Macro Trend Rotation

As of January 1, 2019, I am adding a new model portfolio to the publication. It is called Diamond-Zircon Rotation model portfolio. Over the last several months, many subscribers have shifted to Zircon from Diamond in response to my comments about the negative Macro (long-term) trend in stock prices. Both Diamond and Zircon are based on the same set of signals (which I call “D5”), but Diamond is more aggressive than Zircon; its gains and losses can be expected to be larger.

While the original intent of the Focused 15 Investing model portfolios was that each subscriber would select a model portfolio with a risk profile that is appropriate for their risk tolerance and time horizon, many subscribers have shifted model portfolios over time. This response from subscribers is perhaps inevitable. I have been open about the risks I see in the market and it is easy to rotate from one model portfolio to another. Given this usage of the publication, I sought to develop a more disciplined and robust way of rotating between Diamond and Zircon based on the larger market trends.

The Diamond-Zircon Rotation model portfolio uses a new signal, what I call the Macro Rotation Signal. To create the Macro Rotation Signal, I adapted a subset of the existing algorithms to focus on just the long-term price trend. By doing this, I was able to use algorithms that have been used real-time for about 10 years and have roughly 100 years of history.

The Macro Rotation Signal can be applied to various pairs of more aggressive and less aggressive model portfolios, like Diamond and Zircon. I am also reviewing the advantages of applying the Macro Rotation signal to Sapphire and Onyx (which consists of low volatility sector ETFs). 

The testing suggests that rotating between Diamond and Zircon can reduce weekly losses. Rotation provides the comfort factor of not using the aggressive ETFs (“DDM” in particular) in a negatively trending stock market.  It also enables a single model portfolio to have a wider range of risk exposures without having to trade a large number of ETFs. 

The result of this analysis is the Diamond-Zircon Rotation model portfolio (sg227). The individual existing Diamond and Zircon model portfolios have not changed and can still be used as before.

Now is a good time to introduce the Diamond-Zircon Rotation model portfolio because a key price trend measure (mentioned below) for the DJIA recently turned negative, which indicated that a shift to Zircon would be appropriate. I have spoken to subscribers to notify them about the availability of the Diamond-Zircon Rotation model portfolio.

For those following Diamond-Zircon Rotation, there may be some reduced return over the short-term should market prices begin a long-expected bear-market rally. Yet, the bottom of the current market cycle does not appear to be at hand and future market declines can be sufficiently large to justify the shift to the less-aggressive Zircon at this time.

The Diamond-Zircon Rotation model portfolio can be expected to produce slightly lower returns than Diamond over the long-term (by about 1.5 percentage points per year, annualized) but the variability of returns is also slightly lower. Again, a key advantage is reduced aggressiveness when the market is in a long-term vulnerable trend.

I tested the Macro Rotation Signal over three different time horizons. Because of data limitations, I could not do all tests over the longest time horizon. The first analysis covers 100 years of price history for the DJIA. This analysis focuses on the benefit of using the Macro Rotation Signals to move out of the market during times of vulnerability.

The Macro Rotation Signal is based primarily on two elements, a) the status on the Macro MRI, and b) the overall price trend of the DJIA using a technique similar to a widely used technical analysis tool called Moving Average Convergence Divergence (MACD). The MACD-related element is what turned negative over the last few weeks. The table below shows the performance statistics for the 100-year period for a simple model portfolio consisting of holding the DJIA in positively trending markets and holding cash in negatively trending markets.

These statistics are based on price change only; they do not include dividend return. Nor do they include any return for cash that might be held. The DJIA – Buy-and-Hold is the benchmark for this analysis; it is what would be achieved with no Macro Rotation.

(1918 – 2018)
Rate of Return (annualized, higher is better)
Variability (annualized standard deviation of weekly returns, lower is better)
Ratio of Rate of Return to Variability (higher is better)
DJIA – Buy-and-hold
DJIA using Macro Rotation Signal to get out of market and hold cash

Thus, the Macro Rotation Signal improves returns and reduces variability – both are positive changes. This result is seen in a higher Ratio of Rate of Return to Variability measure.

The average number of rotations per year is 1.8 over the 100 year period. Of course, these are not spread evenly over the period. Instead, they tend to be clustered. The figure below shows the DJIA price (log scale) in brown. The green line reflects the price change of our simplified rotation portfolio.

The better return for the simple model portfolio using the Macro Rotation Signal is based on identifying the negative trends in the market and avoiding losses. Subscribers may recognize this chart from the initial descriptions of the investment approach.

The following chart is of the same series but with a shorter time span, beginning November 1931, at the bottom of the stock market during the Great Depression. This time span highlights how Macro Rotation Signal works during different market environments.

The approach does best when there are market losses. It does not keep up with the buy-and-hold DJIA during strong trending markets, which are circled below.

Over this shortened time period, the following are the statistics for rate of Return / Return Variability (higher is better).

  • For the DJIA (buy and hold):       0.41
  • Using the Macro Rotation signal: 0.67

During the late stages of an ascending market the rotation signal produces a shallower slope than the buy and hold. This indicates that the Macro Rotation Signal reduces risk prematurely. Subscribers will recognize the tendency of the MRI-based approach to underperform in the late stages of an ascending market, which we see in the figure above. I adjust for this in the design of the model portfolios (e.g., Diamond, Zircon). The most challenging period marked “A” on the graph above.

The table below compares simulated returns for the Diamond-Zircon Rotation model portfolio to Diamond and Zircon over the period 1966 through the end of 2018, which includes period A indicated above. These simulations do not include dividend return or any return to the cash held in portfolios because of data limitations over this long time horizon.

1966 - 2018
Rate of Return (annualized, higher is better)
Variability (annualized standard deviation of weekly returns, lower is better)
Ratio of Rate of Return to Variability   (higher is better)
Simulated Diamond (D5 Signal Set using ETF “DDM”)
Simulated Diamond-Zircon Rotation
Simulated Zircon (D5 Signal Set using ETF “DIA”)
DJIA Buy-and-Hold

Zircon’s annualized rate of return is slightly higher than the DJIA Buy-and-hold, but the variability of returns is less than half. This boosts the ratio of return to variability to a high level.

One can see that the Diamond-Zircon Rotation model portfolio has much better performance than Zircon and slightly lower performance than Diamond. For many subscribers with longer time horizons, Diamond might be the right choice. Yet, for those with shorter time horizons or uncomfortable holding aggressive ETFs in negatively trending markets, the Diamond-Zircon Rotation portfolio might be the right choice.

On the three charts below, I show the Macro Rotation Signals for the period 1980 to the end of 2018. One can see the major tops and bottoms of the market, which are indicated. It is at these point that the Macro Rotation Signal adds value.

One can see from the figure some minor tops and bottoms. The Rotation signal is less likely to add value for these. This is particularly true during period A (from 1985 through 1994). Macro Rotation shows considerably greater effectiveness in the period of 2000 to 2018 than than during period of A. Going forward, we want to be prepared for many environments so it is important to consider the success of the approach during the difficult period A.

One can also see in the charts that some of the Macro Rotation shifts are clustered in time; a rotation in one direction is reversed just a few weeks later. To date, I have not identified how to reduce this clustering further without reducing returns.

Trading in the Diamond-Zircon Rotation portfolio is simple and, I believe, mitigates this issue. It holds only two ETFs, ETF “DIA” for the DJIA with no leverage. ETF “DDM” for the DJIA at two times leverage. It does not hold ETFs for long and short-term bonds. Instead, cash is simply help in one’s account. At this time, bond ETFs do not have high return so excluding them does not result in a big negative impact on returns.

As mentioned, I am reviewing applying the Macro Rotation Signal to other pairs of model portfolios. These might have superior performance characteristics while still being easy to implement.

Of course, subscribers are free to use any of the model portfolios. Please review the statistics and the various risks and select the model portfolio appropriate for you.


Is the Current Market Like 1987, 1998, or 2008?

The DJIA continues to be rated “most vulnerable” with a rating of “0.” The scale is 0 to 3, with 3 indicating “most resilient.”  The DJIA achieved the most vulnerable rating on November 30, 2018.  This rating indicates that the index would likely decline with negative news and would recover slowly.  Negative news of the day resulted in major price declines since the first of December. This post discusses where prices may go from here based on the status of CPM’s Market Resilience Indexes (MRI).   

The CPM Investing framework consists of three main MRI for each index (e.g. DJIA, US 10y Treasury).  The Macro MRI indicates the long-term trend in index price.  The peak of the Macro MRI coincides (generally) with the peak in index prices.  The Macro MRI indicates the pricing cycles of resilience lasting several quarters or years. 

The Exceptional Macro MRI indicates when the Macro MRI is nearing a bottom of its cycle and is therefore likely to turn positive.  The onset of the Exceptional Macro serves as the most sensitive indicator of the bottom of a market. 

The Micro MRI indicates the bursts of resilience lasting typically 6 to 24 weeks, depending on environment and asset class.  The Micro MRI cycles are most easily seen in the ups and downs of index prices throughout the year.

The MRI are additive.  When they move together, all moving higher, for example, they reinforce each other and prices tend to follow that direction.  When they move in opposition to each other, some moving up and some moving down, they tend to cancel each other out, and prices tend to be flat. 

To describe the current level of an MRI, we indicate its percentile level within all its weekly levels since the inception of the index.  For example, the DJIA has over 5200 weeks of history since 1918.  The current level is described as the 10th percentile in its historical range.  From that reading, we can see that its level is toward the lowest level of its historical range.  If the level is currently moving down, we can guess that it will not move down much further.  When it is at or near the 1st percentile, it is at the very lowest level of its historical range.  Since the levels are mean reverting, we generally expect the MRI to shift to the positive leg of the cycle and move higher.  This cycle is relatively consistent over time. 

When the Macro and Micro MRI are moving higher (in the positive legs of their cycles), we say they are present and providing resilience.  If the Exceptional Macro is also present, the index has a rating of 3; all three MRI are providing resilience.  When bad news occurs, it may drive prices down.  But the strong resilience of the market will generally cause prices to recover quickly. 

When none are moving higher, the market has a rating of 0.  During these periods, bad news produces bigger declines and slow and incomplete recoveries. 

The MRI levels and directions at a given time for different asset classes can help us position portfolios to favor the asset classes (e.g. stock, bonds, and cash) most likely to be resilient and to avoid those most likely to be vulnerable. For professional investors, this information can add a timeliness element to their existing investment activities.

With its current rating of 0, the DJIA has little ability to shake off bad news.  That said, the Micro MRI (the shortest cycle) is at a low level (10th percentile since 1918) and is therefore poised to turn positive.  This implies the market is likely to soon display short-term resilience that could move the DJIA price higher from its current level.  An absence of bad news or a positive catalyst is often needed to initiate an up-leg of the Micro MRI cycle. 

Yet, when only the Micro is providing resilience, the index price will generally move higher only briefly.  Based on general market behavior over the last 100 years, for this brief move higher to be the beginning of a long-term trend higher, one or both of two conditions would need to be true.  First, the Exceptional Macro would need to be present.  It is not close to being present for the DJIA. Second, the Macro MRI itself would need to turn positive without the advanced warning made by the Exceptional Macro.  This is not likely to happen for the DJIA over the next several weeks.  Thus, I believe the bottom of the US Stock market is likely to be several months away. 

Other MRI-related observations about the current environment:

  • US 10y Treasury Future – It is currently rated 2 (somewhat resilient), with its Micro and Exceptional Macro being positive.  The Macro (long-term) MRI is at the 3rd percentile – a very low level – in the historical range established since 1983 and is close to moving into its up-leg. The important Exceptional Macro is positive and thus foreshadows a shift to a positive Macro MRI.  When the Macro MRI does turn positive, it would signal the bond prices are resilient and likely to move higher.
  • Dollar Index (DXY) – new rating of 1 (somewhat vulnerable to declines) last week, down from a rating of 3 the week before.  This is a rapid shift toward greater vulnerability and suggests a weaker dollar over the next several weeks. 
  • US 2y Yield – shifted to a rating of 0 (most vulnerable to declines) on 11/30/2018.  The Macro MRI abruptly turned negative on that date, having been at the 100th percentile (since 1976), obviously an extremely high level.   In contrast, the Micro MRI is at a very low level for this series – corresponding to the 2nd percentile over the same time period. While the Micro MRI is likely to become positive in the next few weeks and provide temporary support for the 2-year yield level, at the moment, the longer-term (Macro) trend for the 2-year is for lower yields. 
  • US 10y Yield – shifted to a rating of 0 (most vulnerable to declines) last Friday.  The Macro MRI abruptly turned negative last week (12/14/2018).  While the Micro is at a low level and will likely soon turn positive, it will then be rated only a 1, “somewhat vulnerable to declines.”
  • The following stock market indexes have ratings of 0 (most vulnerable to decline): UK Stocks, Europe stocks, Japan stocks, Emerging market stocks (MXEF), Shanghai Composite. Many of these have Micro MRI that are toward the lower ends of their historical ranges and could begin to experience a bear-market rally.  Yet, the Macro MRI is clearly moving in a negative direction from historically high levels, reinforcing the view that these rallies will be brief.  The Exceptional Macro is not close to being present for any of these indexes.  The exception to this generalization is that the Shanghai Composite seems a bit closer than the others to shifting to a more positive long-term trend.  Thus, the mid-term outlook for global stocks is quite negative.
  • Regarding inflation concerns, the relative leadership of global inflation-linked bonds vs. global nominal bonds had called for inflation-linked bonds to be favored (with a rating of 3, most resilient) as recently as November 23, 2018.  Now, inflation-linked bonds are less resilient than nominal bonds (the relative leadership series is rated 1, meaning avoid inflation-linked bonds and favor nominal bonds).  By this measure, a deterioration in inflation expectations has happened quickly. 

Many of these changes have occurred quickly compared to their historical norms.  This may be an additional negative sign for stock markets in general.  Recent negative news has come at a particularly vulnerable time and has sent prices lower. 

Thus, stock prices globally are likely to remain “most vulnerable to declines,” with a rating of 0, or “somewhat vulnerable to declines,” with a rating of 1, for several months.  If general historical precedents based on 100 years of history for the DJIA hold true for the current mix of MRI, any rally driven by a positive Micro MRI will be quickly followed by lower lows. 

While this is the most common scenario (identified as scenario #1 below), there are two scenarios in which the market has begun a long-term trend higher from a configuration of MRI levels and directions much like those we are now experiencing.   All three of these scenarios have levels and directions of MRI like the current state for the DJIA.

Scenario #1 – The upcoming bear-market rally would move prices higher but not establish new highs.  This would be followed by dramatically lower lows.  The recent declines would be seen as an indicator of coming slower economic growth (the market has been signaling peak earnings for the last eleven months). The bear-market rally would be like the one that began in February of 2008.  During February 2008 and now, the market had been sending signals of peak earnings (lower PER but higher PBR measures).  In the earlier period, the market ultimately bottomed quite a bit lower in March of 2009.  We may not experience the same degree of loss as that was experienced in the 2008-2009 period, but following the bear-market rally there could be another decline as the market adjusts gradually over several months to lower growth rates.  

Scenario #2 – The upcoming bear-market rally is absent or muted but a longer-term positive price trend follows.  The recent declines would ultimately be seen as a rapid, large-scale adjustment of valuations similar to the price declines of October 1987.  There was not a strong rally (bear or otherwise) after the October 1987 decline but the decline did not foreshadow further deterioration in the real economy.  Economic growth was strong pre-October-1987 just as it is now.  In this scenario, the negative news catalysts for the price change (trade tensions, threats to Fed Independence, and general Washington chaos) might have the effect of bringing forward in time an adjustment for lower economic growth that would otherwise play out over a longer period (as in scenario #1). 

Scenario #3 – A fast recovery to price levels higher than what has been recently experienced.  The recent declines would be seen as being driven by unfortunately-timed news-of-the-day events. This would be like the decline ending in August of 1998 related to the Long-Term Capital Management crisis, which was then quickly resolved.  But the DJIA price trend was much stronger in 1998 than it is today.  Economic growth was strong in 1998 just as it is now. 

Scenario #1 has the bleakest mid-term outlook. Scenarios #2 and #3 are more positive. For all three, an appearance of the Exceptional Macro, or a new positiver trend in the Macro MRI (within being foreshadowed by the appearance of the Exceptional Macro) will indicate subsequent market action. I will provide update on these scenarios over the next several weeks.

In the meantime, CPM research indicates that the prudent positioning of a multi-asset portfolio is to favor bonds and cash.  Avoid stocks.  The recent sharp declines may not have ended yet.  The algorithms for our more active portfolios will likely attempt to take advantage of any bear-market rally.  The algorithms for our less active portfolios are more likely to sit out the bear-market rally.  

Please contact CPM Investing with any questions or comments.    


Performance Review - Four Years ending July 20, 2018

Last week marked four years since the start of the Focused 15 Investing publication.  This report provides information about how the investment approach has worked over this period.  This report discusses the performance of two model portfolios for the 4-year period ending July 20, 2018 and compares them to various reference points.  An appendix also shows results for all portfolios currently listed in Focused 15 Investing publications.  

The two model portfolios are:
  1. Diamond (sg131), which is the most widely used model portfolio. It holds three ETFs. The signal set that drives Diamond, which I call “D5”, is the primary loss-avoiding component used in all model portfolios. It is designed to provide high absolute returns and avoid losses. 
  2. “US Ind, LC/SC, Multi-Sector Bonds” (sg129). It holds eight ETFs and places greater emphasis on maintaining its performance advantage in upward trending markets. It includes the D5 signal set but also includes relative leadership sleeves for 1) large company (LC) vs. small company (SC) stocks, and 2) various bond sectors. Loss avoidance is not its primary goal. Portfolio sg129 was in the original publications 4 years ago. It is in the publication for institutional investors, which focuses on model portfolios aiming to provide strong returns relative to a benchmark.
The longer-term performance highlights the impacts of the design differences. The table below shows performance[1] characteristics since January 7, 2000.

Annualized Return
Maximum Drawdown[3]

Higher is better
Lower is better
Smaller loss is better
Diamond (sg131)

As one can see in the table above, Diamond has a much higher return than sg129 (25.4 % vs. 15.1%).  At the same time, sg129 had a loss (maximum drawdown) just about as great as Diamond’s.    

Before discussing the performance of these model portfolios over the last four years, I’ll review the market environment. 

 Market Environment

The recent four-year period has seen above average rates of return and below average return variability compared to the last roughly 100 years of the DJIA.  The chart below shows the Price of the DJIA (brown line) on the left-hand scale (log). 

The chart also shows the percentile rank of the rolling 4-year returns for the DJIA (green) across the 100-year period and the percentile rank of the variability of the 4-year returns (yellow), both on the right-hand scale (the horizontal black line is at the 50th percentile on the right-hand scale ranging from 0.00 to 1.00).  The rightmost point of the green line indicates that the 4-year return for the DJIA is at the 64th percentile – a moderately high return.  The rightmost point on the yellow line indicates that the variability of returns is at the 33rd percentile a moderately low level of variability. 

                                                Source:  Bloomberg LLC and CPM Investing LLC

Generally speaking, Diamond produces better returns than its default when the market’s variability (yellow line) is high.  Portfolio sg129 is designed to do better when the market’s returns (green) are high.  This information indicates that the environment was more favorable to model portfolio sg129 than to Diamond.  Diamond has just three ETFs and is designed to avoid losses during periods of high return variability. 

In contrast, model portfolio sg129 (eight ETFs) is designed to outperform its default in positively trending markets, such as what we have experienced the last 4 years.  That said, the absolute return of Diamond is higher, making it attractive to end users in many environments. 

Traded Portfolios Compared to their Defaults

The chart below shows the performance of Diamond and its default.  The blue line represents the performance of using the dynamic target weights in the weekly publication.  The tan line indicates the performance of the same ETFs held at default weights over time.  As indicated in the material describing the Focused 15 Investing approach, the traded portfolio (blue line) can underperform its default (tan line) in the later stages of an upward trending market.  We can see this below in the narrowing of the gap between the traded and default over time. In a strong upward trending market, the line for the traded model (blue) could even pass behind the line for the default (tan).   

 The table below shows performance statistics for this period.  The traded portfolio returned 18.8% (annualized) over the four-year period.  The default returned slightly less, at 18.4%.  

The traded portfolio had less volatility (13.2% vs. 17.2% for the default).  As a result, the traded portfolio had a ratio of return-to-variability (RoR/Var) of 1.42 compared to 1.07 for the default. The value 1.42 is good for the RoR/Var ratio (see section “Funds in Bloomberg with High Return-to-Variability Ratios” for more information about interpreting this statistic).

The graph below shows the same information for sg129.  As it was designed to do, the traded portfolio maintained its performance relative to the default in the later stages of the recent ascending market.  

The table below shows that the traded portfolio had higher returns (12.0% vs. 10.2%, annualized) and lower variability (9.0% vs. 11.5%, annualized) relative to its default.  Correspondingly, the RoR/Var compares favorably at 1.32 vs. 0.89 for the default.  Also, the traded portfolio had a smaller maximum drawdown over this period (down 7% vs. down 13%). 

Traded Portfolios Compared to Select Retirement-Focused Funds

This section shows the return of these two model portfolios compared to two alternatives, which I selected as comparisons years ago based on what one might obtain in a company-sponsored retirement plan.  The two retirement-oriented plans are:
  • VBINX - Vanguard’s ETF with a 60% stock and 40% bond mix (Vanguard 60/40)
  • Russell LifePoints Growth Fund, designated as “RLP – Growth” below. This fund is the most aggressive of the LifePoints funds
The chart below shows Diamond compared to these two funds: 

These funds are more conservative than Diamond; the returns are not as high.  But it is important to note that the RoR/Var ratio for Diamond is higher than for any of the others.  This means that Diamond provides higher returns for the level of variability that must be endured.  Also note that the maximum drawdowns over this period for Diamond and the Russell LifePoints were about the same (down 16%).

The chart below compares these two alternatives (VBINX and RLP-Growth) to sg129.

The variability of sg129 (9.0%, annualized) is less than that of the Russell LifePoints’ (9.2%), but sg129’s return is quite a bit higher (12.0% vs. 4.4%, annualized).  The RoR/Var ratio for sg129 (1.32) is higher than all others. 

Funds in Bloomberg With Returns Similar to Diamond’s

For an additional comparison of Diamond’s return, I searched Bloomberg’s database to find all US-focused mutual funds (including ETFs) that had similar annualized rates of returns (roughly 18-20%) over the same four-year period.

The table below shows that, on average, these 11 funds had a return of 18.9%, which coincidentally matches Diamond’s return for the period. The average variability of the group is 26.8%, which is
more than double Diamond’s 13.2%.

Some of Diamond’s low variability is because of its diversified nature – it holds an allocation to bonds. I had hoped this search of Bloomberg data would have surfaced aggressive balanced funds (holding both stocks and bonds) that may be more directly comparable to Diamond. None were found, and I confirmed this with Bloomberg. It appears that those funds don’t exist in Bloomberg.

Diamond’s RoR/Var ratio is high compared to the average for these investments (1.4 vs. 0.72). 

The ETF DDM, which is the main ETF in Diamond just misses being on this list.  It returned 22.8% (annualized) over this period.  Its variability was 24.9%, which gives it a ratio of 0.92. 

Funds in Bloomberg With High Return-to-Variability Ratios

In order to evaluate the four-year RoR/Var ratios of the two Focused 15 Investing portfolios, I estimated a corresponding statistic based on data available in the Bloomberg databases. I filtered for funds with a North American focus, in US dollars, that are domiciled in the US. In Bloomberg, “funds” include mutual funds, closed-end funds, ETFs, and a range of other fund types. The result was 8,507 funds.

Bloomberg statistics are slightly different than the ones I use[4]. Bloomberg provides three-year and five-year statistics, but not four-year. I estimated the four-year statistics as the average of the three-year and five-year statistics.

The table below shows sections A and B. A shows the percentage of the 8,507 funds estimated to be in the range indicated for RoR/Var, “1.1 to 1.2” for example. B shows the percentage exceeding a certain level, “Higher than 1.2”, for example.

Based on these reference points, Diamond’s RoR/Var ratio of 1.42 and sg129’s of 1.32 place them among the upper 3% and 6%, respectively, of the pool of 8,000+ funds tracked by Bloomberg.

Morningstar ETF Managed Portfolios – Three-Year Return through 12/29/2017

I also compared Diamond and sg129 to funds tracked by Morningstar that are in the class they call “ETF Managed Portfolios.” Like the Focused 15 Investing portfolios, these funds consist of multiple ETFs. Morningstar indicates that they ignore whether the ETFs are leveraged.

Morningstar produces a report showing performance, but the most recent report available is for fourth quarter 2017. The overlapping period with the Focused 15 Investing portfolios is the three years ending that date (12/29/2017).

In the report, Morningstar tracks 1,180 ETF-based funds across a range of different attributes and classifications, shown below.

Of those with a three-year history (the report does not say how many have that length of history), the top 10 performers across all classifications listed above have annualized returns ranging from 11.34% to 17.92%.

Over the same three-year period, Diamond returned 21.0%, and sg129 returned 12.8%. If I reduce these returns by, say, 1.5% for fees, we get Diamond at 19.5%, and sg129 at 11.3% – figures that still place them among the top ten performing funds shown below.

The table below shows the top ten funds in the Morningstar report. (The bottom-performing ones referred to in the title of Exhibit 6 are not relevant and therefore are not shown.)


While the US stock market, as measured by the Dow Jones Industrial Average, has seen strong returns and low variability over the last four years, Focused 15 Investing’s model portfolios have demonstrated better performance characteristics than their default mixes. 

The performance of both Diamond and sg129 over this period has been consistent with their designs. Diamond is designed to avoid losses and have high absolute returns rather than to outperform its default in an upward trending market. While Diamond had strong absolute returns for the period, it had a rate of return similar to its default mix, but with less variability. On the other hand, sg129 is designed to maintain its outperformance during upward trending markets.  This was reflected in the portfolio’s performance; while sg129 had lower absolute returns, it showed better performance relative to its default mix.

The two Focused 15 Investing portfolios have also performed better than select retirement-oriented funds. This is indicated in the comparison to Vanguard’s VBINX and Russell’s LifePoints Growth funds. 

While obtaining directly comparable performance information for a large number of funds is difficult, the data available from Bloomberg and Morningstar suggest that the Focused 15 Investing model portfolios are among the strong performers over the last four years.  


Appendix: Appendix: Model Portfolio Performance by Focused 15 Investing Publication

The following section shows performance statistics for the current roster of model portfolios by publication.  The publications are:
  1. The main US Dollar (USD) publication. 
  2. Institutional Investors. These model portfolios tend to have a higher number of ETFs and emphasize performing well relative to their default mixes. Please note: Model portfolio sg99 was in the original publication along with sg129. Portfolio sg99 is designed for low variability and to have fewer ETFs than sg129. 
  3. Investors in Australia. These portfolios focus on improving the RoR/Var ratio and keeping trading frequency low.
  4. Investors in Japan.

1. Focused 15 Investing - USD

Model Portfolio Performance Since 7/18/2014 as of 7/20/2018

Diamond - 3 ETFs (sg131)
           Ann RoR    Ann Var    RoR/Var
Traded       18.7      13.2       1.4
Default      18.4      17.2       1.1

Sapphire - 1 ETF (sg147)
           Ann RoR    Ann Var    RoR/Var
Traded       23.1      17.1       1.3
Default      23.0      22.6       1.0

Emerald - 2 ETFs (sg148)
           Ann RoR    Ann Var    RoR/Var
Traded       21.5      15.8       1.4
Default      20.4      20.0       1.0

Ultra Diamond - 3 ETFs (sg174)
           Ann RoR    Ann Var    RoR/Var
Traded       26.4      18.7       1.4
Default      25.4      25.1       1.0

Diamond-Onyx - 5 ETFs (sg176)
           Ann RoR    Ann Var    RoR/Var
Traded       12.7       8.2       1.5
Default      12.4      10.9       1.1

Mosaic - 8 ETFs (sg213)
           Ann RoR    Ann Var    RoR/Var
Traded       11.0       9.7       1.1
Default       6.0      13.6       0.4

2. Focused 15 Investing - Inst'l Pro USD

Model Portfolio Performance Since 7/18/2014 as of 7/20/2018

US Ind, LC/SC, MS Bonds - 8 ETFs (sg129)
           Ann RoR    Ann Var    RoR/Var
Traded       11.9       9.0       1.3
Default      10.2      11.5       0.9

US Ind, US Ind/Trans, MS Bonds - 7 ETFs (sg99)
           Ann RoR    Ann Var    RoR/Var
Traded        6.4       6.2       1.0
Default       8.2       9.9       0.8

DJIA x2, US Ind/Trans - 5 ETFs (sg150)
           Ann RoR    Ann Var    RoR/Var
Traded        9.7       7.4       1.3
Default      11.3      11.3       1.0

DJIA x2, EME/B, Com, L Vol Sctrs - 8 ETFs (sg113)
           Ann RoR    Ann Var    RoR/Var
Traded       13.0       9.0       1.4
Default      10.5      12.9       0.8

DJIA, EM E/B, LC/SC, MS Bonds - 10 ETFs (sg122)
           Ann RoR    Ann Var    RoR/Var
Traded       10.4       7.2       1.4
Default       8.0       8.9       0.9

DJIA x2, LC vs SC, Onyx - 7 ETFs (sg204)
           Ann RoR    Ann Var    RoR/Var
Traded       16.3      10.7       1.5
Default      14.6      13.9       1.1

Simulated performance since the inception of the newsletter July 18, 2014

3. Focused 15 Investing - Professional AUD

Model Portfolio Performance Since 7/18/2014 as of 7/20/2018

IEM, IVV - 4 ETFs (sg98)
           Ann RoR    Ann Var    RoR/Var
Traded       10.5       7.2       1.4
Default      10.4      10.2       1.0

IEM, IVV, VLC/VSO - 6 ETFs (sg172)
           Ann RoR    Ann Var    RoR/Var
Traded       10.7       7.7       1.4
Default      11.3      10.5       1.1

MXAU, IVV, VLC/VSO - 5 ETFs (sg71)
           Ann RoR    Ann Var    RoR/Var
Traded        3.7       6.1       0.6
Default       5.5       9.3       0.6

MXAU, VLC/VSO, EM E/B - 8 ETFs (sg183)
           Ann RoR    Ann Var    RoR/Var
Traded        6.5       6.9       1.0
Default       7.0       9.5       0.7

VLC/VSO, EM E/B - 5 ETFs (sg187)
           Ann RoR    Ann Var    RoR/Var
Traded       10.7       8.4       1.3
Default       9.2       9.0       1.0

Currencies - 3 ETFs (sg184)
           Ann RoR    Ann Var    RoR/Var
Traded        1.1       4.2       0.3
Default      -3.8       9.3      -0.4

Simulated performance since the inception of the newsletter July 18, 2014

4. Focused 15 Investing - Professional JPY

Model Portfolio Performance Since 7/18/2014

Diamond JPY - 4 ETFs (sg185)
           Ann RoR    Ann Var    RoR/Var
Traded       22.1      17.3       1.3
Default      18.1      23.0       0.8

Emerald Impact - 3 ETFs (sg186)
           Ann RoR    Ann Var    RoR/Var
Traded       23.3      20.7       1.1
Default      20.4      26.7       0.8

Simulated performance since the inception of the newsletter July 18, 2014

[1] All performance figures for Focused 15 Investing model portfolios are based on returns of the indexes that the ETFs track and the weekly target weights for the ETFs.  The performance figures do not reflect costs and fees, such as fees collected by the ETF providers, trading costs for implementing the model portfolio in accounts, and fees for the Focused 15 Investing publication. 

[2] Annualized standard deviation of weekly returns. 

[3] Maximum Drawdown indicates the greatest loss over the time period indicated.  It is determined by finding the greatest gap between a high price level and the next subsequent low-price level.

[4] I use weekly return data to create a simple ratio of annualized return to annualized standard deviation of returns.  Bloomberg reports annualized monthly statistics and reports only 3y and 5y Sharpe Ratios.  I do not subtract the risk-free rate in my calculations, a difference that is less meaningful during the current period of low short-term rates.