New Global Tactical Model Series added…

For the convenience of those interested in tracking Mebane Faber’s popular Global Tactical Asset-Allocation model that he originally featured in his 2006 paper, I have added that model among our tactical ETF models. As I discussed in a Seeking Alpha article, I have replaced the original 10 period moving average with the 8 period…it just seems to work better. Overall though, readers will find this tracks pretty close to what Meb has on his own site.

As some of you are probably aware, Meb has published some updates to his original paper, the most recent being February 2013.  In the latest update, Meb introduced 8 additional asset-classes for a total of 13.   He also discussed several alternative methods of allocating funds, one which included the discussion of combining a momentum-based ranking system along with the original use of the trend following moving average.  (Links to both the original and the updated paper can be found on the Reference page.)

This inspired me to conduct some research of my own given the tremendous success I have had with applying momentum across a variety of asset-classes.  After testing many combinations of factors, the finished model ranks the 13 ETFs using a ranking system that combines both momentum and volatility.  Any ETF that is not above the 8 period moving average is eliminated.  Finally, instead of selecting  the top five ETFs as Meb does in his paper, I settled on buying the top three in equal weight as the best choice. Below in the table are my test results.

Number of ETFsCAGRSharpe RatioMaximum DrawdownTotal Return (dividends reinvested)

To summarize, less than three and the portfolio volatility reached unacceptable levels and more than three, the portfolio returns quickly diminish.   Thus, I have aptly named the new model, GTAA – Focus Three.

For some who may think that owning just three ETFs each month is too limited, remember that each ETF is in itself extremely diverse.  For example, the iShares Russell 1000 Growth ETF, a current model holding, is diversified with 625 separate securities.

I personally really like the stability of this model and how well it navigated the the 2007-2009 period.   Unlike some of my other models, this model does not include an inverse fund but never the less, the inclusion of fixed-income ETFs provided enough opportunity to keep downside risk contained to acceptable levels.

For individual investors looking for a single model that covers most all of the major asset-classes, I believe this could be a good choice.  And for financial advisors who want a simple but effective way to managed their client book, I would have to think this model could serve them well and provide the ability to build a very scaleable practice.

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Can Relative Strength be used for Market Timing?

I wanted to construct a simple illustration as to why I am so confident of the models offered at this site and their ability to adapt to the markets.  While Relative Strength (RS) is not often thought of as a "market timing" tool per se, the ability of RS to identify important shifts in the market is well documented.  As important as it is to understand what the market is favoring, an equally important benefit of following an RS strategy is the ability of RS to identify those asset classes that investors should avoid.

To create the above "buy" and "sell" signals, I set up a model using two ETFs:  SPY and SHY (which is a default I use for "cash").  The RS is calculated using a 3-month and 6-month combined weighted score with an added volatility filter.  A model constructed in this fashion will favor an asset as long as the return is commensurate with the amount of risk being taken.  If the volatility is increasing but the return is not, then the model will default to cash (SHY).   I used a default monthly holding period with the calculation being completed on the last trading day of the month and the model rebalanced on the first trading day of the following month.

The efficacy of this approach can be demonstrated two ways.  First, in the chart above, I have labeled the points in which the respective signals occurred.  Note that the initial sell signal occurred on the November 30, 2007 rebalance with the SPY trading around 142.  On December 1, 2007, the model would be 100% invested in SHY, a position that would be held until June 1, 2009.  Thus, one of the worst portfolio drawdowns in history resulting in what could have been a near 55% decline, was avoided.  

On June 1, 2009, the model was rotated back to SPY, a position that would be held for one full year.  At that time, the model reverted back to SHY missing the balance of last summer's sideways chop, and then re-entered the market on November 1, 2010.   

Shown another way, the graphs below show the performance difference between simply "buying and holding" the S&P 500 vs. the aforementioned RS model.

  The RS model not only significantly out performed a "buy and hold" approach but it also reduced volatility by 66%!   An additional benefit to this type of approach is that all decisions are 100% mathematical and all human emotion is removed.  This gives investors high statistical probability of avoiding large losses while providing significantly higher total return in nearly all market conditions.  While the future of the market is unknown, the existence of mathematical expressions between relative return and risk should continue to be a useful guide for investors.   

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The Paradox of Choice…Can Having Too Many ETFs Make You Unhappy?

Social scientist Barry Schwartz makes the case in his book "Paradox of Choice – Can Having Too Many Choices Make You Unhappy" that unlimited choices produces genuine suffering.  The more choices we have to make, the less certainty we seem to have. Let's apply this to investing.

Today, there are over 1,000 Exchange Traded Funds (ETFs), representing one of the fastest growing segments of the investment industry.  ETFs first became popular back in the early 1990s with the introduction of  "SPY", or Standard & Poor's Depository Receipts.  Also known as SPDR or Spider, this ETF has gone on to become the largest in the world. Initially designed to provide a fast and affordable way to mimic popular stock market indices and sectors, today ETFs have proliferated to represent an array of regions, sectors, commodities, futures, and other asset classes.  

So, according to Schwartz, when faced with seemingly unlimited choices that have significant consequences, such as investing, people will relentlessly search for the best option.  These people spend a great deal of time and energy on choices that will never satisfy them.  Which brings me to the main point of this post and to why I created PortfolioCafe.

Relative Strength investing and mechanical stock screening approaches have the ability to quickly and easily cut through the many choices presented to investors.  With Relative Strength we can quickly and easily reduce the universe of ETFs to only those that matter at this moment.  The best performing investment opportunities naturally present themselves to us.  With mechanical, multi-factor models, investors can screen through thousands of stocks and find the small handful that meet a given criteria.  By following such approaches, investors can reduce their choices and apply their limited time and energy in a meaningful way.

I am not against choice or the many new ETFs which have been constructed.  Quite to the contrary, I think investors have never had it so good.  For much of my career as a broker, the only way to hedge a portfolio against downside risk was buy purchasing put options or shorting stocks.  Today, investors can easily hedge a portfolio or actually profit from market declines through inverse ETFs.  Also, it has never been so easy to build a well diversified portfolio with exposure to a variety of asset classes.  So choice is good.

What I think is missing for many investors is the means to filter the many choices.  Too much information and too many choices causes paralysis. Investors are constantly bombarded with "tips" and "market news" which in reality is nothing more than "noise".   

PortfolioCafe was designed around systematic and mechanical approaches to investing which reduce the time and energy spent on decision making.  The systems and models presented within this site are well grounded upon research and historical evidence.  The "Paradox of Choice" has been greatly reduced to a handful of well thought out and carefully researched systematic approaches to investing. 

In my next post, I will discuss "The Art of Becoming an Investor Minimalist".

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