfolio value. The simulation is for the period Jan-2-2000 to April-1-2014.
This model is intended to be used hedging long market exposure, not as a stand-alone model. It periodically holds a maximum of 5 short positions of large-cap stocks. The model was backtested from Jan-2-2000 to May-4-2014 on the Portfolio123 simulation platform as a stand-alone-model and would have provided an annualized average return of 26.5% with a max drawdown of -22.7% over this period.
This model uses the signals from the iM-Best(SPY-SH) Market Timing System, substituting the Canadian ETF XIU for SPY and switches between XIU and Cash instead of SH. XIU tracks the S&P/TSX 60 Index and currency is Canadian Dollar.
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The TIAA Real Estate Account, despite showing good returns over the last four years, is a typical example of a fund with disappointing performance over the longer term. In order to maximize one’s returns one has to know when to enter and exit the fund. My analysis shows that TIAA Real Estate may peak in the second half of 2014 which would provide an early indication to reduce one’s exposure. A firm sell signal would arise when its 1-year rolling return moves below 0%.
The modified Coppock indicator will produce a buy signal for Gold within a few weeks. This is the result of various projections using random numbers between -$20 and +$30 and -$30 and +$20 for the weekly change of the gold price, representing upward- and downward trends for the metal’s price, respectively.
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