Market Map Stays In Cash

As another predefined date for actionable asset allocation as defined by the Market Map model has been reached, at this time the model is indicating holding the allocation in cash. As there was a possiblity that the model could allocate to bonds during this July, the negative trend in bonds cancels the opportunity. In a single late signalling case, ( 9/3/1982 in table below ) out of 14 occurences back to 1924, did the model indicate an allocation to bonds outside of the early weeks of the July time frame. If the model should indicate this late behavior again, we will update the blog ..

The next actionable allocation date will be 12/31/2015 …

Map Model
All signals BOND
Buy Date Sell date BOND return
07/11/46 10/30/46 -6.1%
7/5/1960 10/03/60 2.6%
09/03/82 10/02/82 5.5%
07/10/92 10/02/92 3.2%
07/11/97 10/03/97 6.6%
7/2/1998 10/02/98 9.7%
07/02/99 10/02/99 1.1%
07/06/00 9/28/00 3.4%
07/06/01 9/29/01 7.5%
07/05/02 10/04/02 15.9%
07/05/08 10/03/08 4.5%
07/09/10 10/01/10 6.6%
07/08/11 09/30/11 21.3%
07/11/14 09/29/14 3.50%
average 6.1%

Model With “Sell In May” Component Goes To Cash

As May 1st occurred last week, the Market map model combined with the “Sell in May” component using the small cap value universe, has signaled a cash allocation. The model previously signaled an allocation to small cap value on 09/27/14 ( here: Previous instances of buy and hold returns during cash allocation periods are reflected in the chart below.

Small Cap Value returns during  Sell in May Cash

Further explanation on the Market Map model using the “Sell in May” component can be found here:

Probability of allocation to TLT (iShares 20+ Year Treasury Bond ETF) on 7/1O/15 = 5O%

Market Map: Staying the Course for the Long Term 2015

As we head into Spring 2015 with the model in a cash position, we look back at the model’s performance in 2014 and note it as a year of “underperformance” vs. the S&P 500 (as the model produced a return of 8% and the S&P500 benchmark produced 13.5% ). From time to time, it is possible for an occurrence, such as this, to happen and for us to react with skepticism, uncertainty, and doubt, especially when it involves our investments. We are “hard wired” and  persuaded by societal cues into thinking in terms of “short term” results and we tend to define the equity market in terms of “winning” and “losing” ( we are much more sensitive to “losing”).

We are fortunate to have 9 decades of  historical model performance with which to analyze and review past occurrences of when the model “underperformed” the S&P 500.


ScreenHunter_540 Apr. 07 17.52


Model underperf years

As we can see in table 1 and the chart above, these years of underperformance have happened occasionally and are evenly distributed over the sample with “consecutive” years of underperformance occurring in sporadic fashion.




ScreenHunter_539 Apr. 07 17.43

Table 2 shows the ratio of outperforming vs. underperforming occurrences and cum % performance.

The stock market’s price is the discounted present value of it’s future earnings and the market  can “overshoot” this present value for periods of time. During this part of the investment cycle, this “overpricing” can be caused by: 1) portfolio analysts’ upwardly adjusted revisions in earnings estimates and  2) investors’ optimism and “fear of missing out”  as the market rises or has, in retrospect, produced many consecutive positive years returns. We must expect that these periods will exist and can expect to leave some “gains on the table” with the knowledge that we are accumulating and compounding assets over the “long term”. We can gain perspective by examining the “long term” performance statistics, and adjust our reactivity and concern accordingly . 

We can also gain perspective by viewing, in a graphic sense, how much equity exposure towards historical market up moves or down moves has been realistically “captured” by the model in order to achieve portfolio alpha (in this presentation) :




Asset allocation since 01/20/15 = cash
Probability of allocation into TLT (iShares 20+ Year Treasury Bond ETF) on 7/13/15 = 5O%






Market Map update 01/05/2015

In the current market environment, in order for us to make tactical decisions and define and manage the risk in our portfolio, we use component 1 and 2 identify and measure the annual returns of “overperformance” of the S&P500 index versus it’s 40 year compound growth rate. Further identified are consecutive years of “overperformance”and 2014 represented the 3rd year of “overperformance” by this quantification.  The chart below shows previous occurrences of of susequent returns after the consecutive years of “overperformance”:

Subsequent years

This gives us preliminary knowledge towards “mapping” risk to reward in the upcoming market environment.  As shown above, statistically, odds of consecutive years of overperformance leading to negative returns are slightly more than 50% since 1924. Another way of stating this would be “the odds on which price will revert back to the “mean” in relation to past occurences”.

To be conclusive in our decision making process, we look next to component 3, which defines risk outcomes derived through an analysis from data contained in the months of Nov, Dec, and Jan and segregated into “risk profiles”. These “risk profiles” further refine statistical insight towards actionable tactical allocation decisions with final risk profile readings being calculated in the 3rd week of January ( 01/16/2015 ). In the present case, since the consecutive years of outperformance regime has occurred, we look for the following:

1) a “neutral” or “high” risk profile reading will shift the portfolio allocation towards a “cash” position or

2)  a “favorable invest 1st half of year” risk profile will keep the allocation  in equities /  Powershares QQQ ( QQQ ) until the first week of Jul.  The charts below reflect past risk profile return outcomes. 

The chart below illustrates historical returns from the ” Favorable Invest 1st Half ” and “High” risk profiles:

Favorable Invest 1st HalfHigh risk profile

Stay tuned for update on weekend of 01/16/2014 …

For further explanation on the model see post :

The recent performance of component #4 ( 4th quarter of 2014; when which we allocated to QQQ from TLT  ) was again positive contributing to further statistical significance and long term alpha. The charts below show all historical returns for component 4 “select 4th quarters” since 1924, including the 4th quarter of 2014 :

ScreenHunter_428 Jan. 05 19.48

ScreenHunter_429 Jan. 05 19.49

Market Map update 09/15/2014

As the Market Map model’s current allocation is longer dated U.S. bonds ( TLT ), we again look ahead to the predefined allocation schedule and to the model’s components in preparing for the next tactical allocation action. On 09/29/14, component 4, “4th quarters characteristically showing statistically significant probability of profitability”, will come into play.  The allocation will shift from TLT, to the SPY or QQQ  etfs, with the QQQ achieving higher alpha historically.

Additionally, the model combined with the “Sell in May” component is also affected by this 4th quarter rule and allocates from cash to the small cap value universe ( as described here:

Allocation 4th Q  2014

This table and graph show  the previous instances and performances of component 4.

4  quarters  table

4th quarters graph

We examine the performance of the above table and graph and the historical performance table here: for the purposeful reminder of staying with the model for a long term, multi year asset accumulation process through time diversification and compounding, and not for the purposes of developing pride and arrogance and the turning of quick profits.

The next predetermined asset allocation date will be: 01/16/2015

Review of Allocation Dates ( Objective 3 )

One of the pitfalls of active investment management is the inability to follow the rules of one’s investment discipline. This could be because the investor / manager uses subjective means to determine asset allocation ( thereby “anchoring” off of the “purchase prices” of assets) or because the signals produced by their process’s algorithm occur in a random fashion and can’t be “anticipated” with precision. These biases, along with a lack of robust historical testing and trustworthy empirical results, ultimately lead to cognitive dissonance and uncertainty in many investors’ asset allocation decisions. 

The Market Map model was designed to alleviate these pitfalls with the application of “predefined” dates used in asset allocation decisions, which we spell out as “objective 3″ in our list of model objectives. In this way, instead of letting ambiguity and purchase price control our decision process, we let “date” control it.   In previous posts, we have charted the course of the model’s asset allocation process in real time and have published actionable reminders ahead of the actual allocation dates. The tables below show the definity of the method. The first table shows the historical Equity allocation dates and the second table shows the cash and bond allocation dates. In a perfect world, it would be nice to predefine 100% of the equity allocation dates yet, as shown in the first table, the model comes up with 77% predefined.

Equity Allocation predefined dates

Cash Bond Allocation Predefined dates

…. Model remains in TLT until 9/29/2014

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