Weekly RS Recap

November 7, 2016

The table below shows the performance of a universe of mid and large cap U.S. equities, broken down by relative strength decile and quartile and then compared to the universe return.  Those at the top of the ranks are those stocks which have the best intermediate-term relative strength.  Relative strength strategies buy securities that have strong intermediate-term relative strength and hold them as long as they remain strong.

Last week’s performance (10/31/16 – 11/4/16) is as follows:

ranks

This example is presented for illustrative purposes only and does not represent a past or present recommendation.  The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  The performance above is based on pure price returns, not inclusive of dividends, fees, or other expenses.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

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Point and Figure RS With Micro Caps

November 2, 2016

We have written quite a bit over the years about using point and figure relative strength for stock selection.  One of the whitepapers that discusses the basics of using RS can be found here.  In a lot of the research (including the whitepaper in the link) we use a universe of large capitalization stocks.  There really isn’t a good reason for the use of that universe.  Generally speaking, it is easier to deal with large caps because the information tends to be cleaner, and people are usually more interested in hearing about companies they know and recognize.

Point and figure relative strength works just as well or better on universes of small capitalization stocks.  The small cap universe is incredibly dynamic, and each year there are plenty of big winners and plenty of companies that wind up going out of business.  The dispersion of returns is very high, which is very good for a momentum strategy.  The micro capitalization universe has stocks in it that are even smaller than the small cap universe.  Micro caps are truly the wild, wild west.  The other characteristic with micro caps that make it a good universe for relative strength analysis is there is very little analyst coverage on these companies because they are so small.  That makes it easier to find undiscovered gems than it is in a larger capitalization universes.

To define a micro cap universe, we took the all of the stocks trading on US exchanges at the end of each calendar year and included everything ranked every company by market capitalization.  Stocks ranked from number 2000 through 3500 were included in the universe.  That universe essentially includes the bottom half (in terms of market cap) of the Russell 2000 and then another 500 stocks that don’t even qualify for inclusion in the Russell 2000 Index.  At each month we ranked every stock in the universe by relative strength versus a micro cap benchmark.  If you are unfamiliar with how a point and figure relative strength ranking works you can find an explanation in the paper linked to above.  Stocks were placed into one of four baskets at each month end based on point and figure relative strength chart configuration (signals and columns).  Each month the baskets were refreshed and all of the stocks in each basket were equally weighted.  Equally weighting each stock on a monthly basis would prove to be difficult in actual portfolio management, but we are just trying to get an idea about the power of relative strength in this universe.

microeqmicroret

(Click To Enlarge)

The Universe return listed above is the monthly equal weighted return of all the stocks in the universe.  We have included this because most broad market benchmarks are capitalization weighted and do not get the benefit of getting reweighted each month at no cost.  The returns of the universe are the best apples-to-apples comparison of how the universe was constructed.  The Benchmark return is a blended return of two different indexes: Russell 2000 Total Return and Russell Microcap Total Return.  The data on the Russell Microcap index doesn’t go back to the beginning of our test.  Before the microcap index was available we used the Russell 2000, and then linked that index performance to the microcap index when the data became available.

The stocks on a point and figure buy signal and in a column of X’s are the strongest stocks.  That basket of stocks performs remarkably well with very good volatility characteristics.  One thing that appears to be the case in the microcap universe is that relative strength helps find quality companies.  There are so many microcap companies that are, for lack of a better term, a hot mess.  Quality is extremely important when dealing with such small firms.  Most large cap companies are large because they have multiple products, experienced management teams, and defined processes and controls.  Sure, large cap companies make mistakes and their stock prices can go down quite a bit, but it is nothing like what goes on in the microcap space.  Momentum is very important when looking at very small stocks, and it also helps filter out a lot of the companies with poor quality characteristics.

Momentum works in a number of different markets and across markets.  In a universe of very small companies it is no different.  Using point and figure relative strength as a filter to focus on the strongest stocks in the universe is a great way to increase your odds of success.

Performance data is the result of hypothetical back-testing.  Investors cannot invest directly in an index.  Indexes have no fees.  Back-tested performance results have certain limitations.  Back-testing performance differs from actual performance because it is achieved through retroactive application of an investment methodology designed with the benefit of hindsight.  Back-tested performance do not represent the impact of material economic and market factors might have on an investment advisor’s decision making process if the advisor were actually managing client money. Past performance is not indicative of future results. Potential for profits is accompanied by possibility of loss.  Neither the information nor any opinion expressed shall constitute an offer to sell or a solicitation or an offer to buy any securities, commodities or exchange traded products.  This document does not purport to be complete description of the securities, markets or developments to which reference is made.  Performance is inclusive of dividends, but does not include any transaction costs.

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Weekly RS Recap

October 31, 2016

The table below shows the performance of a universe of mid and large cap U.S. equities, broken down by relative strength decile and quartile and then compared to the universe return.  Those at the top of the ranks are those stocks which have the best intermediate-term relative strength.  Relative strength strategies buy securities that have strong intermediate-term relative strength and hold them as long as they remain strong.

Last week’s performance (10/24/16 – 10/28/16) is as follows:

ranks

This example is presented for illustrative purposes only and does not represent a past or present recommendation.  The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  The performance above is based on pure price returns, not inclusive of dividends, fees, or other expenses.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

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David Letterman on Prospect Theory

October 25, 2016

I stumbled across this gem from the NYT recent interview with David Letterman:

More earnestly, he added: “Maybe life is the hard way, I don’t know. When the show was great, it was never as enjoyable as the misery of the show being bad. Is that human nature?”

Yep, it is definitely human nature.  And it has implications for our investment behavior as well.  From then entry on Prospect Theory in Investopedia:

According to prospect theory, losses have more emotional impact than an equivalent amount of gains. For example, in a traditional way of thinking, the amount of utility gained from receiving $50 should be equal to a situation in which you gained $100 and then lost $50. In both situations, the end result is a net gain of $50.

However, despite the fact that you still end up with a $50 gain in either case, most people view a single gain of $50 more favorably than gaining $100 and then losing $50…

…Prospect theory also explains the occurrence of the disposition effect, which is the tendency for investors to hold on to losing stocks for too long and sell winning stocks too soon. The most logical course of action would be to hold on to winning stocks in order to further gains and to sell losing stocks in order to prevent escalating losses.

When it comes to selling winning stocks prematurely, consider Kahneman and Tversky’s study in which people were willing to settle for a lower guaranteed gain of $500 compared to choosing a riskier option that either yields a gain of $1,000 or $0. This explains why investors realize the gains of winning stocks too soon: in each situation, both the subjects in the study and investors seek to cash in on the amount of gains that have already been guaranteed. This represents typical risk-averse behavior.

David Letterman perfectly articulated a condition that affects most of us: we feel the impact of loss and pain to a greater degree than we feel the impact of an equivalent amount of gain or joy.  Left unchecked this disposition effect creates all kinds of problems in our investing behavior.  We hold on to the losers because if we don’t actually sell a loser then we won’t have have to admit that the trade didn’t work and we think we are avoiding some measure of pain.  And the winners, well we sell them as fast as possible to avoid seeing those gains evaporate (even if it means missing out on the continuation of that trend).

The only problem with giving in to the disposition effect is that it leads to very poor investment results.  See Jim O’Shaughnessey’s What Works on Wall Street.

So what can be done?  As with most things in life that work, the solution is not complicated.  It only requires great discipline.  It is for this very purpose that adherence to models (which enforce discipline and helps combat the disposition effect) is front and center in the Dorsey Wright experience.  It may never become “easy” to take the trades that a well-designed model provides, but I can attest to the fact that it is easier and I believe more profitable than trying to navigate the markets without models.

The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.

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Weekly RS Recap

October 24, 2016

The table below shows the performance of a universe of mid and large cap U.S. equities, broken down by relative strength decile and quartile and then compared to the universe return.  Those at the top of the ranks are those stocks which have the best intermediate-term relative strength.  Relative strength strategies buy securities that have strong intermediate-term relative strength and hold them as long as they remain strong.

Last week’s performance (10/17/16 – 10/21/16) is as follows:

ranks

This example is presented for illustrative purposes only and does not represent a past or present recommendation.  The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  The performance above is based on pure price returns, not inclusive of dividends, fees, or other expenses.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

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Relative Strength Spread

October 18, 2016

The chart below is the spread between the relative strength leaders and relative strength laggards (top quartile of stocks in our ranks divided by the bottom quartile of stocks in our ranks; universe of U.S. mid and large cap stocks).  When the chart is rising, relative strength leaders are performing better than relative strength laggards.    As of 10/17/16:

rs-spread

The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

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Elkhorn Commodity Rotation Strategy ETF (DWAC)

October 17, 2016

While the majority of investors allocate their dollars primarily between equities and fixed income, there are a number of alternative assets that may add value to the portfolio over time.  Furthermore, the advent of ETFs has made it easy for investors to gain exposure to areas of the financial markets that were previously reserved for the savviest of investors.  One such example is the Commodity asset class.  Today, investors can select from upwards of 140 ETFs and ETPs to introduce commodity exposure into the portfolio, instead of trading futures contracts. One of the newer ETF products to hit the market within this space is the Elkhorn Commodity Rotation Strategy ETF DWAC, which uses the Dorsey Wright methodology to target those commodities with the strongest relative strength characteristics.

One of the main factors which helps enable a relative strength based strategy to generate strong returns is ample performance dispersion among the investable universe.  The most popular commodities discussed by mainstream media are precious metals (gold, silver, platinum) and energy (crude oil), but that only scratches the surface of this asset class as a whole. For example, the “softs” complex (which includes Sugar, Cotton, Cocoa, Orange juice, and Coffee) certainly isn’t making CNBC headlines on a daily basis, but Sugar futures are the top performing commodity on the year and have registered an impressive gain of over 50% in 2016.  On the flip side, agricultural Commodities such as Live Cattle (-20.22%), Wheat (-20.79%) and Lean Hogs (-25.27%) continue to lag and remain in very firm downtrends.  At some point these trends will change, but the dispersion which exists within the asset class remains wide year over year.

Generally speaking there are about 5 different commodity sectors: precious metals, industrial metals, livestock, agriculture, and energy.  One of the most commonly used benchmarks for the asset class is the S&P Goldman Sachs Commodities Index (GSCI).  It was launched in May 2007 and holds approximately 24 different commodities. The index allocations are world production weighted based on the average quantity of production of each commodity.  Currently, the index is allocated as follows:  Energy (70.44%), Industrial Metals (8%), Precious Metals (3.68%), Agriculture (12.78%), and finally Livestock (5.11%).   As a result, energy is the tail that wags the dog in this instance, accounting for more than two-thirds of the index’s performance. This is not unusual to see across many broad based commodity ETFs, making the DWAC quite different from the rest of the pack in terms of the exposure it offers.

The underlying index follows a Dorsey Wright relative strength based strategy to make its allocation decisions. The product also implements the dynamic roll methodology in order to avoid cost of carry issues at futures expiration. The universe for the underlying index includes 21 different commodities, and the index will target the top five on a monthly basis with a 20% weighting in each. The ability to tactically rotate through a broad universe of commodities and concentrate within the top performing sectors while eliminating exposure to the weak sectors is what makes this product both dynamic and unique. As of 9/30/2016, the current allocations in DWAC are as follows: Sugar, Silver, Coffee, Zinc, and Cotton. Additional information regarding historical allocations and other product info can be found on the DWAC factsheet.

DWAC vs. GSCI Equity Curves

1995-2015

Below we have as we plotted the equity curves in order to help compare historical performance of DWAC vs. GSCI.

1

DWAC inception date: Sept 21, 2016, GSCI inception date: May 7, 2007 – data prior to inception is based on a back-test of the underlying indexes.  Please see the disclosures for important information regarding back-testing.  DWAC Returns are calculated on a total return basis.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss. 

DWAC vs. GSCI Performance

1995-2015

The table below gives a detailed perspective on the historical performance for each index.  Notice that DWAC offers a higher annualized return, and does so with lower annualized volatility.  Additionally, losses have been relatively contained when compared to the benchmark, while periods of outperformance have been instrumental in cumulative performance.

  • Cumulative Returns:  DWAC (+576.80%) vs. GSCI (-18.35%)
  • Annualized Returns:  DWAC (+10.02%) vs. GSCI (-1.01%)
  • Volatility (Annualized):  DWAC (22.23%) vs. GSCI (28.19%)
  • Largest Annual Loss:   DWAC (-20.24% – 1998) vs. GSCI (-46.49% – 2008)
  • Largest Annual Gain:  DWAC (+50.91% – 2006) vs. GSCI (+49.74% – 2000)
  • # Years Outperforming:  DWAC  (12 years) vs. GSCI  (8 years)
  • Total Performance in Outperforming Years:  DWAC (+253.90%) vs. GSCI (+73.11%)2

DWAC inception date: Sept 21, 2016, GSCI inception date: May 7, 2007 – data prior to inception is based on a back-test of the underlying indexes.  Please see the disclosures for important information regarding back-testing.  DWAC returns are calculated on a total return basis.  Returns do not include all potential transaction costs.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

Performance data for the model is the result of hypothetical back-testing.  Performance data for prior to inception date is the result of backtested underlying index data.  Investors cannot invest directly in an index. Indexes have no fees.  Back-tested performance results have certain limitations. Back-testing performance differs from actual performance because it is achieved through retroactive application of an investment methodology designed with the benefit of hindsight. Model performance data as well as back-tested performance do not represent the impact of material economic and market factors might have on an investment advisor’s decision making process if the advisor were actually managing client money. Past performance is not indicative of future results. Potential for profits is accompanied by possibility of loss.

Neither the information nor any opinion expressed shall constitute an offer to sell or a solicitation or an offer to buy any securities, commodities or exchange traded products.  This document does not purport to be complete description of the securities or commodities, markets or developments to which reference is made.  

 

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Weekly RS Recap

October 17, 2016

The table below shows the performance of a universe of mid and large cap U.S. equities, broken down by relative strength decile and quartile and then compared to the universe return.  Those at the top of the ranks are those stocks which have the best intermediate-term relative strength.  Relative strength strategies buy securities that have strong intermediate-term relative strength and hold them as long as they remain strong.

Last week’s performance (10/7/16 – 10/14/16) is as follows:

ranks

This example is presented for illustrative purposes only and does not represent a past or present recommendation.  The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  The performance above is based on pure price returns, not inclusive of dividends, fees, or other expenses.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

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Manager Insights: Third Quarter Review

October 10, 2016

The stock market spent the majority of the summer months moving sideways in a tight trading range.  The S&P 500 finished the quarter up almost 4%, and is sitting on a gain of 7.8% so far this year.  International equity markets were a bright spot, and outperformed domestic markets.  Developed markets finished up 6.5% and Emerging markets finished with a gain of 9.2%.  Bonds also finished in positive territory with a 0.5% gain.  Commodities were a weak spot in the third quarter.  After strong gains in the first six months of the year, the S&P GSCI Commodity Index gave back 4.2% over the summer and now sits at a gain of 5.3% for the year.

We continue to see rotation below the surface in a number of different asset classes.  This is nothing new, but we think the rotations we are seeing now have the potential to be very beneficial to our strategies.  In the U.S. equity markets there has been a momentum shift out of areas such as high dividend and low volatility stocks.  The relentless reach for yield drove many investors into stocks instead of bonds, and drove valuations to historically high levels.  The same valuation issues cropped up in low volatility stocks, which have been quite the hot ticket for the last year or so.  These are not the areas that usually lead a robust bull market.  Low Volatility, especially, tends to lead during down markets.  As a result, there was a lot of hand wringing about how solid the market actually was with that kind of leadership.  We felt the leadership we were seeing was more a result of investor’s preference for yield (and the lack of good fixed income options) rather than an indictment on the overall market.

The new leadership that appears to be emerging is what is traditionally considered positive for a strong bull market.  Small capitalization stocks have had spotty performance for a while, but they really picked up steam in the third quarter.  The Russell 2000 Total Return index finished with a gain of 9% moving it well ahead of the S&P 500 for the year.  Technology stocks also dramatically outperformed what could be considered the old leadership (Utilities, Consumer Staples, and Low Volatility) over the summer.  The relative improvement in these higher volatility areas shows investors are gaining more confidence in the market.  Confidence is an incredibly important piece of the puzzle for momentum strategies so we are looking at this new development very favorably.

The appetite for higher volatility investments is also increasing internationally.  As previously mentioned, Emerging markets had a fantastic third quarter.  Latin America has been the biggest driver of that performance so far this year.  For the past couple of years, international markets have not fared as well as our domestic markets.  That appears to be changing, and we are seeing increasing allocations to Emerging markets in those account styles that allocate internationally and globally.  The overall composition of those portfolios has changed dramatically over the course of the year.

As we head in to the final three months of the year it is impossible not to think about the upcoming election.  Frankly, it is nothing short of a circus sideshow at this point.  We fully understand the uncertainty people feel because neither candidate seems like a good choice.  That, however, is politics, and we are investing.  We encourage you not to get caught up in the headlines.  We do expect some volatility around election time, but we don’t think either candidate’s victory means doom or exuberance for the stock market.  It is incredibly difficult to forecast how politics will affect the market, and most so called experts get it wrong.  Keep your politics out of your investing plan and you will be much better off for it in the long run.  Never forget that there is always some reason not to invest, but the reality is that investing in stocks is a tremendous way to build wealth over time.

The final three months of the year should be interesting to say the least.  There are pieces falling in to place that lead us to believe our relative strength strategies can do quite well if these trends are sustainable.  If you have any questions about any of our strategies please give us a call at any time.

This information is from sources believed to be reliable, but no guarantee is made to its accuracy.  This should not be considered a solicitation to buy or sell any security.  Unless otherwise stated, performance numbers are not inclusive of dividends or fees.  Investors cannot invest directly in an Index.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

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Q4 2016 PowerShares DWA Momentum ETFs

October 10, 2016

The PowerShares DWA Momentum Indexes are reconstituted on a quarterly basis.  These indexes are designed to evaluate their respective investment universes and build an index of stocks with superior relative strength characteristics.   This quarter’s allocations are shown below.

PDP: PowerShares DWA Momentum ETF

pdp

DWAS: PowerShares DWA Small Cap Momentum ETF

dwas

DWAQ: PowerShares DWA NASDAQ Momentum ETF

dwaq

PIZ: PowerShares DWA Developed Markets Momentum ETF

piz

PIE: PowerShares DWA Emerging Markets Momentum ETF

pie

Source: Dorsey Wright, MSCI, Standard & Poor’s, and NASDAQ, Allocations subject to change

We also apply this momentum-indexing methodology on a sector level:

sector-momentum

See www.powershares.com for more information.  

The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.

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Weekly RS Recap

October 10, 2016

The table below shows the performance of a universe of mid and large cap U.S. equities, broken down by relative strength decile and quartile and then compared to the universe return.  Those at the top of the ranks are those stocks which have the best intermediate-term relative strength.  Relative strength strategies buy securities that have strong intermediate-term relative strength and hold them as long as they remain strong.

Last week’s performance (10/3/16 – 10/7/16) is as follows:

ranks-10-10-16

This example is presented for illustrative purposes only and does not represent a past or present recommendation.  The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  The performance above is based on pure price returns, not inclusive of dividends, fees, or other expenses.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

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Adapt or Die

October 4, 2016

The Economist recently pointed out just how much change there has been in the characteristics of the companies that make the list of the top ten market cap companies today versus 2006:

James Manyika, of the McKinsey Global Institute, points out that today’s superstar companies are big in different ways from their predecessors. In the old days companies with large revenues and global footprints almost always had lots of assets and employees. Some superstar companies, such as Walmart and Exxon, still do. But digital companies with huge market valuations and market shares typically have few assets. In 1990 the top three carmakers in Detroit between them had nominal revenues of $250 billion, a market capitalisation of $36 billion and 1.2m employees. In 2014 the top three companies in Silicon Valley had revenues of $247 billion and a market capitalisation of over $1 trillion but just 137,000 employees.

economist

Three of the companies that made the list in 2006 continue to make the list today (Exxon Mobil, General Electric, and Microsoft).  Here’s what I find most interesting about those companies that made the list at the end of 2006—their performance since that time has largely been dismal (with the exception of MSFT).

perf_economist

Microsoft was the only one of the ten to have performance that exceeded that of the S&P 500.  Six of the ten have actually had negative total returns since the end of 2006.  Anyone who thinks it is safe to go with the biggest, most well-known companies for their portfolio would have been unpleasantly surprised by the results.

There is wisdom in the old adage The only constant in life is change.  It’s true!  The markets exemplify this reality every day.  It is for this very reason that the relative strength tools you have at your fingertips with the Dorsey Wright Platform are so essential.  They provide a disciplined way to stay with the relatively strong stocks and seek to avoid the relatively weak stocks.

The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  This example is presented for illustrative purposes only and does not represent a past recommendation.

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September SMA Performance Update

October 1, 2016

Detailed performance of our Systematic Relative Strength Portfolios is shown below.  International, Core, Aggressive, and Balanced added to their margins of outperformance for the year.  We continue to like what we see from a technical perspective with the broad U.S. equity market in a positive trend and above the range of the last couple of years.  We have also seen a strong pick-up in international equity performance—particularly in emerging markets.

sma-perf

To receive the brochure for these portfolios, please e-mail andyh@dorseymm.com or call 626-535-0630.  Click here to see the list of platforms where these separately managed accounts are currently available.

Total account performance shown is total return net of management fees for all Dorsey, Wright & Associates managed accounts, managed for each complete quarter for each objective, regardless of levels of fixed income and cash in each account.  Information is from sources believed to be reliable, but no guarantee is made to its accuracy.  This should not be considered a solicitation to buy or sell any security.  Past performance should not be considered indicative of future results.  The S&P 500 is a stock market index based on the market capitalizations of 500 leading companies publicly traded in the U.S. stock market, as defined by Standard & Poor’s.  The Barclays Aggregate Bond Index is a broad base index, maintained by Barclays Capital, and is used to represent investment grade bonds being traded in the United States.  The 60/40 benchmark is 60% S&P 500 Total Return Index and 40% Barclays Aggregate Bond Index.  The NASDAQ Global ex US Total Return Index is a stock market index that is designed to measure the equity market performance of markets outside of the United States and is maintained by Nasdaq.  The Dow Jones Moderate Portfolio Index is a global asset allocation benchmark.  60% of the benchmark is represented equally with nine Dow Jones equity indexes.  40% of the benchmark is represented with five Barclays Capital fixed income indexes. Each investor should carefully consider the investment objectives, risks and expenses of any Exchange-Traded Fund (“ETF”) prior to investing. Before investing in an ETF investors should obtain and carefully read the relevant prospectus and documents the issuer has filed with the SEC.  ETFs may result in the layering of fees as ETFs impose their own advisory and other fees.  To obtain more complete information about the product the documents are publicly available for free via EDGAR on the SEC website (http://www.sec.gov) There are risks inherent in international investments, which may make such investments unsuitable for certain clients. These include, for example, economic, political, currency exchange, rate fluctuations, and limited availability of information on international securities.

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Systematic Relative Strength Portfolios (SMA/UMA Platforms)

September 28, 2016

Picture1

Our Systematic Relative Strength portfolios are available as separately managed accounts at a large and growing number of firms.

  • Wells Fargo Advisors (Global Macro available on the Masters/DMA Platforms)
  • Morgan Stanley (IMS Platform)
  • TD Ameritrade Institutional
  • UBS Financial Services (Aggressive and Core are available on the MAC Platform)
  • RBC Wealth Management (MAP Platform)
  • Raymond James (Outside Manager Platform)
  • Stifel (Opportunity Platform)
  • Kovack Securities (Growth and Global Macro approved on the UMA Platform)
  • Charles Schwab Institutional (Marketplace Platform)
  • Envestnet UMA
  • Fidelity Institutional
  • Adhesion Wealth

Different Portfolios for Different Objectives: Descriptions of our seven managed accounts strategies are shown below.  All managed accounts use relative strength as the primary investment selection factor.

Aggressive:  This Mid and Large Cap U.S. equity strategy seeks to achieve long-term capital appreciation.  It invests in securities that demonstrate powerful relative strength characteristics and requires that the securities maintain strong relative strength in order to remain in the portfolio.

Core:  This Mid and Large Cap U.S. equity strategy seeks to achieve long-term capital appreciation.  This portfolio invests in securities that demonstrate powerful relative strength characteristics and requires that the securities maintain strong relative strength in order to remain in the portfolio.  This strategy tends to have lower turnover and higher tax efficiency than our Aggressive strategy.

Growth:  This Mid and Large Cap U.S. equity strategy seeks to achieve long-term capital appreciation with some degree of risk mitigation.  This portfolio invests in securities that demonstrate powerful relative strength characteristics and requires that the securities maintain strong relative strength in order to remain in the portfolio.  This portfolio also has an equity exposure overlay that, when activated, allows the account to hold up to 50% cash if necessary.

International: This All-Cap International equity strategy seeks to achieve long-term capital appreciation through a portfolio of international companies in both developed and emerging markets.  This portfolio invests in those securities with powerful relative strength characteristics and requires that the securities maintain strong relative strength in order to remain in the portfolio.  Exposure to international markets is achieved through American Depository Receipts (ADRs).

Global Macro: This global tactical asset allocation strategy seeks to achieve meaningful risk diversification and investment returns.  The strategy invests across multiple asset classes: Domestic Equities (long & inverse), International Equities (long & inverse), Fixed Income, Real Estate, Currencies, and Commodities.  Exposure to each of these areas is achieved through exchange-traded funds (ETFs).

Balanced: This strategy includes equities from our Core strategy (see above) and high-quality U.S. fixed income in approximately a 60% equity / 40% fixed income mix.  This strategy seeks to provide long-term capital appreciation and income with moderate volatility.

Tactical Fixed Income: This strategy seeks to provide current income and strong risk-adjusted fixed income returns.   The strategy invests across multiple sectors of the fixed income market:  U.S. government bonds, investment grade corporate bonds, high yield bonds, Treasury inflation protected securities (TIPS), convertible bonds, and international bonds.  Exposure to each of these areas is achieved through exchange-traded funds (ETFs).

Picture2

To receive fact sheets for any of the strategies above, please e-mail Andy Hyer at andyh@dorseymm.com or call 626-535-0630.  Past performance is no guarantee of future returns.  An investor should carefully review our brochure and consult with their financial advisor before making any investments.

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Dialing Down the Noise

September 27, 2016

The Harvard Business Review’s October 2016 Issue includes a deep look at decision making by authors Kahneman, Rosenfield, Ghandhi, and Blaser.  Their conclusion: “noise”, left unchecked, renders decision making highly inconsistent.

At a global financial services firm we worked with, a longtime customer accidentally submitted the same application file to two offices. Though the employees who reviewed the file were supposed to follow the same guidelines—and thus arrive at similar outcomes—the separate offices returned very different quotes. Taken aback, the customer gave the business to a competitor. From the point of view of the firm, employees in the same role should have been interchangeable, but in this case they were not. Unfortunately, this is a common problem.

Professionals in many organizations are assigned arbitrarily to cases: appraisers in credit-rating agencies, physicians in emergency rooms, underwriters of loans and insurance, and others. Organizations expect consistency from these professionals: Identical cases should be treated similarly, if not identically. The problem is that humans are unreliable decision makers; their judgments are strongly influenced by irrelevant factors, such as their current mood, the time since their last meal, and the weather. We call the chance variability of judgments noise. It is an invisible tax on the bottom line of many companies.

Some jobs are noise-free. Clerks at a bank or a post office perform complex tasks, but they must follow strict rules that limit subjective judgment and guarantee, by design, that identical cases will be treated identically. In contrast, medical professionals, loan officers, project managers, judges, and executives all make judgment calls, which are guided by informal experience and general principles rather than by rigid rules. And if they don’t reach precisely the same answer that every other person in their role would, that’s acceptable; this is what we mean when we say that a decision is “a matter of judgment.” A firm whose employees exercise judgment does not expect decisions to be entirely free of noise. But often noise is far above the level that executives would consider tolerable—and they are completely unaware of it.

The prevalence of noise has been demonstrated in several studies. Academic researchers have repeatedly confirmed that professionals often contradict their own prior judgments when given the same data on different occasions. For instance, when software developers were asked on two separate days to estimate the completion time for a given task, the hours they projected differed by 71%, on average. When pathologists made two assessments of the severity of biopsy results, the correlation between their ratings was only .61 (out of a perfect 1.0), indicating that they made inconsistent diagnoses quite frequently. Judgments made by different people are even more likely to diverge. Research has confirmed that in many tasks, experts’ decisions are highly variable: valuing stocks, appraising real estate, sentencing criminals, evaluating job performance, auditing financial statements, and more. The unavoidable conclusion is that professionals often make decisions that deviate significantly from those of their peers, from their own prior decisions, and from rules that they themselves claim to follow.

My emphasis added.  Among the author’s proposed solutions to the “noise” problem was the was following:

The most radical solution to the noise problem is to replace human judgment with formal rules—known as algorithms—that use the data about a case to produce a prediction or a decision. People have competed against algorithms in several hundred contests of accuracy over the past 60 years, in tasks ranging from predicting the life expectancy of cancer patients to predicting the success of graduate students. Algorithms were more accurate than human professionals in about half the studies, and approximately tied with the humans in the others. The ties should also count as victories for the algorithms, which are more cost-effective.

This will sound very similar to advice that Dorsey Wright has been giving for many years: Embrace models!  Try as we might to be consistent, without the framework of a systematic investment model, our own subjective decision making will be all over the place.  Then, how can we tell if our investment success or failure is the result of skill or just good or bad luck?  Of course, you can’t simply blindly adhere to just any systematic investment model.  The decision rules upon which the model has been built must stack the odds in your favor.  Extensive testing, as is detailed here, has give us the necessary input to build systematic relative strength strategies that “dial down the noise” and allow us to focus on execution of a well-designed investment process.

Focus on the process and the results will take care of themselves.

The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.

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Weekly RS Recap

September 26, 2016

The table below shows the performance of a universe of mid and large cap U.S. equities, broken down by relative strength decile and then compared to the universe return.  Those at the top of the ranks are those stocks which have the best intermediate-term relative strength.  Relative strength strategies buy securities that have strong intermediate-term relative strength and hold them as long as they remain strong.

Last week’s performance (9/19/16 – 9/23/16) is as follows:

ranks

This example is presented for illustrative purposes only and does not represent a past or present recommendation.  The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  The performance above is based on pure price returns, not inclusive of dividends, fees, or other expenses.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

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Relative Strength Spread

September 22, 2016

The chart below is the spread between the relative strength leaders and relative strength laggards (top quartile of stocks in our ranks divided by the bottom quartile of stocks in our ranks; universe of U.S. mid and large cap stocks).  When the chart is rising, relative strength leaders are performing better than relative strength laggards.    As of 9/21/16:

spread

The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

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Momentum & Value vs. Growth & Value

September 20, 2016

At Dorsey Wright, we believe momentum can be used as a stand-alone investment strategy, however, combining it with other smart beta factors to which momentum is negatively correlated has its advantages.  We have referenced this in previous blog posts, noting that it allows for a portfolio to capture alpha at different periods of the market cycle, which in turn can reduce both drawdowns and volatility.   In this post we would like to discuss the potential benefits of combining momentum with value versus combining growth and value.   Furthermore, we will take a look the correlation of excess returns for each portfolio, and wrap things up by comparing the returns of each.

To begin, let’s take a look at the side by side performance (annual figures) for the products we will be using in our study:  PowerShares DWA Momentum Portfolio PDP, Russell 1000 Growth Index RLG, and the Guggenheim S&P 500 Pure Value ETF RPV.  We can reference this table in comparison to the results we get when combining the smart beta factors we mentioned earlier.  In order to get proper historical data, we used the underlying index (total return) for both RLG and RPV.  For PDP, total return figures were used starting on 3/1/2007.  The table below confirms that when using each of these products as a stand-alone investment product.  As we can see, momentum outperforms all other factors but also at a slightly elevated volatility.   Perhaps the most surprising theme is the underperformance of the growth factor throughout this time frame.

all

PDP inception date: March 1, 2007, RLG inception date: May 22, 2000, RPV inception date:   March 1, 2006 – data prior to inception is based on a back-test of the underlying indexes.   Please see the disclosures for important information regarding back-testing.  PDP returns do not include dividends prior to 3/1/2007.  Returns do not include all potential transaction costs.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss. 

Next, let’s take a look at the correlation coefficients when comparing the returns of each portfolio.  Below we’ve plotted the returns of each portfolio against each other on a year-to-year basis.   The correlation of excess returns between PDP and RPV came out to be -.50 during this time period, just slightly better then RLG vs. RPV (which registered -.40).   Again, both of these are impressive in terms of negative correlation which hopefully will give us the ability to capture alpha at different areas of the market cycle once we construct our portfolios.   Typcially our goal in doing this is lowering portfolio volatility and reducing max drawdowns when compared to using them as stand alone investments.

pdp-vs-rpv

PDP inception date: March 1, 2007, RLG inception date: May 22, 2000, RPV inception date:   March 1, 2006 – data prior to inception is based on a back-test of the underlying indexes.   Please see the disclosures for important information regarding back-testing.  PDP returns do not include dividend prior to 3/1/2007.  Returns do not include all potential transaction costs.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss. 

rlg-vs-rpv

PDP inception date: March 1, 2007, RLG inception date: May 22, 2000, RPV inception date:   March 1, 2006 – data prior to inception is based on a back-test of the underlying indexes.   Please see the disclosures for important information regarding back-testing.  PDP returns do not include dividend prior to 3/1/2007.  Returns do not include all potential transaction costs.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.  

In conclusion, the portfolios we will construct are going to be based on a static allocation of 70%/30%.  To clarify, both the momentum and growth allocations will remain at 70%, while the value portion will be 30%.  The portfolios are re-balanced annually (although as we mentioned the allocation will remain static).    Looking at the table below, we can see that the momentum/value combination portfolio outperformed has over the growth/value combination.   The returns are nearly double, while volatility remains the same at 22%.   Market participants looking to combine a portion of their value portfolio with another allocation would certainly seem to benefit by using a momentum product vs. a growth product.

summary

PDP inception date: March 1, 2007, RLG inception date: May 22, 2000, RPV inception date:   March 1, 2006 – data prior to inception is based on a back-test of the underlying indexes.   Please see the disclosures for important information regarding back-testing.  PDP returns do not include dividend prior to 3/1/2007.  Returns do not include all potential transaction costs.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss. 

DWA provides the underlying index for PDP (discussed above) and receives licensing fees from Invesco PowerShares based on assets invested in the Fund.

Some information presented is the result of a strategy back-test.  Back-tests are hypothetical (they do not reflect trading in actual accounts) and are provided for informational purposes to illustrate the effects of the strategy during a specific period.  Back-tested results have certain limitations.  Such results do not represent the impact of material economic and market factors might have on an investment advisor’s decision making process if the advisor were actually managing client money.  Back-testing also differs from actual performance because it is achieved through retroactive application of a model investment methodology designed with the benefit of hindsight.  

Neither the information within this email, nor any opinion expressed shall constitute an offer to sell or a solicitation or an offer to buy any securities, commodities or exchange traded products.  This article does not purport to be complete description of the securities or commodities, markets or developments to which reference is made. 

The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  Relative Strength is a measure of price momentum based on historical price activity.  Relative Strength is not predictive and there is no assurance that forecasts based on relative strength can be relied upon.

 

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Small Caps On the Move

September 19, 2016

One of the simplest ways to determine the relative strength of small caps versus large caps is to use the SmartChart function to divide IWM (or another small cap ETF or index) by SPX.  As shown below, large caps generally had the better relative strength in 2014 and 2015, as reflected by the declining RS chart, but it has been a different story in 2016.  We have seen a series of higher highs and higher lows on the relative strength chart in 2016 as small cap indexes like the Russell 2000 have generally performed better than large caps.

iwm-vs-spx

Small cap momentum, however, had a slow start in the first half of the year, generally underperforming cap weighted small cap indexes like the Russell 2000.  However, it looks like that may be changing.  Our PowerShares DWA Small Cap Momentum ETF (DWAS) has pulled ahead of IWM so far in Q3 and both DWAS and IWM are well ahead of the S&P 500 for the quarter as shown in the table below.

qtd_dwas_iwm_spx

Source: Dorsey Wright.  *7/1/16 – 9/8/16.  Price return only, not inclusive of dividends or transaction costs.

A quick review of the index construction process for The PowerShares DWA Small Cap Momentum ETF (DWAS):

  • Holds 200 stocks out of a universe of approximately 2,000 small cap stocks
  • Stocks are selected for this index based on PnF relative strength characteristics
  • The index is weighted by relative strength so that out of the 200 stocks that make it into the index, those with the better relative strength get the most weight
  • Rebalanced quarterly to remove any stocks that have lost sufficient relative strength and to replace them with stronger stocks

Among the things that we can control in this index construction process is to make sure that the process remains the same from one quarter to the next.  All 200 stocks meet the necessary relative strength requirements to go into the index when it is rebalanced.  Each quarter we see that some of those holdings continue to perform well and some of them don’t.  Shown below is the quarter to date performance for the 200 holdings in DWAS so far in Q3.

dispersion_dwas

Source: Dorsey Wright. *7/1/16 – 9/8/16.  Price return only, not inclusive of dividends or transaction costs.

The best performing holding is +162% and the worst performing holding is -34% so far this quarter.  As is true each quarter, those stocks that maintain favorable relative strength will stay in the index and those that have sufficiently deteriorated will get replaced.

With U.S. equities ranked number 1 in DALI and with small caps showing improving relative strength, this may be an area that deserves some consideration.

Dorsey Wright is the index provider for a suite of momentum ETFs, including DWAS, at PowerShares.  See www.powershares.com for more information.  The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.

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Hedgeweek: Using Momentum to Invest in ADRs

September 13, 2016

Great new article by John Lewis in Hedgeweek:

American Depositary Receipts are an effective way for US investors to gain exposure to international stocks. Dorsey, Wright & Associates’ John Lewis explains how using a momentum strategy can prove effective in building the right exposure to this instrument class.

Read the full article here.

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Weekly RS Recap

September 12, 2016

The table below shows the performance of a universe of mid and large cap U.S. equities, broken down by relative strength decile and quartile and then compared to the universe return.  Those at the top of the ranks are those stocks which have the best intermediate-term relative strength.  Relative strength strategies buy securities that have strong intermediate-term relative strength and hold them as long as they remain strong.

Last week’s performance (9/6/16 – 9/9/16) is as follows:

ranks

This example is presented for illustrative purposes only and does not represent a past or present recommendation.  The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  The performance above is based on pure price returns, not inclusive of dividends, fees, or other expenses.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

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It’s All At The Upper End

September 7, 2016

Almost all of the performance from a relative strength or momentum model comes from the upper end of the ranks.  We run different models all the time to test different theories or to see how existing decision rules work on different groups of securities.  Sometimes we are surprised by the results, sometimes we aren’t.  But the more we run these tests, the more some clear patterns emerge.

One of these patterns we see constantly is all of the outperformance in a strategy coming from the very top of the ranks.  People are often surprised at how quickly any performance advantage disappears as you move down the ranking scale.  That is one of the things that makes implementing a relative strength strategy so difficult.  You have to be absolutely relentless in pushing the portfolio toward the strength because there is often zero outperformance in aggregate from the stuff that isn’t at the top of the ranks.  If you are the type of person that would rather “wait for a bounce” or “wait until I’m back to breakeven,” then you might as well just equal-weight the universe and call it a day.

Below is a chart from a sector rotation model I was looking at recently.  This model uses the S&P 500 GICS sub-sectors and the ranks were done using a point & figure matrix (ie, running each sub-sector against every other sub-sector) and the portfolio was rebalanced monthly.  You can see the top quintile (ranks 80-100) performs quite well.  After that, good luck.  They are all clustered together well below the top quintile.

matrix ranks

This is a constant theme we see.  The very best sectors, stocks, markets, and so on drive almost all of the outperformance.  If you miss a few of the best ones it is very difficult to outperform.  If you are unwilling to constantly cut the losers and buy the winners because of some emotional hangup, it is extremely difficult to outperform.  The basket of securities in a momentum strategy that delivers the outperformance is often smaller than you think, so it is crucial to keep the portfolio focused on the top-ranked securities.

The returns used within this article are the result of a back-test using indexes that are not available for direct investment.  Returns do include dividends, but do not include transaction costs.  Back-tested performance is hypothetical (it does not reflect trading in actual accounts) and is provided for informational purposes to illustrate the effects of the discussed strategy during a specific period.  Back-tested performance results have certain limitations.  Such results do not represent the impact of material economic and market factors might have on an investment advisor’s decision making process if the advisor were actually managing client money.  Back-testing performance also differs from actual performance because it is achieved through retroactive application of a model investment methodology designed with the benefit of hindsight.  Dorsey, Wright & Associates believes the data used in the testing to be from credible, reliable sources, however; Dorsey, Wright & Associates, LLC (collectively with its affiliates and parent company, “DWA”) makes no representation or warranties of any kind as to the accuracy of such data. Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

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Weekly RS Recap

September 6, 2016

The table below shows the performance of a universe of mid and large cap U.S. equities, broken down by relative strength decile and quartile and then compared to the universe return.  Those at the top of the ranks are those stocks which have the best intermediate-term relative strength.  Relative strength strategies buy securities that have strong intermediate-term relative strength and hold them as long as they remain strong.

Last week’s performance (8/29/16 – 9/2/16) is as follows:

ranks 09.06.16

This example is presented for illustrative purposes only and does not represent a past or present recommendation.  The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  The performance above is based on pure price returns, not inclusive of dividends, fees, or other expenses.  Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.

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AADR Investor Conference Call Recording

September 1, 2016

AADR Investor Conference Call Recording – Please click here to listen to John Lewis, Senior Vice President at Dorsey, Wright and Associates, who serves as AADR’s portfolio manager discuss the fund’s investment strategy in detail.

Click here for the press release detailing the announcement that Dorsey Wright was recently named the sub-advisor of this ETF.

See www.advisorshares.com for more information.

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Dividend-Paying Stocks: Getting a Broader Picture

September 1, 2016

Among the biggest investor-driven trends in the market right now is the thirst for yield.  The paltry yields available in most sectors of fixed income just are not providing the type of income that investors are looking for and so they are increasingly looking at earning that yield from dividend-paying stocks.  However, an exclusive focus on yield provides an incomplete picture of the returns that an investor may achieve.  There is also the performance of the stock itself that must be factored into the evaluation.

When we rank our universe of securities to construct the First Trust Dorsey Wright Dividend UITs, our relative strength ranks are determined by the total return of the stocks (price return + yield).  For comparison’s sake, consider the construction methodology of the S&P Dividend SPDR (SDY) which is based upon the S&P High Yield Dividend Aristocrats Index.  That index is designed to measure the performance of the highest dividend yielding S&P Composite 1500  Index constituents that have followed a managed-dividends policy of consistently increasing dividends every year for at least 20 consecutive years.

In the table below, I show the top 10 holdings for both SDY and for the First Trust Dorsey Wright Relative Strength Dividend UIT, Series 22.  While the top 10 holdings for SDY have a slightly higher yield, the top 10 holdings of the Dorsey Wright UIT have had better total returns over the past 12 months.

uit_sdy

*DWA Top 10 is the top 10 holdings in the First Trust Dorsey Wright Relative Strength Dividend Top 50 UIT, Series 22.  Performance 8/24/15 – 8/24/16.  Source: Yahoo! Finance.  Returns are inclusive of dividends, but do not include any transaction costs.

Evaluating dividend-paying stocks from a total return perspective seems to be fairly uncommon, yet it can make a significant difference in performance for the client while still allowing them to seek above-market yields.

Past performance is not indicative of future results.  Potential for profits is accompanied by possibility of loss.  See http://www.ftportfolios.com for more information.

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