Dull Market? Not in Small Caps

August 23, 2016

When investors sit down with their financial advisor to construct an asset allocation, international equities are typically one of the major asset classes considered for a meaningful portion of the allocation.  When it comes to determining how you are going to get that international equity exposure, there are no shortage of options.  Among the most popular is to simply invest in a cap-weighted index fund like the iShares MSCI EAFE (EFA).  However, as shown below EFA hasn’t made a whole lot of progress over the past year.  Keep in mind that the MSCI EAFE, like all cap-weighted indexes, are driven by the mega-cap stocks in the index.  In environments when the large and mega caps are doing well, an index such as this may be a great choice.

efa

8/17/15-8/17/16

However, investors may wish to see if there are better returns in some of the mid or smaller cap international companies.  To get a sense of where the best returns in international equities have come over the past year, we ran a query of ADRs from FactSet that trade at least $1MM USD per day on average.  That gave us a list of 269 stocks with a market cap ranging from $261,353 MM to $362 MM.  This is the USD market cap for the Underlying (or the Primary Security).  All of the primary securities trade on foreign exchanges so the Market Cap numbers have all been brought back to USD so everything is apples to apples.  I then broke the group of ADRs into thirds by market cap and looked at the trailing 12 month returns of the stocks.  In the table below you will see the average, median, minimum, and maximum return for stocks in each of those thirds.

trailing 12

Source: FactSet.  8/17/15-8/17/16.  Returns are inclusive of dividends, but do not include transaction costs.

Where has the action been over the past year?  Clearly, the best returns have come from the smaller companies.  A cap-weighted international equity benchmark isn’t going to do a whole lot for you there.

When advisors ask why it is that our Systematic RS International portfolio has done as well as it has, part of the answer is that we can invest in small, mid, and large cap ADRs.  Some quick facts on our Systematic RS International portfolio:

  • Inception 3/31/2006.
  • Reached a 10-year track record in March of this year.
  • Can invest in small, mid, and large cap ADRs from both developed and emerging international markets
  • Holds 30-40 ADRs.
  • Buys securities out of the top quartile of our ranks and sells them when they fall out of the top half of our ranks
  • Allocations are determined by relative strength
  • Available on over 15 SMA platforms, including Stifel, RBC, and Raymond James.

See below for the performance of the strategy over time:

intl 1

intl 2

As of 7/31/16

This portfolio is available as a separately managed account and a unified managed account at a number of firms.  To receive the fact sheet for this portfolio, please e-mail andyh@dorseymm.com or call 626-535-0630.

1The performance represented in this brochure is based on monthly performance of the Systematic Relative Strength International Model.  Net performance shown is total return net of management fees, commissions, and expenses 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.  The advisory fees are described in Part 2A of the adviser’s Form ADV.  The starting values on 3/31/2006 are assigned an arbitrary value of 100 and statement portfolios are revalued on a trade date basis on the last day of each quarter.  All returns since inception of actual Accounts are compared against the NASDAQ Global ex US Index.  The NASDAQ Global ex US Index Total Return Index is a stock market index that is designed to measure the equity market performance of global markets outside of the United States and is maintained by Nasdaq.  The performance information is based on data supplied by the Manager or from statistical services, reports, or other sources which the Manager believes are reliable.  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.  Past performance does not guarantee future results. In all securities trading, there is a potential for loss as well as profit. It should not be assumed that recommendations made in the future will be profitable or will equal the performance as shown. Investors should have long-term financial objectives when working with Dorsey, Wright & Associates.

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Weekly RS Recap

August 22, 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 (8/15/16 – 8/19/16) 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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High RS Diffusion Index

August 17, 2016

The chart below measures the percentage of high relative strength stocks (top quartile of our ranks) that are trading above their 50-day moving average (universe of mid and large cap stocks.)  As of 8/16/16.

diffusion

The 10-day moving average of this indicator is 78% and the one-day reading is 67%.

The relative strength strategy is NOT a guarantee.  There may be times where all investments and strategies are unfavorable and depreciate in value.  Investors cannot invest directly in an index.  Indexes have no fees.  Past performance is no guarantee of future returns.  Potential for profits is accompanied by possibility of loss.

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Something for the Pitch Book

August 16, 2016

Brian Pornoy, Director of Investor Education at Virtus, recently included the following thought-provoking chart in his commentary titled What Does the Stock Market Owe You?:

BP blog 6_23

The chart encompasses daily snapshots of the total return (i.e., dividends included) of the S&P 500®, a broad index of U.S. stocks, from 1928 until today. Reading the picture from left to right, what you’re looking at are “rolling” time periods of increasing duration. A rolling time period thinly slices our windows on market returns over whatever period we choose to define them. So, for example, a rolling three-year period could be the market returns from November 1, 1953 to October 31, 1956. The next three-year period would be November 2, 1953 to November 1, 1956. And so on. I looked at the rolling returns over periods ranging from one to ten years in length. All in, it encompasses tens of thousands of observations.

Pornoy’s conclusion were as follows:

  • Notice that the average return over these different periods is remarkably consistent. It’s about 10%. Not surprisingly, many people reflexively believe that “the market” returns about 10% per year. They’re not whistling Dixie. Based on history, that’s about right.
  • Yet that mode of thinking—asking “what’s the average?”—reflects the brain’s bias toward locking onto specific point estimates. We prefer to fixate on a precise number and reject, often subconsciously, thinking in statistical, probabilistic terms. In other words, we don’t naturally play the odds. Sure, to say instead that the market returns “about 8-12%” per year is a baby step in the right direction. Unfortunately the world is much messier than that. The following observations, therefore, force us out of our comfort zone, as they force us to think in terms of dynamic ranges and probabilities.
  • For each of the rolling periods, I show the maximum and minimum returns: the biggest gains and the biggest losses. Thus, over thousands of rolling one-year periods going back to 1928, the largest one-year gain was 171% and the largest one-year loss was -71%. This range is massive. (Note that the most extreme results occurred during the 1930s.)
  • What this tells us is clear: In the short term (please forget days and months, even a year counts as short term), stock market returns are extremely volatile; they are basically random. The fact that the rolling one-year “average” is around 11% tells you nearly nothing about what the market can and will deliver you. Over the past century, we’ve seen one-year periods when some investors nearly tripled their money, while others lost more than two-thirds of it.

Those investors/pundits who are predisposed to be bullish can use data such as this to argue for aggressive allocations.  After all, what’s not to like about those average and max returns!  Those investors/pundits who are predisposed to be bearish can use the same data to argue for conservative allocations.  The latter group will simply focus on the worst outcomes over those rolling time periods.

It also occurs to me that an advisor who has embraced Dorsey Wright into their practice could use that chart to demonstrate to a client or prospect the value that they can bring to the table.  We all know what the market has done in the past.  From that history, we can clearly observe the massive degree of variability.  Armed with that knowledge, I’m not sure how many investors will continue to be fully comfortable with a strategic approach to asset allocation that offers little flexibility.

Something to consider adding to the pitch book.

Past performance is no guarantee of future returns.  Dorsey Wright is a research provider to Virtus.

HT: Abnormal Returns

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Relative Strength Spread

August 16, 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 8/15/16:

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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Weekly RS Recap

August 15, 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 (8/8/16 – 8/12/16) 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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Quote of the Week

August 9, 2016

“More investors don’t copy our model because our model is too simple. Most people believe you can’t be an expert if it’s too simple.” ~Charlie Munger when asked why more investors hadn’t copied Berkshire Hathaway’s approach to investing[1]

HT: The Cordant Blog / Abnormal Returns

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Replay of Webinar on Systematic RS Portfolios

August 8, 2016

Click here for a replay of the August 8th webinar on our Systematic RS Portfolios with Andy Hyer.

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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Home Country Bias – A Global Phenomenon

August 8, 2016

A recent Vanguard research piece highlights the prevalence of home country bias:

home

Cullen Roche’s take:

What this chart is showing is that every country has a home bias. So, if you’re an American investor you tend to hold mostly domestic stocks. If you’re a Japanese investor you tend to hold mostly Japanese stocks. So on and so forth. And what’s crazy to think here is that you’re literally just buying stocks from one country because you were born there and for whatever reason, you think that’s the only country whose stocks you should own. Of course, we should know better.

The empirical research (see Aness 2011 & Vanguard 2006) clearly shows that international diversification works. And it works for the same reasons that domestic diversification works. Basically, by owning a bigger pool of assets you reduce specific risks within your domestic economy such as domestic economy risk and currency risk.

A great example of this is Japan. One of the great worries every investor has is falling into the Japan trap where you undergo 20 years of stagnant or negative returns. As I noted in “The Importance of Global Asset Allocation“, it’s imperative that investors diversify abroad to avoid such a risk. Yet almost every domestic investor has an overweight in their domestic economy.

It just shows that irrational investing persists despite the well founded empirical evidence that shows how risky home bias can be.

For a variety of reasons, investors are just more comfortable with what they know even though international exposure has the potential to be a valuable part of their overall portfolio.  However, investors in relative strength strategies may take some measure of comfort in looking at an international equity strategy that employs a portfolio management process that they are familiar with, but just applies it to an international equity universe.  For that reason, investors may want to consider our Systematic RS International portfolio.  The portfolio management rules used for this portfolio are similar to the rules we use for some of our domestic equity portfolios.  We rank a universe of securities by their relative strength, buy stocks out of the top quartile of our ranks and sell them when they fall out of the top half of our ranks.  What is different is that rather than evaluating a universe of U.S. mid and large cap stocks, our model is evaluating a universe of about 500 ADRs from both developed international markets and emerging markets.  This portfolio just reached a 10-year track record earlier this year and we are very proud of the results.  Performance details shown below:

intl perf

intl perf 2

As of 7/31/16

This portfolio is available as a separately managed account and a unified managed account at a number of firms.  If your clients fall into the category of investors who need to beef up their international equity exposure this may be a solution that they can get excited about.  To receive the fact sheet for this portfolio, please e-mail andyh@dorseymm.com or call 626-535-0630.

1The performance represented in this brochure is based on monthly performance of the Systematic Relative Strength International Model.  Net performance shown is total return net of management fees, commissions, and expenses 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.  The advisory fees are described in Part 2A of the adviser’s Form ADV.  The starting values on 3/31/2006 are assigned an arbitrary value of 100 and statement portfolios are revalued on a trade date basis on the last day of each quarter.  All returns since inception of actual Accounts are compared against the NASDAQ Global ex US Index.  The NASDAQ Global ex US Index Total Return Index is a stock market index that is designed to measure the equity market performance of global markets outside of the United States and is maintained by Nasdaq.  The performance information is based on data supplied by the Manager or from statistical services, reports, or other sources which the Manager believes are reliable.  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.  Past performance does not guarantee future results. In all securities trading, there is a potential for loss as well as profit. It should not be assumed that recommendations made in the future will be profitable or will equal the performance as shown. Investors should have long-term financial objectives when working with Dorsey, Wright & Associates.

 

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Relative Strength Spread

August 2, 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 8/1/16:

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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Q&A with John Lewis, CMT

August 1, 2016

John Lewis is the Senior Portfolio Manager at Dorsey Wright.  Since joining Dorsey Wright in 2002, Mr. Lewis has developed strategies for the firm’s Systematic series of separate accounts, the Technical Leaders Index methodology, global asset allocation strategies, and multiple series of UITs. His work is technically driven and focuses on relative strength and momentum as the main factors in the investment process.

Q: What is the role that computer programming plays in your portfolio management responsibilities?

A:  Computers play an integral part in designing new strategies and maintaining existing ones.  We have designed a ton of different investment processes over the years and we have done so much testing that we have a pretty good idea of what will and won’t work and how to integrate that into a portfolio.  That knowledge base is really invaluable and is really the most important part of the process.  But we can harness the power of the computer to validate and stress test all of those ideas.  We are able to run tens of thousands of tests if we need to in order to make sure our ideas have merit.  On an ongoing basis, our strategies are designed to be systematic so using a computer to do all of the calculations for us is a huge time saver and allows us to run a large number of strategies with minimal human capital.

Q: How did you develop those computer programming skills?

A:  This story is 100% true.  I was working in San Diego and part of my job function required me to stay later than everyone else to get data loaded into our systems for the next trading.  All of my friends on the floor were leaving early (remember, the market closes at 1:00 on the West Coast) to go to the beach, golfing, or whatever, and it was always difficult for me to cut out a little early.  When faced with such a large problem it often takes drastic measures to solve it.  So I taught myself how to program visual basic and I set up a bunch of Excel macros to run stuff while I was out of the office.  It would up working really well so I just kept going and figuring stuff out along the way.  Computer programming has always been pretty easy for me, and I have had any formal training or anything like that.  The result of that decision to teach myself how to program in order to leave work early was the launching pad to what we are doing today.  However, my golf game is still terrible and my beach body has rapidly become something that shouldn’t be allowed on the beach.

Q: What led to the development of the family of Systematic Relative Strength portfolios (separately managed accounts)?

A: We did a review of our portfolios and tried to figure out what was working and what wasn’t.  As we dug deeper into the data it became clear that relative strength was really driving the performance and not any of the other “stuff” that went into the decision making.  Our testing process actually led us down a totally different path than how most things get tested.  We started with a bunch of inputs and kept whittling down the list.  Instead of finding something that worked and trying to add additional things to the model, we kept asking ourselves if we could accomplish the same goal with fewer things in the model.  The more streamlined you make a model the more robust it should be over time.  There are fewer things to break.  Whenever we talk about the process for our portfolios, people seem to think we aren’t as sophisticated as other managers who use a bunch of different factors and constantly reoptimize them.  But the fact of the matter is that we have computers too and we could do that if we wanted to.  There is a very elegant simplicity to how we set up our models, and sometimes that is actually harder to accomplish than making something that is very complex.

Q: Many in the industry argue for multi-factor investment models.  The family of Systematic Relative Strength portfolios employs just one input—relative strength.  Why?

A: Relative Strength (momentum) is one of the premier investment factors out there.  Our expertise lies in building and implementing investment processes using momentum.  That is really where our edge is so we try to exploit that as best as we can.  Over the years we have gained a lot of experience in using other factors along with momentum so you have probably seen us write about other factors, but they are still centered around relative strength.  Momentum is a great factor, it is very objective, and it lends itself very well to the type of systematic models we are good at building.

Q: Of the 7 strategies in the family of Systematic Relative Strength portfolios, one can’t help but take note of the International portfolio.  Is there anything unique about the way that this strategy is managed that may have contributed to its success?

A:  The International strategy uses a universe of ADR’s.  It is one of our smaller strategies in terms of assets under management, but one of our best performers.  The ADR universe is very unique.  There is a ton of dispersion in that universe meaning there are a lot of stocks that have tremendous performance and others that have dreadful performance.  That is great for any relative strength strategy.  In addition, it is a very flexible strategy so we can swing the allocation between developed and emerging whenever we need to.  The ADR strategy is really unique and now that we have a 10 year live track record under our belt I would not be surprised to see interest in that strategy pick up dramatically in the coming years.

Q: What is the trade-off investors face when they choose between our Aggressive, Core, and Growth portfolios, all of which invest in U.S. mid and large cap equities?

A:  It is a classic risk and return tradeoff.  The Aggressive strategy is the most aggressive application of momentum.  That means it has more turnover, more volatility, and over long periods of time higher potential return.  However, it can go quite a while underperforming the other strategies if we aren’t in a good momentum market.  The difference between Core and Growth really comes down to the cash component.  We can raise cash in the Growth portfolio if necessary.  Obviously, that is very beneficial in down markets, but can result in lagging performance in up markets.  All three of those strategies have done well despite not having a real good momentum environment for a while.

Q: Our most popular separately managed account by assets continues to be our Global Macro portfolio.  Why do you think this portfolio has seen so much demand?

Global Macro is a very flexible global tactical asset allocation strategy.  This appeals to a lot of investors because it is so difficult to determine where the best returns will be in the future.  A strategy like global macro just goes to where the momentum is and can invest in a number of different asset classes.  If equities are doing well, we are overweight there.  If things shift and commodities start doing well the portfolio will shift along with it.  What is also appealing is the disciplined application of the process.  Making global trend predictions is darn near impossible.  We know that so we don’t even try to do it.  We are wrong a lot, but the goal is not to stay wrong.  We don’t paint ourselves into a corner and hold on to a prediction we made.  We just position the portfolio to wherever the strength is and make changes when that strength changes.  That is a very appealing way to capitalize on global trends in a very uncertain environment.

To receive the brochure for our Systematic Relative Strength portfolios, please e-mail andyh@dorseymm.com or call 626-535-0630.

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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July SMA Performance Update

August 1, 2016

The broad U.S. equity market moved through resistance to all-time highs in July.  International equity markets also had a strong month.   All 7 of our Systematic RS portfolios made gains for the month and most all remain well ahead of their benchmarks for the year.  See detailed performance below.

Also, click here for a Q&A with our Senior Portfolio Manager, John Lewis, CMT.

July performance

To receive the brochure for these portfolios, please e-mail andy@dorseywright.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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Weekly RS Recap

August 1, 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 (7/25/16 – 7/29/16) 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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Managing Lumpy

July 26, 2016

Ben Carlson highlights perhaps the single biggest frustration for investors:

The thing is, stock market returns have always been lumpy. Historical returns always look great on paper, but the actual experience of living through them is never really close to the average results. Average is typically the exception, not the rule.

He used the following chart to illustrate just how lumpy the returns in the S&P 500 have been over time:

S&P 500

Yet, the S&P 500 TR Index had 9.5% annualized return over this time frame.  What’s not to like about those average results?

This makes me think of the following visual depiction of the same reality:

reality

Source: Twitter, @ThinkingIp

Perhaps some clients can be coached into a passive long-term buy and hold approach to investing and can avoid buying high and selling low.  However, for many investors, the lumpy nature of the markets is just too much for them to handle.  Such basics as diversification by asset class and by strategy can help smooth out the ride.

We have found that there is also a place for a strategy that has the ability to raise cash to try to help buffer some of the market downturns.  Psychologically, this can help as clients tend to take comfort in knowing that there is some ability to play defense in their portfolio.  One of the seven strategies in our family of Systematic Relative Strength portfolios is called Growth and this portfolio invests in 20-25 U.S. mid and large cap equities when it is fully invested.  However, it also has the ability to raise up to 50 percent cash in the portfolio when market conditions dictate.

Over time, the performance of the strategy has been better than that of the S&P 500, with less volatility than the S&P 500:

growth 07.14.16

growth stats

Ultimately, good financial advisors help their clients successfully navigate the “lumpiness” of market returns though a combination of coaching/hand holding as well as designing an asset allocation that will create a risk/return experience that the clients can handle.  If you think your clients could benefit from making our Growth portfolio part of that plan, please contact Andy Hyer at 626-535-0630 or andyh@dorseymm.com.  Our family of Systematic Relative Strength portfolios are available on a large and growing number of SMA and UMA platforms.

The performance represented above is based on monthly performance of the Systematic Relative Strength Growth Model.  Net performance shown is total return net of management fees, commissions, and expenses 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.  The advisory fees are described in Part 2A of the adviser’s Form ADV.  The starting values on 12/31/2006 are assigned an arbitrary value of 100 and statement portfolios are revalued on a trade date basis on the last day of each quarter.  All returns since inception of actual Accounts are compared against the S&P 500 Index.  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 performance information is based on data supplied by the Manager or from statistical services, reports, or other sources which the Manager believes are reliable.  Past performance does not guarantee future results. In all securities trading, there is a potential for loss as well as profit. It should not be assumed that recommendations made in the future will be profitable or will equal the performance as shown. Investors should have long-term financial objectives when working with Dorsey, Wright & Associates.

 

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Weekly RS Recap

July 25, 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 (7/18/16 – 7/22/16) is as follows:

ranks

Performance by sector for the week is shown below:

sector 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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Sector Performance

July 22, 2016

The table below shows performance of US sectors over the trailing 12, 6, and 1 month(s).  Performance updated through 7/21/16.

sector

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.  Source: iShares

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Combining Different Momentum Factors

July 18, 2016

Momentum can be calculated in a number of different ways.  As long as you are measuring the strength of price appreciation over an intermediate time horizon most logical calculation methods will work to one degree or another.  The standard, academic definition of momentum usually means taking the price appreciation of a security over a predefined time period and comparing it to all of the other securities in the universe.  It is common to use a 12 month window to calculate the price appreciation, but 6 and 9 months are also used.  (Note: most academic studies “skip” the most recent month to account for short-term mean reversion, but we will not address that here).  You can also calculate momentum using moving averages, slopes of regression lines, and point and figure relative strength charts.  There is no one right way to calculate momentum that will guarantee you better performance in the future.  This is similar to value investing.  There is no one correct way to determine a company’s intrinsic value and analysts use a lot of different tools to arrive at their valuations.

No matter what calculation method you choose it will have strengths and weaknesses.  What we want to look at here is using a combination of momentum calculations that have different strengths and weaknesses to improve the overall ranking system.  Two such calculation methods are the moving time window approach and point and figure relative strength.  The moving time window approach is very dependent on time.  If you are using a 12 month window, what happened 12 months plus one day ago makes no difference in the calculation.  In addition, anything that happens between those two points is also irrelevant.  All that matters is the distance from point A to point B.  Point and figure, on the other hand, removes time and only focuses on the volatility of ratio between a security’s price and an underlying benchmark.  That volatility can take place at any time in history and it will be reflected in the point and figure chart.  We have written several whitepapers on point and figure relative strength which you can access here if you want to learn more.

One challenge with any time window based approach is what to do with securities that have been extremely strong that begin to underperform.  Usually a system is set up to own securities from the top 10% or 20% or the ranks and sell them when the fall below a given threshold.  But it may take a tremendous amount of underperformance to actually fall out of the top of the ranks.  In the following example, NVIDIA Corp is up about 168% and at the top of the ranks.  In order to fall out of the top decile, NVIDIA would have to fall below the trailing performance of McCormick & Company, which is only up 35%.  Those numbers will be moving targets as the time window moves forward, but you get the idea – extreme performers have to fall quite a ways before they are actually sold.

Perf

(Click To Enlarge)

Combining point and figure relative strength signals with a time window approach can help solve this problem.  This issue doesn’t affect every security you buy.  It generally only affects the extreme performers, but it does happen often enough that you can substantially enhance returns by using a point and figure relative strength overlay.  Point and figure signals are divided up into “signals” for the long-term and “columns” for intermediate term signals.  We have found that the most bullish configuration is for a security to be on a buy signal and in a column of X’s versus the benchmark.  (You can find a whitepaper about that topic here).  That simply means a security is outperforming the benchmark on an intermediate term basis.

One of the things that makes a security’s point and figure relative strength chart less bullish is if the column reverses from X’s to O’s, which indicate the relative performance is declining over the intermediate term.  In order to get that reversal, the security must underperform the benchmark by 3 units of volatility.  This is known as the three box reversal, and has been around since the 1950’s.  The unit of volatility we are using is simply percentage performance of the performance versus the benchmark, which we set at 6.5% (click here to see research about box sizes).  So if a security underperforms the benchmark by 19.5% (6.5%*3) the column will flip from X’s to O’s and we than have a less bullish configuration.  This is also very similar to a trailing relative strength stop!

Adding a point and figure overlay to the example above would require NIVIDIA to underperform the market by about 20% to get sold from the portfolio.  It wouldn’t have to fall all the way out of the top of the ranks.  This can be a very big help when looking at securities with extreme performance.  The point and figure also does a couple of other things that make it better than a simple trailing stop.  First, it prevents the system from rebuying the security because it may still be the top performer after it hits the trailing stop.  Second, the point and figure configuration allows for an easy re-entry into the security if it reverses and continues to perform well.  If the security rises 19.5% (6.5% box size * 3 boxes) after the point and figure chart reverses to O’s, the chart will reverse back to X’s and the security will be eligible to be purchased again.

To measure the value of adding a point and figure overlay we ran Monte Carlo trials of a high momentum system.  The Monte Carlo trials are designed to eliminate the effect of picking a few lucky securities that might skew the test results.  We used an investment universe made up of the top 1000 stocks by market capitalization traded in the U.S.  The portfolios held 50 stocks at a time, and any new purchases were made out of the top decile of the ranks.  The ranks were based on the trailing 250 day total return performance.  We examined the portfolios each week and any security that fell out of the top quartile of the ranks was sold.  When a new security needed to be purchases we picked a stock out of the top decile at random that we didn’t already own.  There are always more securities in the top decile than we need to own because we had 50 holdings, but the top decile contained 100 securities.  By drawing securities at random we created 100 different equity curves over the period from 1989 through 2015.  The results of the 100 trials are shown below.  The mean is simply the average performance of all 100 trials during the year.  Some trials performed better than others, but since we were using the exact same process most of the performance difference from one model to the next can be attributed to luck.

RndPerf

(Click To Enlarge)

Over time, the 250 day trailing performance model does very well.  The average of all 100 trials over the entire test period annualizes at 14.66% (without transaction costs), and all 100 of the trials wound up outperforming the S&P 500.

The model used above was simply a trailing performance ranking.  It didn’t account for the extreme performance problem discussed above.  We ran the same Monte Carlo process using the 250 day performance ranks and added a point and figure relative strength overlay.  We required each security to be on a point and figure buy signal and in a column of X’s on its relative strength chart versus the S&P 500 Total Return Index.  The results of adding the point and figure overlay are shown below.

RndPerfPnF

(Click To Enlarge)

The Mean PnF line shows the average of all 100 trials with the point and figure relative strength overlay year by year.  Adding the point and figure overlay improves the average performance of the models 223 basis points per year from 14.66% to 16.89%.  That is a significant increase to an original system that was already generating quite a bit of outperformance.  By running 100 trials of randomly selected high momentum stocks, we can be very confident that the performance difference isn’t the result of a few lucky trades that one system picked up and the other didn’t.

The point and figure relative strength overlay acts similar to a trailing stop, and helps solve the problem of when extreme performers actually cease being high momentum securities.  Adding a point and figure relative strength overlay is an extremely effective way to boost the performance of a time based momentum system.

 

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 strategyduring 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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Combining Equity Momentum (PDP) & Managed Futures (CSAIX)

July 11, 2016

One of the more surprising themes for many market participants thus far into 2016 has been the impressive strength of the commodities asset class.   What started off as a sharp rally from the lows in the energy sector quickly flowed into other commodities such as precious metals, softs (sugar) and ags (soybeans).   A lack of trend in US equities has helped funds flow into commodities as market participants search for yield in other asset classes.   Another tailwind for commodities has been the range bound activity in the US Dollar.  This in turn makes them cheaper to export overseas and therefore increases demand.

Although it may not be the most popular asset class amongst traditional fund managers, there is certainly demand for commodities markets among institutional traders.   For example, managed money (CTA’s and Macro Hedge Funds) is often focused on looking for trending markets in both foreign exchange and commodities to allocate toward their portfolios.  Given the size and leverage these funds have access too, the commodities and foreign exchange markets are often subject to large trending moves which can continue for extended periods of time.  Although momentum and trend following are often used interchangeably, they actually differ in the fact momentum (ex. 12 mo. trailing return) is typically thought of as relative while trend following techniques (ex. moving averages) are more absolute in nature.  Our main point in mentioning CTA’s and Hedge Funds is that given their ability to rotate through various asset classes and take both sides of the market (long or short) they typically have a negative correlation to long only equity managers.

Assuming the negative correlation between the two strategies holds true, combining a long only equity momentum portfolio with some type of managed futures strategy would certainly seem make sense in terms of reducing volatility and drawdowns while maintaining alpha above a related benchmark.  Let’s investigate this matter further by using the Power Shares DWA Momentum Portfolio (PDP) and combining it into a portfolio with the Credit Suisse Managed Futures Strategy Fund (CSAIX).   Note we will be using the returns of the underlying index (CSTHFMF0 – Credit Suisse Hedge Fund Index Managed Futures) in order to pull the historical data for CSAIX since its inception was 9/28/12.

Here is a brief summary of each strategy side by side.     As shown below, PDP outperforms both the Credit Suisse Hedge Fund Index Managed Futures Strategy CSAIX and SPX over the allotted time frame in this study.  However, as we saw in our previous posts it does so with slightly elevated volatility.   All other performance metrics aside, the main concept we want to emphasize is the differences in returns each year between PDP (momentum) and CSAIX (managed futures).  The most obvious example is 2008, when CSAIX posted an impressive 18.33% gain while both PDP and the SPX suffered steep double digit losses.

Click on graphic for larger version

ANNUAL RETURNS

PDP inception date: March 1, 2007, CSAIX inception date: Sept 28, 2012 – 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.  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. 

The graphic below shows a comparison of annual returns using the time period 1998 and 2015 in which the correlation of excess returns between momentum and managed futures  was  (-0.91)  A few of the outlier years to take note of which contain major differences in performance are 1999, 2008, 2009, and finally 2014.   Some of the largest differences in performance can be attributed to periods of heighted equity market volatility (ex 2008).   Excess volatility tends to create more opportunities for managed futures strategies.  On the other hand, the past 5 years (with the exception of 2014) showed equity momentum outperforming managed futures as the stock market continued its strong bull market while many commodities and foreign exchange rates were lacking volatility and any type of sustained trend (up or down).

Click on graphic for larger version

correlations

PDP inception date: March 1, 2007, CSAIX inception date: Sept 28, 2012 – 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.  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. 

The table below goes through similar allocation structure of how we set up our low volatility and value portfolios in combination with momentum in previous posts.  Our main goal here is to stay consistent and create a robust process that has very few moving parts.  The portfolios are all re-balanced annually but each allocation remains consistent each year.   The main goal is to emphasize the benefit of combining two negatively correlated strategies in order to take advantage of the performance differences each will achieve throughout different market cycles.

Click on graphic for larger version

HISTORICAL ALLOCATIONS

The returns above are based on hypothetical back-tests of the various allocation options.  PDP inception date: March 1, 2007, CSAIX (inception date: Sept 28, 2012 – data prior to inception is based on a back-test of the underlying indexes. 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.  PDP returns do not include dividends.  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. 

Let’s take it a step further and add one simple risk metric to our portfolio and see if we can reduce volatility even further.   Over time, it’s typically been the case that a long only equity momentum/trend following based strategy tends to perform better while the SPX is above its 200 day moving average.   On the flip side, when the SPX is below its 200 day moving average, periods of heightened volatility are more frequent and can lead to steep draw downs in these portfolios.   This is not always the case but over the years research has shown that the 200 day moving average is often considered a reliable proxy for a risk on/risk off environment.

Interestingly enough, this “risk off” environment is often where managed futures strategies thrive and tend to see their best results.  One main reason for this is the abundance of “fat tail” trades that seem to occur during these market cycles.  The below table compares a model we have created using a 200 day moving average as a risk proxy to determine how we will allocate our portfolio using equity momentum (PDP) and a managed futures strategy (CSAIX).   The allocation will be 80% equity momentum/20% managed futures when the S&P is above its 200 day moving average and 80% managed futures/20% equity momentum when it is below.  In order to reduce turnover, the portfolio will only be re-balanced on a month-end basis.

Click on graphic for larger version

CSAIX

PDP inception date: March 1, 2007, CSAIX  inception date: Sept 28, 2012 – data prior to inception is based on a back-test of the underlying indexes Performance of the switching strategy is the result of back-testing.  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. PDP returns do not include dividends.  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. 

Let’s take it a step further and add one simple risk metric to our portfolio and see if we can reduce volatility even further.   Over time, it’s typically been the case that a long only equity momentum/trend following based strategy tends to perform better while the SPX is above its 200 day moving average.   On the flip side, when the SPX is below its 200 day moving average, periods of heightened volatility are more frequent and can lead to steep draw downs in these portfolios.   This is not always the case but over the years research has shown that the 200 day moving average is often considered a reliable proxy for a risk on/risk off environment.

Interestingly enough, this “risk off” environment is often where managed futures strategies thrive and tend to see their best results.  One main reason for this is the abundance of “fat tail” trades that seem to occur during these market cycles.  The below table compares a model we have created using a 200 day moving average as a risk proxy to determine how we will allocate our portfolio using equity momentum (PDP) and a managed futures strategy (CSAIX).   The allocation will be 80% momentum/20% managed futures when the S&P is above its 200 day moving average and 20% equity/80% managed futures when it is below.  In order to reduce turnover, the portfolio will only be re-balanced on a month-end basis.

 

 

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Q3 2016 PowerShares DWA Momentum ETFs

July 5, 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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Commodity Turns

June 28, 2016

With commodities in focus (having moved to the number 2 spot of DALI in the past week), we wanted to draw your attention to some interesting research published by Arrow Funds.

DALI

Source: Dorsey Wright, as of 6/23/16

From their piece Commodity Turns:

The table below illustrates the 10-year, 5-year, and 3-year annualized returns for eight major asset classes through December 31, 2015.  The table also shows the average rolling annualized returns and the worst single rolling time periods from January 1970 through December 2015.

Commodities had a 10-year annualized return of -10.56% as of 12/31/2015, which also happens to be the worst 10-year rolling period since 1970.  But since 1970, commodities have actually averaged 8.38% across all rolling 10-year periods—a difference of 18.94% between the recent 10-year return and the rolling 10-year average.  For those who subscribe to the idea of “reversion to the mean” where extreme returns revert back to the average, a case could be made for commodities to turn in a more favorable direction.

reversion the mean

Like many asset classes, commodity returns go through periods of ups and downs.  Sometimes they have been the best performing asset class, sometimes the worst, and often somewhere in between.  With declining oil prices, a drop in precious metals and slowing global growth, commodities have been out of favor with investors for several years.  Due to the historically low correlation and potential diversification benefits, many investors are eager for commodities to make an upward turn.

The table below illustrates the calendar year performance for each of the eight asset classes and the relative rankings of commodities.  Commodities had back-to-back double digit negative returns and finished in the last place for the calendar years 2014 and 2015.  Since 1970, that has only happened two other times, in 1975-76 and 1997-98, as highlighted in yellow.  The table also illustrates the calendar year performance for 1977 and 1999, which are the years immediately following the back-to-back last place finishes (highlighted in green).

asset class history

The outcome for 2016 and beyond still remains to be seen and past performance is never indicative of future returns.  But history does shown that commodities have had the ability to reverse from sustained lows and deliver significant gains.  After back-to-back last place rankings, the single year returns that followed in 1977 and 1999 for commodities were impressive.  Perhaps even more interesting for investors with a longer time horizon are the average returns for the following three year periods 1977-1979 and 1999-2001, as illustrated in the table below.

3 year commodity

Click here for disclosures.

Two potential solutions for investors who are looking for commodity exposure are The Arrow DWA Balanced Fund (DWAFX) and the Arrow DWA Tactical Fund (DWTFX and DWAT).  Both of these strategies have the ability to allocate to commodities when they are in favor (and both have the ability to rotate away from commodities when they are out of favor.

As shown below, The Arrow DWA Balanced Fund (DWAFX) has the ability to allocate between 10 and 40 percent to Alternatives, including commodities.

dwafx

The Arrow DWA Tactical Fund (DWTFX and DWAT), has the ability to allocate between 0 and 90 percent to Alternatives.  Commodities can be up to 30 percent of that allocation.

dwtfx

Environments where commodities are in favor have the potential to be good environments for the performance of these strategies.  We have seen our commodity exposure in both of these funds increase in recent months.  Click here and here to see the 5/31/16 holdings of these funds.

The Arrow DWA Balanced Fund (DWAFX) is available as a mutual fund — click here for more information.

The Arrow DWA Tactical Fund (DWTFX) is available as a mutual fund and as an ETF (DWAT).  It is also available as the Global Macro portfolio on a number of SMA and UMA platforms, including the Wells Fargo Masters and DMA platforms. —click here for more information.  Contact Andy Hyer at andyh@dorseymm.com for information about the SMA/UMA.

See www.arrowfunds.com for a prospectus.  Dorsey Wright is research provider to Arrow Funds for The Arrow DWA Balanced and Arrow DWA Tactical Funds.  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

June 27, 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 (6/20/16 – 6/24/16) 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

June 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 6/21/16:

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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Manage Your Luck

June 21, 2016

“Luck is the residue of design”

                      –Branch Rickey

There is a lot more luck involved in investing than people think.  I’m not saying there isn’t skill involved in investing or that there aren’t ways to outperform the market over time.  Even if you have a process that can be shown to outperform the market over long time periods, there can be a great deal of variation in returns from year to year.  A well designed investment model can certainly help manage some of that luck, but it is difficult to eliminate it entirely.

Several years ago I looked at some momentum models in a unique way.  Most research on equity momentum involves buying a large basket of stocks (the top decile or top quintile, for example) and rebalancing on some preset schedule (like monthly).  There are a lot of active strategies that aren’t run that way so we wanted to find out how much variation there could be in owning a sub set of the high momentum stocks and rebalancing more frequently.  Do you need to own all of the big winners in order for a momentum strategy to work?

In order to attempt to answer that question I created a process that picked stocks at random out of a high momentum basket and held them until they were weak.  (You can read about it in more detail in the original whitepaper I published by clicking here.)  In the test shown in this post, I am using a universe of the top 1000 market capitalization stocks traded on US exchanges.  That eliminates the problem of holding very illiquid stocks; every stock in that universe should have sufficient liquidity to trade without major slippage costs.  Each week the stocks were ranked by their trailing 12 month performance, which is a very standard way to measure momentum.  Anything that ranked in the top decile based on the trailing 12 month performance rank was considered to be “eligible” for the portfolio.  Anything that ranked below the top quartile of the ranks was eliminated immediately from the portfolio.  The portfolio was set up to hold 50 stocks.

Most tests would just pick the top ranked stock when something needed to be bought.  The difference in my test was we picked something at random from the “eligible” list.  There were about 100 eligible stocks each week – the top 10% of the 1000 stock universe (excluding buyouts, etc…).  Then I ran the process 100 times to create 100 different equity curves.  It would be the same thing as giving the eligible list to 100 different people each week and telling them they can pick anything they want off the list as long as they don’t already own it.  You are going to wind up with 100 totally different portfolios over time with the only thing in common being the process of buying high momentum stocks and selling them when they get weak.

The results of the 100 trials are summarized in the table and graph below (click the image to enlarge).  The table shows the return of the S&P 500 as well as the average return of the 100 trials each year.  There is also a section that shows where the quartile breaks occur each year.  The graph shows the returns year by year with the red bar being the average return, the box showing where the mid quartiles are, and the whiskers extending to the min and max returns.  The green dot is the S&P 500.

Random Numbers

Random Graphs

The biggest thing that should jump out at you is that even by picking stocks at random, all 100 trials outperform the S&P 500 Total Return Index.  That is pretty amazing.  The actual stocks you put into the portfolio don’t matter as much as you would think.  The process is what is important.  Constantly cutting the losers and buying winners is what drives the performance.  The process helps to manage the luck of stock picking over time!

You can also see that from year to year the returns can vary quite a bit.  So what is the difference?  Literally, luck.  Some years the process is lucky, some years it isn’t, but when the process is solid it works out over time.  It is also a good reminder of why it is so important to focus on the process rather than the results over a short time period.  Just because a process underperforms for a year it doesn’t mean it is “broken.”  This, unfortunately, is how most investors think.  There is so much research on poor investor behavior I’m not even going to attempt to address it here!

A solid investment process winds up managing the luck that exists in implementing the system over short time periods.  Momentum is a robust enough factor to handle picking stocks and random from a highly ranked sub set of securities and then selling them when they are weak.  What happens from year to year is a lot about luck, but over time the design of the process overcomes the luck.

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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Dorsey Wright Separately Managed Accounts

June 15, 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 Nicolaus (Opportunity Platform)
  • Kovack Securities (Growth and Global Macro approved on the UMA Platform)
  • Charles Schwab Institutional (Marketplace Platform)
  • Envestnet UMA (Growth, Aggressive, Core, Balanced, International, and Global Macro approved)
  • Fidelity Institutional

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 andy@dorseywright.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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Relative Strength Spread

June 15, 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 6/14/2016:

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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