Market Map: Staying the Course for the Long Term

As the stock market performs it’s weekly and monthly gymnastics, we can wait patiently for the next tactical allocation shift, and thus, do other things with our time. In order to not become distracted with the market’s behavior and stay focussed on long term asset allocation, we can review 90 years of Market Map model data to discipline our reflexive brain circuitry. We have no need for technical “chart pattern” analysis, economists’/analysts’/TV personalities’ opinions, the Wall Street Journal, etc. We just rely on the body of evidence from our statistical analysis thereby using reliable components and prepare ourselves beforehand with predetermined dates on which to take action.

In chart 1 of the previous article, were presented the statistcal outcomes of various investing time frames using buy & hold. In viewing four 20 year periods and the most recent 10 year period of the Market Map model (below), we can see that the model did indeed provide positive outcomes.

Chart 1

1924 – 1943

Model vs. SP500 1924 -1943

Chart 2

1944 – 1963

Model vs. SP500  1944 - 1963

Chart 3

1964 – 1983

ScreenHunter_70 Apr. 21 17.10

Chart 4

1984 – 2003

Model vs. SP500 1983 - 2003

Chart 5

2004 – 2013

Model vs. SP500  2004 - 2013

Chart 6

Model using Nasdaq 100/QQQ and S&P500

Model NDX  SPX  25 yrs  1989 - 2013

Viewing returns from a different perspective, chart 7 below shows rolling 20 year returns of the 3 data series. The 20 year CGRs of Nasdaq 100 and S&P500 using the model have been trending up:

Chart 7

20 yr GAGR

Neutral Risk Profile study

As 2014 was identified as a “neutral risk profile” year in the January 22nd post, in order to get a sense of the signature of past neutral risk years, the chart below reveals the historical neutral years return distribution for the S&P500 buy&hold with the corresponding model returns included. The distribution is relatively even (there are equally large gains on the left compared to the losses on the right). The cumulative return for the Model outperformed the S&P500 as the model tends to capture profitable points during the year when applicable. Over the long term, the allocation may have been in cash when the market was going up and, conversely, going down. We just go with the flow.

Chart 8

Neutral trend years

Asset allocation since 1/17/14 = cash
Probability of allocation to TLT (iShares 20+ Year Treasury Bond ETF) on 7/O9/14 = 5O%
Probability of allocation to QQQ / SPY on 1O/O3/14 = 1OO%


Market Map: Portfolio Diversification with Dividend Growth and Small Cap Value

In past articles, we have favored the use of the Powershares QQQ Trust ETF (QQQ) over small cap value weighted methodology for use with the Market Map model because of QQQ’s ultra low expense ratios, tax ratios, and accompanying comparable performance. The model and QQQ has also held a performance advantage, historically, over the SPDR Trust ETF (SPY), and Vanguard Total market ETF (VTI).
In this article, we explore portfolio “diversification” using: 1) a portfolio of popular dividend growth stocks 2) the “growth” universe (the QQQ etf) and 3) a “small cap value” universe (the Vanguard Small Cap value ETF (VBR)). As many investors find psychological comfort and safety by the “mere exposure effect” of owning a portfolio of “great” U.S. company names with growing dividend streams, they tend to shy away from exposure to the growth stock and small cap value universes because of perceived risk. Yet, for the population of middle and upper aged investors that have gotten a late start in their retirement asset accumulation phase, a compound “total return” from a strict dividend growth portfolio or the buy and hold of low cost total market fund(s) or S&P500 index fund(s) may be too little, too late in helping them meet their goals. Portfolios consisting of growth and small cap value etfs combined with the Market Map asset allocation models diversified with a buy & hold/annually rebalanced portfolio of quality dividend growth stocks (with the possible eventual goal of, as preferred by many, a total dividend paying/income producing portfolio), is a reasonable approach in alleviating the reluctance of investing in the growth and small cap equity universes while exposure to those universes can serve as the “faster turtles” in the “long term” accumulation phase of the assets.

In order to build a resolute belief in the “long term” view, we rely on data driven methods as defense against the “noise” of the financial markets and the anecdotal information presented by the media. Chart 1, prepared by Robert Shiller, reveals total market return statistics for varying time frames. We can see that, over the last 140 years, 20 year investment periods have had 100% probability of success, 15 year have had 95%, and then lower probabilities of success as the data moves left. Since the Market Map model was designed towards the long term investing time frame, we have used the 20 year time frame in our diversification study.

Chart 1

Shiller chart

Additionally as described in the beginning of the article, with the increasing longevity of the population , investors who are “slow starters” on their retirement asset accumulation plan and have missed the conventional 30 to 40 year asset accumulation “glide path” window (with a retirement age commencing at 65 ) typical of a more stable work, salary, and 401K contribution history, may still be afforded a chance in accumulating sufficient assets for a financially satisfying “late” retirement in a 15 plus year accumulation phase window.

The Quality Dividend Growth portfolio

The Dividend Growth portfolio applied to the diversification study* comprised of MMM, XOM, MRK, JNJ, MCD, PG, ED, GE, MO, KO (with a switch of GE for WMT on 01/02/08 for performance optimisation). The stocks are useful because they possess 40 plus year price history and have been stalwarts of consistent dividend payment increases.
Additionally, an analysis was conducted on the effect of different rebalancing frequencies on this portfolio over two different 20 year time frames and we found that, as Chart 2 and Chart 3 reflect, an annual rebalancing frequency was sufficient, did add value to the returns, and was implemented into the management of the 2 and 3 style allocation blends represented below.

Chart 2

Quality div growth 1970 - 1994

Chart 3

Quality div growth 1994 - 2013

Portfolio Diversification Using 3 Style Universes

Charts 4, 5, 6, and7 illustrate the types of returns achieved over the past 20 year period in terms of $ accrual using different percentage “blends” of asset allocations of the 3 style universes.

Chart 4 represents the first example of diversification “blend”. The Quality Dividend Growth portfolio was assigned a 60% allocation and the Growth** and Small Cap Value portions were each assigned a 20% allocation. The total portfolio was rebalanced every 5 years:

Chart 4

Pie chart 1

Chart 5 $ growth of each separate portfolio allocation and the combined total return of the 20-20-60% blend since 1994:

perf chart 1

Chart 6 represents the second example of diversification “blend” using a 20-20-60% configuration.
Quality Dividend Growth was again (initially) assigned a 60% allocation and the Growth and Small Cap Value portions were assigned each 20%. However, after a 5 year period, the allocation percentages were switched so that the Quality Dividend portion received 40% allocation and the Growth and Small Cap portions each increased to 30% allocation, or at total of 60% for both. Also, during this switch, the total portfolio was rebalanced.

Chart 6

Pie chart 2

Chart 7

perf chart 2

3 Portfolios and Volatility

Chart 8

DrawdD 1

Chart 9

DrawdD 2

Chart 10

DrawdD 3

Diversification Using 2 style Universes

In the previous charts 8, 9, and 10, we can see that the volatility, as measured by peak to trough drawdowns, was highest with the Small Cap value universe. In consideration of those investors who may have concern about having portfolio exposure to the greater volatility as represented by the small cap universe, we can utilize a 2 portfolio blend of the lesser 2 volatility universes by excluding the Small Cap Value style from the allocation mix (and consequently forgoing style diversification). These results are seen in charts 11, 12, 13, and 14 below:

Chart 11

Pie chart 2

Chart 12 $ growth of each separate portfolio allocation and the combined total return of the 40-60% blend since 1994:

Chart 12

perf chart 3

Chart 13 represents the second example of diversification “blend” using just the QDG and Growth portfolios.
Similar to the 3 style diversification blend, Quality Dividend Growth was again assigned a 60% allocation and the Growth portion was assigned 40%. After each 5 year period, the allocation percentages were switched so that the Quality Dividend portion received 40% allocation and the Growth portion increased to 60% allocation (and vice versa), accompanied with a rebalance:

Chart 13

Pie chart 4

Chart 14

perf chart 4

As with the value that the annual rebalancing provided the 10 stock Quality Dividend Growth portfolio over the non rebalanced version in charts 2 and 3, so did the 5 year 60% allocation “switch” between Quality DG and Growth/Small Cap value styles provide value versus the non “switched” versions.

Performance Comparisons and Vanguard Target Retirement

The charts shown below present an overview of the $ returns and compound growth rates of select items that have been covered in the article. We can see that the rate of growth for Quality Dividend portfolio slowed dramatically from 1994 – 2013 vesus the 1970-1989 period and that the performance of the combined diversified blends took the lead in the latter. As the data used for the Growth portfolio calculation in the 1970 – 1989 period was taken from the Nasdaq OTC composite and that the Nasdaq 100 outperformed the Nasdaq Composite from 1985 – 1989 (and beyond), we can assume that the performance for the blends would have been improved if the Nasdaq 100 was a viable option for use in a portfolio in that period.
An additional item included for comparison in charts 16, 17, and 18 is a mix of Vanguard funds that is part of their “Target Retirement” series (as with many other investment companies’ “Target date” offerings) and is a popular choice with the disciples of the John Bogle investment approach ***. The portfolio shown was constructed using a diversified equal weighted mix of three Vanguard funds: 1) Total Stock Market 2) Total International and 3) Total Bond Market. In the calculation, the mix was rebalanced every 5 years in order to maintain consistency with the calculation of the other portfolios in this article.

Chart 15

Growth Traject 2

Chart 16

Growth Traject 1

Chart 17

Perf compariasons

Chart 18

DrawdD 4

As we can see in chart 16, the compound returns and $ accrual of the Quality Dividend Growth and the Vanguard Target portfolios were admirable. The returns for most retirement plans constructed using Exchange Traded Funds **** seem to fall somewhere in between that of the Quality Dividend Growth and Vanguard “Target retirement” trajectories shown. Of course, there are many disparate factors that could affect contribution regularity applied towards a plan in “later” years and terminal asset accrual could vary from a strict extrapolated target.
Surprisingly, focusing on volatility concerns, the largest peak/trough drawdown for the Vanguard portfolio fared slightly better than the buy & hold of the Small Cap value (VBR) etf. Granted, the sample size used in the volatility calculation for the Vanguard portfolio is smaller than the other universes’ volatility charts in the study, yet the results still seem to run counter to the premise that holding a broadly diversified portfolio of funds (including the incorporation of a Total bond fund) provides “less risk”.

A Long Term Look at Compound Growth

A look at chart 19 shows 20 year compounded growth rates for various combined portfolio blends and universes over a 25 year span. Some observations include:1) The Quality Dividend Growth portfolio (yellow line) appeared to have a 6 year, 20 year Compound Growth Rate performance run of 3000% – 5000% from 1996 to 2002 and has since slowed to a sub 1000% 20 year CGR performance 2) the Small Cap Value universe (blue line) stayed in the 1000% CGR range until around 2004 and has since trended upward 3) the Growth universe CGR (green line) has consistently trended upward and 4) the combined 20-20-60% diversification blend (black line) tracked the performance run of the Quality DG portfolio until 2003 and appears to have stabilized between the 2000% – 3000% range, reflecting the strength of the Small Cap Value and Growth universes.
The reason to review this visual information, along with chart 1 and 16, is that it can further help solidify our conviction in “staying the course” for 20 year period(s). Knowing, for example, that the 20-20-60% blend is the product of the calculation of the 3 diversified universes with varying cyclical natures (at this moment, upward trending Growth universe, lower trending Quality DG, and awakening ? Small Cap Value) gives us an idea, along with historical volatility information, of the 20 year potential performance percentage and behavior of this blend. Obviously, an investor can invest in just the QQQ or the SPY with the Market Map model exclusively if they so choose, but this study provides some food for thought towards a diversified retirement asset accumulation plan.

Chart 19
20 year CGR


In the broad world of retirement plan investment choices, there are many different schools of thought and somewhat confusing misconceptions. As shown in this study with additional input from the previous articles:

a) tactical asset allocation models that have produced repeatable and consistent outcomes when applied to a Small Cap value and Growth stock universe, and combined with a buy & hold of a Dividend growth stock portfolio, have produced steeper asset accumulation trajectories over a 20 year investment period versus an exclusive buy & hold portfolio of Dividend growth, further providing style diversification albeit with more volatility.

b) tactical asset allocation models ( in “a)” ) when applied to a Growth stock universe and combined with a buy & hold of a Dividend growth stock portfolio, have produced steeper asset accumulation trajectories over a 20 year investment period versus an exclusive buy & hold portfolio of Dividend growth, providing less style diversification albeit with only slightly more volatility.

c) the use of the term “less risk” in literature regarding a broadly diversified portfolio of Vanguard funds targeted towards retirement is a misconception see here

Last but not least are the questions asked such as:

40 years ago, the dividend “stalwarts” were younger, mid to large cap size companies and have since turned into “mega” cap companies … If the slowing of the 20 year CGR shown in chart 19 has been a a reflection of a cap size growth effect and in order to achieve the types of returns produced from 1970 – 2002, which mid to large cap companies would represent the “new” era of dividend growers as replacements for the mature companies?

Or … will the expansion of the sales of products and services into developing markets give the mega cap dividend payers a cyclical move up in the portfolio’s 20 year CGR moving forward ?

To alleviate the management of annual rebalancing of a 10 stock dividend growth portfolio, would a dividend ETF used in it’s place be a reasonable option?

Unfortunately, the above questions are the very ones that turn us into stock selection portfolio managers (with all of the latent obsessional behavioral tendencies and performance drift accompanied therein) and pull us slightly away from the non-subjective rule based simplicity of using a data driven tactical model. Yet for the comfort that “brand” stocks provide an investor, it is an uncomfortable reality in this particular form of style diversification.

** Growth as represented by Nasdaq 100 index/QQQ using the Market Map model. Small Cap value as represented by the French small cap value weighted 2 factor model/Vanguard Small Cap Value ETF using the Market Map model.

instead of settling for the conventional, we frequently remind ourselves that “there’s gotta be a better way” and “we can take it to the next level“.

Market Map Model Allocates To Cash

Our first article introduced the implementation of five components which, during fixed times in a given year, present us with a “map” of where to allocate capital between exchange traded funds based on 1) market indices (the SPDR Trust ETF (SPY), Vanguard Total market ETF (VTI), or Powershares QQQ Trust ETF (QQQ)SPY), 2) long treasury bonds (the iShares 20+ Year Treasury Bond ETF (TLT) or the Vanguard Long-Term Treasury Fund Investor Shares (VUSTX)) or 3) “cash” (short term treasury equivalents/money market funds).

At the end of 2013, the initial requirements towards taking action in allocating assets from the equity ETFs to “cash” via components #1 and #2 (ie. consecutive years of “overperformance”; performance greater than an average of the 40 CAGR of the S&P500 index) were satisfied. Since then, we also needed further and final confirmation from component #3 (the “performance score” derived from time series analysis from the November, December, and January time period). On 01/17/2014, this requirement was satisfied with the final “risk profile” outcome generated from the combined effect of components 1,2,& 3 = Neutral. Hence, a Neutral risk profile reading equates with a shift in asset allocation from equity based index etf’s to a “cash” allocation ( short term treasury equivalents). An explanation of the four risk profiles used in the Market Map model are described here

Table 1 shows the performance of the neutral risk profile years encompassed in the past 90 years data set.

Table 1

post 1 17 2014 neutral table

Table 2 = Market Map model performance using the S&P500 index over last 15 years of asset allocation periods through 01/17/2014.

Table 2

post 1 17 2014  SPX table

Table 3 = Market Map model performance using the Nasdaq 100 index over last 15 years of asset allocation periods through 01/17/2014.

Table 3

post 1 17 2014 NDX table

In conclusion, the Market Map model has indicated that an asset allocation change from an equity position to a cash position is warranted. The next time frame of note for a possible asset allocation shift will occur in the beginning of July.

In navigating the sea of financial opinion and emotion, we can find solace and confidence in 90 years of non-subjective, statistically significant data incorporated into a model that has produced consistent and repeatable outcomes.

Market Map update 12/30/2013

As we approach the end of 2013, we look to the components that make up the Market map model to give us a systematic indication of tactical asset allocation changes, if any.

Component #1 and #2 calculate:

1) the annual performance(s) of the SP 500 index versus calculation of an average of the 40 year CAGR ( compound annual growth rate ) of the SP 500 index ( total return basis ).

2) Rule set applied to mean variance / regression calculations performed on “consecutive” years of annual “overperformance” or “underperformance” that occur as calculated in # 1. See objective # 5.

The average of the 40 year CAGR calculation of the S&P500 up to 12/2013 is 10.3%

The return for the S&P500 for 2012 was 15.9%

The return for the S&P500 for 2013 has been 31.7%

2012 and 2013 have produced consecutive returns > the calculation of component #1.

Component #3  derives data from a time series analysis applied to strategic data points occurring over the months of November, December, and January segregated into performance scores. These scores have had high correlation coefficients relative to the following year’s market performance and are integrated with component #2.

Objective #5 does not apply for this year .

Since the requirement for 2 consecutive years for components #1 and #2 has been fulfilled, this indicates that the market has “overperformed” it’s mean as calculated by the algorithm. We now have an alert towards asset allocation action. We need to wait for the calculation of component #3, which occurs in the middle part of January. If component #3 calculation produces a “Favorable Risk Year 6 month” profile, then we will remain allocated in the equity ETF’s QQQ ( or the SPY ) until July 2014. If it produces a “Neutral” or “High Risk” reading, then we will allocate assets towards cash equivalents. The most recent asset allocation action was taken 12/30/2011; SPY @ 125.5 and QQQ @ 55.8.
If “brand new” capital is to be put to work, then allocation towards the QQQ or SPY ETF would be performed, near the end of the last trading day of the year.

Table 1,2  show previous instances of the current scenario:

Table 1
Deploying brand new cash last trading day of year. Component #3 indicates “Favorable 6 month”:


Table 2
Deploying brand new cash, last trading day of year. Component # 3 indicated “Neutral” or ” High risk”:

Whipsaws Map


Market Map component described here:

Market Map risk profiles:

We are long QQQ

Market Map  ….. Think different(ly)


Market Map Model 2 : Using Small Cap Value Weighted Portfolio

This article examines Market Map model 2 applied to a portfolio with a tilt towards a small capitalization “value weighted” methodolgy.  The portfolio constructed using this methododolgy is based on the Fama/French “factor” model; the factors being beta, size, value, and momentum. The DFA US Small Cap Value (DFSVX), a mutual fund whose composition utilizes the factor model, was created through the efforts of Dimensional Fund Advisors

Additionally, the analysis combines MMap model 2 with a “Sell in May” component, both of which are applied to the Small cap data. The initial details of Market Map model (as applied to the S&P500 index) are covered here and the “Sell in May” primer is here .

The Small Cap indices and historical performance data compiled for the analysis and calculation for the tables below come from: 1) the DFA US Small Cap Value I (1999 to 2013) from the Morningstar website 2) the “Small capitalization Average Value Weighted” portoflio formed on size and momentum (1927-1998 ) from the Kenneth R. French data library 3) the Nasdaq 100 index (1989-1999) / Powershares QQQ Trust ETF (QQQ) (2000-2013) and 4) Barclays iShares 20+ Year Treasury Bond ETF (TLT) / Vanguard Long-Term Treasury Fund Investor Shares (VUSTX) / or 30 year bond rate.

Table 1

Market Map model 2 + Sell in May allocation dates using Small cap indices data and 30 yr. Bond proxy  1927 – 2013

SV signal dates Map sell in May 1927- 1973   SV  trade dates Map 2 Sell may SV 1974 - 2013

Table 2

Statistics for table 1 :

Stats 86 year

Table 2 shows that over an 86 year period,  both the Market Map model 2 and MM model 2 with the added “Sell in May” component outperformed the Small Cap value buy an hold with less risk, with the “Sell in May ” component outperforming by a wide margin.

Tables 3 – 6

Historical 25 year annual returns tables :
Small cap Buy Hold   Small Cap Map 2

Small Cap Sell in May  QQQ Map 2
Table 7

Historical statistics based on tables 2 – 5 using MM model 2 with Small cap value and Nasdaq 100 / QQQ 1989 – 2013  :

Stats 25 years Sell in May

Table 8

Annualized returns 5, 15, 25, 86 years

Stats annual returns

In viewing tables 3–8, the Market Map model 2 combined with “Sell in May” component (table 8 item c) outperformed items a, b, and d. The “Sell in May” component improved the performance of the series when applied to the Small cap value porfolio, but didn’t provide performance improvement when applied to the Nasdaq 100/QQQ index (analysis not shown). The reason for the performance superiority of “Sell in May” when applied to the Small cap universe is unknown; perhaps there was/is performance advantage gained during the November–December period years when the “Sell in May” was invested and the MM model 2 was in cash ?.

As the work of Fama and French has proven that a Small cap 4 factor model is dominant in compound return and risk versus the performance of the other Morningstar style box classifications, an interesting aspect of this study is that the QQQ ETF, while representing a “large cap growth/blend” classification in the style box, has returns comparable to items b and c in table 8 with similar risk characteristics when the Market Map model is applied. In determining the best performing asset vehicle for investment in the Market Map program, one aspect that can give the QQQ ETF an advantage over Small cap value funds over a long investment time frame, is the consideration of management fee and tax ratios. In terms of Tax Cost and Net Expense Ratios, QQQ has much lower ratios than those of the DFA US Small Cap Value.

We believe that a small cap value factor portfolio has greater return potential than the QQQ as measured by the MMap model results and by the research conducted by Fama and French. Yet, until a low expense and low tax ratio exchange traded fund that reflects an underlying Small Value Momentum factor methodolgy becomes available and accrues reasonable trading history, we favor the use of the QQQ ETF as the appropriate “small cap” investment vehicle for the Market Map model for the foreseeable future.

” When everyone is looking for the needle in the same haystack, go look in a different haystack”

Market Map Model 2 : Using Nasdaq Composite And Nasdaq 100 Index

In our first article, we listed low cost Exchange Traded Funds that could be utilized by the Market Map models during equity allocation periods;one of those ETF’s being the Powershares QQQ Trust ETF (QQQ). As we continue our search for alpha, in this article, we will input data for the Nasdaq 100 index (NDX) into the Market Map historical record as it is the underlying proxy for the QQQ. And, in order to achieve more robust testing, we will also employ the Nasdaq Composite index from 1962 through 1987 (as the NDX historical price history starts in 1985).  

Going forward, in order to avoid redundancy in presenting historical entry and exit data output from the Market Map models #1 and #2, we will only present the applicable statistics tables. Readers can reference the data for MMap models entry and exit tables in the previous articles here and here

Statistics 1962 – 2013:

Map Nasd Stats 1962

Statistics 2000 – 2013:

NDX QQQ stats revised

As expected with our model, smaller cap growth stocks provide the best returns so far, albeit with more volatility. In our next post, we will implement a Fama and French value portfolio into the Market Map model.

Market Map Model 2 : Enhancing Returns With Bonds

In previous articles, we looked at the objectives, components and risk profiles of the Market Map model. In this article we add two options to Model #1: 1) a strategic allocation of assets towards Long-term treasuries during “cash” allocation periods (using the iShares 20+ Year Treasury Bond ETF (TLT) or the Vanguard Long-Term Treasury Fund Investor Shares (VUSTX)) and 2) a two stage asset allocation towards equities during qualifying periods of significant market underperformance (component #5 in the first article).

Option #1 employs a trend identifier for positioning into bonds.

Option #2 was designed with the intention of alleviating behavioral biases that can occur when committing a single, full 100% allocation instance towards equities during significant market downtrend scenarios. Instead, when in the throes of these scenarios, equity allocation is committed in two 50% increments.

Market Map model 2 Historical Table vs. S&P 500 (dividends excluded)

*Bond returns shown reflect 75% allocation. Allocation level can vary depending on each individual’s risk tolerance

Historical Bond pricing used TLT, VUSTX, and 30 year Long bond rate

Map + 50% BOND calc 1
Map + 50% BOND calc 2
Map + 50% BOND calc 3
Map 50% BOND calc 4
Map 50% BOND calc 5

Bond Allocation Dates:
Statistics 50% BOND calc

Statistics 1924-2013, 2000-2013

Statistics Map 50% BOND 1924
Statistics Map 50% BOND 2000

In comparing the statistics tables above to the statistics tables for Market Map model 1, here we can surmise that adding bond allocation and using a two stage entry strategy for select equity allocation enhances overall returns and lowers max drawdown albeit with higher portfolio turnover.

In our next article, we will apply the Market Map model to the Nasdaq Composite and the Nasdaq 100 index.