What Are We Really Trying To Accomplish Here?

February 28, 2014

March 1st is the seventh anniversary of our Technical Leaders Index launching on the NYSE.  The last seven years have seen some crazy markets!  Through it all we have been really happy at how the index has adapted to the different market environments we have had.

We often get caught up in the day-to-day gyrations of the market and we forget to take a step back and look at what a strategy is designed to accomplish.  The Technical Leaders Index is designed to keep the index invested in high momentum stocks.  It is a process that is supposed to cut the underperforming stocks out and ride the winners as long as they continue to outperform.  That is how most successful momentum and trend-following strategies work.

With that in mind, I thought it would be interesting to show everyone what would be coming out of the index and what would be going in if we rebalanced it today.  Remember, the process is designed to cut out the stocks that aren’t performing well and to buy stocks that are performing better than what we are selling.  Here are the stocks we would be selling (I have taken the names off the charts for compliance reasons, but the actual names of the stocks don’t really matter anyways):

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And here is what we would be buying:

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Pretty remarkable difference, right?  The performance over the last few months is quite different for the two groups of stocks.  Over time that is what the Technical Leaders process does.  It constantly replaces weak stocks with stronger ones.

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Sector Performance

February 28, 2014

The chart below shows performance of US sectors over the trailing 12, 6, and 1 month(s).  Performance updated through 2/27/2014.

s_c 02.28.14

Numbers shown are price returns only and are not inclusive of transaction costs.    Source: iShares

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Survivorship Bias

February 28, 2014

Everyone in the financial services industry has seen awesome-looking backtests for various return factors or trading methods, but most people don’t even know what survivorship bias is.  When I see one of those amazing backtests and I ask how they removed the survivorship bias, the usual answer is “Huh?”

A recent post by Cesar Alvarez at Alvarez Quant Trading shows just how enormous survivorship bias can be for a trend following system.  Most people with amazing backtests, when pushed, will concede there might be “some” effect from survivorship.  None of them ever think it will be this large!

Here, Mr. Alvarez describes the bias and shows the results:

Pre-inclusion bias is using today’s index constituents as your trading universe and assuming these stocks were always in the index during your testing period. For example if one were testing back to 2004, GOOG did not enter the S&P500 index until early 2006 at a price of $390. But your testing could potentially trade GOOG during the huge rise from $100 to $300.

Rules

  • It is the first trading day of the month
  • Stock is member of the S&P500 (on trading date vs as of today)
  • S&P500 closes above its 200 day moving average (with and without this rule)
  • Rank stocks by their six month returns
  • Buy the 10 best performing stocks at the close

Source: Alvarez Quant Trading

(click on image to enlarge to full size)

Mind-boggling, isn’t it?  The fantastic system that showed 30%+ returns now shows returns of less than 8%!!  (The test period, by the way, was 2004-2013.)

Unfortunately, this is the way much backtesting is done.  It’s much more trouble to acquire a database that has all of the delisted securities and all of the historical index constituents.  That’s expensive and time-consuming, but it’s the only way to get accurate results.  (Needless to say, that’s how our testing is done.  You can link to one of our white papers that additionally includes Monte Carlo testing to make the results even more robust.)  By the way, the pre-inclusion bias also shows very clearly how the index providers actually manage these indexes!

Mr. Alvarez concludes:

People often write about systems they have developed using the current Nasdaq 100 or S&P 500 stocks and have tested back for 5 to 10 years. Looking at this table shows that one should completely ignore those results.

When looking at backtested results, it often pays to be skeptical and to ask some questions about survivorship bias.

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Quote of the Week

February 28, 2014

Markets will be permanently efficient when investors are permanently objective and unemotional.  In other words, never.—-Howard Marks, Oaktree Capital

This quotation is taken from a much longer think-piece about the role of luck in investing that I first saw on Advisor Perspectives.  Mr. Marks points out that while markets are often structurally fairly efficient, they are often quite inefficient on a cyclical basis when investors freak out.  Highly recommended reading.

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How Not to be a Terrible Investor

February 27, 2014

Morgan Housel at Motley Fool has a wonderful article on how investors can learn from failure.  He sets the tone with a few different quotes and anecdotes that point out that a lot of being a success is just avoiding really dumb mistakes.

At a conference years ago, a young teen asked Charlie Munger how to succeed in life. “Don’t do cocaine, don’t race trains to the track, and avoid all AIDS situations,” Munger said. Which is to say: Success is less about making great decisions and more about avoiding really bad ones.

People focus on role models; it is more effective to find antimodels—people you don’t want to resemble when you grow up.    Nassim Taleb

I’ve added the emphasis, but Mr. Housel makes a good point.  Learning from failure is equally important as learning from success.  In fact, he argues it may be more important.

If it were up to me, I would replace every book called How to Invest Like Warren Buffett with a one called How to Not Invest Like Lehman Brothers, Long-Term Capital Management, and Jesse Livermore. There are so many lessons to learn from these failed investors about situations most of us will face, like how quickly debt can ruin you. I’m a fan of learning from Buffett, but the truth is most of us can’t devote as much time to investing as he can. The biggest risk you face as an investor isn’t that you’ll fail to be Warren Buffett; it’s that you’ll end up as Lehman Brothers.

But there’s no rule that says you have to learn by failing yourself. It is far better to learn vicariously from other people’s mistakes than suffer through them on your own.

That’s his thesis in a nutshell.  He offers three tidbits from his study of investing failures.  I’ve quoted him in full here because I think his context is important (and the writing is really good).

1. The overwhelming majority of financial problems are caused by debt, impatience, and insecurity. People want to fit in and impress other people, and they want it right now. So they borrow money to live a lifestyle they can’t afford. Then they hit the inevitable speed bump, and they find themselves over their heads and out of control. That simple story sums up most financial problems in the world. Stop trying to impress people who don’t care about you anyways, spend less than you earn, and invest the rest for the long run. You’ll beat 99% of people financially.

2. Complexity kills. You can make a lot of money in finance, so the industry attracted some really brilliant people. Those brilliant people naturally tried to make finance more like their native fields of physics, math, and engineering, so finance has grown exponentially more complex in the last two decades. For most, that’s been a disservice. I think the evidence is overwhelming that simple investments like index funds and common stocks will demolish complicated ones like derivatives and leveraged ETFs. There are two big stories in the news this morning: One is about how the University of California system is losing more than $100 million on a complicated interest rate swap trade. The other is about how Warren Buffett quintupled his money buying a farm in Nebraska. Simple investments usually win.

3. So does panic. In his book Deep Survival, Laurence Gonzalez chronicles how some people managed to survive plane crashes, getting stranded on boats, and being stuck in blizzards while their peers perished. The common denominator is simple: The survivors didn’t panic. It’s the same in investing. I’ve seen people make a lifetime of good financial decisions only to blow it all during a market panic like we saw in 2008. Any financial decision you make with an elevated heart rate is probably going to be one you’ll regret. Napoleon’s definition of a military genius was “the man who can do the average thing when all those around him are going crazy.” It’s the same in investing.

I think these are really good points.  It’s true that uncontrolled leverage accompanies most real blowups.  Having patience in the investing process is indeed necessary; we’ve written about that a lot here too.  The panic, impatience, and insecurity he references are really all behavioral issues—and it just points out that having your head on straight is incredibly important to investment success.  How successful you are in your profession or how much higher math you know is immaterial.  As Adam Smith (George Goodman) wrote, “If you don’t know who you are, the stock market is an expensive place to find out.” 

Mr. Housel’s point on complexity could be a book in itself.  Successful investing just entails owning productive assets—the equity and debt of successful enterprises—acquired at a reasonable price.  Whether you own the equity directly, like Warren Buffett and his farm, or in security form is immaterial.  An enterprise can be a company—or even a country—but it’s got to be successful.

Complexity doesn’t help with this evaluation.  In fact, complexity often obscures the whole point of the exercise.

This is actually one place where I think relative strength can be very helpful in the investment process.  Relative strength is incredibly simple and relative strength is a pretty good signaling mechanism for what is successful.  Importantly, it’s also adaptive: when something is no longer successful, relative strength can signal that too.  Sears was once the king of retailing.  Upstart princes like K-Mart in its day, and Wal-Mart and Costco later, put an end to its dominance.  Once, homes were lit with candles and heated with fuel oil.  Now, electricity is much more common—but tomorrow it may be something different.  No asset is forever, not even Warren Buffett’s farmland.  When the soil is depleted, that farm will become a lead anchor too.  Systematic application of relative strength, whether it’s being used within an asset class or across asset classes, can be a very useful tool to assess long-term success of an enterprise.

Most investing problems boil down to behavioral issues.  Impatience and panic are a couple of the most costly.  Avoiding complexity is a different dimension that Mr. Housel brings up, and one that I think should be included in the discussion.  There are plenty of millionaires that have been created through owning businesses, securities, or real estate.  I can’t think of many interest rate swap millionaires (unless you count the people selling them).  Staying calm and keeping things simple might be the way to go.  And if the positive prescription doesn’t do it for you, the best way to be a good investor may be to avoid being a terrible investor!

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Fund Flows

February 27, 2014

Mutual fund flow estimates are derived from data collected by The Investment Company Institute covering more than 95 percent of industry assets and are adjusted to represent industry totals.

ici 02.27.14

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Rolling 10-Year Momentum Returns

February 26, 2014

To get a sense for just how effective momentum investing has been over time, consider the rolling 10-year returns for the following momentum index compared to the S&P 500.  The data starts in January 1927 so the first 10-year period ends in January 1937.

momentum 02.26.14

Source: Ken French Data Library, Global Financial Data (1/1/1927 – 1/31/2014); Returns include dividends but do not include any transaction costs; The momentum index is based the Ken French momentum series (Equal-weighted index of the top half market cap, top third momentum of a universe of U.S. stocks).  This momentum index rebalanced monthly based on trailing 12 month returns of the securities.  

The chart below measures the difference between the 10-year returns for the momentum index minus the 10-year returns for the S&P 500:

momentum2 02.26.14

Note that the momentum index outperformed the S&P 500 in every rolling 10-year period during this study.  Yes, some 10-year periods were better than others for momentum from a relative performance perspective.  Also, the difference in performance between momentum and the S&P 500 for the 10-year period ending 1/31/2014 was 2.97%.  This is on the lower end of the range over the test period.  It would not surprise me at all to see this margin of outperformance revert to the mean in the years ahead (the average difference in performance between momentum and the S&P 500 for rolling 10-year periods was 5.63% over this test period).

Past performance is no guarantee of future returns.

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High RS Diffusion Index

February 26, 2014

The chart below measures the percentage of high relative strength stocks that are trading above their 50-day moving average (universe of mid and large cap stocks.)  As of 2/25/14.

diffusion 02.26.14

The 10-day moving average of this indicator is 74% and the one-day reading is 79%.

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Relative Strength Spread

February 25, 2014

The chart below is the spread between the relative strength leaders and relative strength laggards (universe of mid and large cap stocks).  When the chart is rising, relative strength leaders are performing better than relative strength laggards.    As of 2/24/2014:

spread 02.25.14

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Rediscovering Passion for Europe

February 24, 2014

The WSJ reports on the resurgent demand for European equities:

U.S. fund managers are rediscovering their passion for Europe—and not just as a vacation destination.

Since the start of the year, American investors have ramped up their bets on European stocks, spurred on by a brightening economic outlook and low interest rates.

The continent’s stock markets became a favored destination last year as the region emerged from a bruising recession. This year, with U.S. stock indexes treading water after a rip-roaring 2013, interest in European stocks has grown further, fund managers say.

Investors have sent $24.3 billion into European equity funds this year through Feb. 19, according to fund tracker EPFR Global. U.S. stock funds have seen $5 billion in outflows.

In the exchange-traded-fund world, three of the top four stock-based funds in terms of investor inflows in 2014 are the Vanguard FTSE Europe, the iShares MSCI EMU and the Vanguard FTSE Developed Markets ETFs—all of which have heavy exposure to Europe. The three have seen a combined $4.23 billion in new money this year, while $19.1 billion has flowed out of the largest U.S. stock ETF, the SPDR S&P 500 fund.

My emphasis added.  All three of the ETFs referenced above are cap-weighted ETFs.  To those three, I have added the PowerShares DWA Developed Markets Momentum ETF (PIZ), which had better performance in 2013 and is also ahead of those three so far in 2014:

Europe_perf

 (click to enlarge)

Source: Dorsey Wright; YTD performance through 2/21/14; Performance does not included dividends or any transaction costs

While PIZ is not exclusively focused on Europe, it is certainly heavily weighted to that region:

piz alloc

(click to enlarge)

Source: PowerShares

PIZ has had inflows of $360 million over the past year and now has $671 million in assets.

Past performance is no guarantee of future returns.  Dorsey Wright is the index provider for PIZ.  Dorsey Wright also currently owns EZU.  All past holdings for the trailing 12 months is available upon request.

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Weekly RS Recap

February 24, 2014

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 (2/18/14 – 2/21/14) is as follows:

ranks 02.24.14

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The Growing Case Against ETFs

February 21, 2014

That’s the title of a Marketwatch article by mutual fund columnist Chuck Jaffe.  I have to admit that usually I like his columns.  But columns like this make me nuts!  (See also The $ Value of Patience for an earlier rant on a similar topic.)

Here’s the thesis in a nutshell:

…safe driving comes down to a mix of equipment and personnel.

The same can be said for mutual funds and exchange-traded funds, and while there is growing consensus that ETFs are the better vehicle, there’s growing evidence that the people using them may not be so skilled behind the wheel.

The article goes on to point out that newsletters with model portfolios of mutual funds and ETFs have disparate results.

Over the last 12 months, the average model portfolio of traditional funds—as tracked by Hulbert Financial Digest—was up 20.9%, a full three points better than the average ETF portfolio put together by the same advisers and newsletter editors. The discrepancy narrows to two full percentage points over the last decade, and Hulbert noted he was only looking at advisers who run portfolios on both sides of the aisle.

Hulbert posited that if you give one manager both vehicles, the advantages of the better structure should show up in performance.

It didn’t.

Hulbert—who noted that the performance differences are “persistent” — speculated “that ETFs’ advantages are encouraging counterproductive behavior.” Effectively, he bought into Bogle’s argument and suggested that if you give an investor a trading vehicle, they will trade it more often.

Does it make any sense to blame the vehicle for the poor driving?  (Not to mention that DALBAR data make it abundantly clear that mutual fund drivers frequently put themselves in the ditch.)  Would it make sense to run a headline like “The Growing Case Against Stocks” because stocks can be traded?

Mutual funds, ETFs, and other investment products exist to fulfill specific needs.  Obviously not every product is right for every investor, but there are thousands of good products that will help investors meet their goals.  When that doesn’t happen, it’s usually investor behavior that’s to blame.  (And you’re not under any obligation to invest in a particular product.  If you don’t understand it, or you get the sinking feeling that your advisor doesn’t either, you should probably run the other way.)

Investors engage in counterproductive behavior all the time, period.  It’s not a matter of encouraging it or not.  It happens in every investment vehicle and the problem is almost always the driver.  In fact, advisors that can help manage counterproductive investor behavior are worth their weight in gold.   We’re not going to solve problems involving investor behavior by blaming the product.

A certain amount of common sense has to be applied to investing, just like it does in any other sphere of life.  I know that people try to sue McDonald’s for “making” them fat or put a cup of coffee between their legs and then sue the drive-thru that served it when they get burned, but whose responsibility is that really?  We all know the answer to that.

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High RS Diffusion Index

February 19, 2014

The chart below measures the percentage of high relative strength stocks that are trading above their 50-day moving average (universe of mid and large cap stocks.)  As of 2/18/14.

diffusion 02.19.14

After reaching a single-day low of 26% on 2/3/14, this index has rebounded sharply.  The 10-day moving average is 58% and the one-day reading is 79%.

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Weekly RS Recap

February 18, 2014

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 (2/10/14 – 2/14/14) is as follows:

ranks 02.18.14

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Relative Strength Spread

February 11, 2014

The chart below is the spread between the relative strength leaders and relative strength laggards (universe of mid and large cap stocks).  When the chart is rising, relative strength leaders are performing better than relative strength laggards.    As of 2/10/2014:

RS Spread 02.11.14

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January Arrow DWA Funds Update

February 10, 2014

01/31/2014

The Arrow DWA Balanced Fund (DWAFX)

At the end of January, the fund had approximately 46% in U.S. Equities, 26% in Fixed Income, 16% in International Equities, and 11% in Alternatives.

DWAFX fell 1.85% in January, after gaining 15.77% in 2013.

After a remarkable year for equities in 2013, stocks pulled back in January.  Fixed Income prices moved higher, helping to buffer the overall returns of the fund for the month.  Interest rates moved sharply higher in the spring and summer of 2013, during initial announcements of Fed tapering of its quantitative easing program, but rates had chopped sideways for the last couple months.   January was not exactly a case of what performed best in 2013, performed worst in January.  Rather, Healthcare, which was one of last year’s biggest winners continued to gain relative strength and actually generated positive returns for the month.  Small and mid-caps also generally continued their favorable performance compared to large caps.  The biggest losses for the month came from our international equity exposure, including Japan, Netherlands, and Germany.

We believe that a real strength of this strategy is its balance between remaining diversified, while also adapting to market leadership.  When an asset class is weak its exposure will tend to be towards the lower end of the exposure constraints, and when an asset class is strong its exposure in the fund will trend toward the upper end of its exposure constraints.  Relative strength provides an effective means of determining the appropriate weights of the strategy.

dwafx

The Arrow DWA Tactical Fund (DWTFX)

At the end of January, the fund had approximately 90% in U.S. equities and 9% in International equities.

DWTFX fell 3.30% in January, after gaining 26.19% in 2013.

There were no changes in holdings in the fund in January.  Healthcare and Small-Cap Growth held up relatively well, while Consumer Discretionary and European Equities were among our worst performers for the month.  Many of the longer-term relative strength trends remain firmly in place, even will the pull back over the last couple of weeks: U.S. equities continue to have strong relative strength, Emerging Markets and Commodities continue to be particularly weak, and Fixed Income and Currencies are not strong enough to warrant exposure at this point.

This strategy is a go-anywhere strategy with very few constraints in terms of exposure to different asset classes.  The strategy can invest in domestic equities, international equities, inverse equities, currencies, commodities, real estate, and fixed income.  Market history clearly shows that asset classes go through secular bull and bear markets and we believe this strategy is ideally designed to capitalize on those trends.  Additionally, we believe that this strategy can provide important risk diversification for a client’s overall portfolio.

dwtfx

A list of all holdings for the trailing 12 months is available upon request.  Past performance is no guarantee of future returns.  See www.arrowfunds.com for a prospectus.

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Fund Flows

February 6, 2014

Mutual fund flow estimates are derived from data collected by The Investment Company Institute covering more than 95 percent of industry assets and are adjusted to represent industry totals.

ici 02.06.14

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The Power of Buying Pullbacks

February 5, 2014

Buying pullbacks is a time-tested way to boost returns.  From time to time, we’ve discussed the utility in buying pullbacks in the market.  Buying the dips—instead of panicking and selling—is essentially doing the opposite of how most investors conduct their affairs.  In the past, much of that discussion has involved identification of market pullbacks using various oversold indicators.  (See, for example, Lowest Average Cost Wins.)  In a recent article in Financial Planning, Craig Israelsen proposes another good method for buying pullbacks.

The gist of his method is as follows:

The basic rule for investment success is as old as the hills: Buy low, sell high. But actually doing it can be surprisingly difficult.

Selling a stock or fund that has been performing well is tough. The temptation to ride the rocket just a little longer is very strong. So let’s focus on the other element: Buy low.

I propose a disciplined investment approach that measures performance against an annual account value target. If the goal is not met, the account is supplemented with additional investment dollars to bring it up to the goal. (For this exercise, I capped supplemental investment at $5,000, in acknowledgement that investors don’t have endlessly deep pockets.)

Very simply, the clients will “buy low” in years when the account value is below the target. If, however, the target goal is met at year’s end, the clients get to do a fist pump and treat themselves to a fancy dinner or other reward.

One benefit of this suggested strategy is that it is based on a specific performance benchmark rather than on an arbitrary market index (such as the S&P 500) that may not reflect the attributes of the portfolio being used by the investor.

In the article, he benchmarks a diversified portfolio against an 8% target and shows how it would have performed over a 15-year contribution period.  In years when the portfolio return exceeds 8%, no additional contributions are made.  In years when the portfolio return falls short of 8%, new money is added.  As he points out:

It’s worth noting that the added value produced by this buy-low strategy did not rely on clever market timing in advance of a big run-up in the performance of the portfolio. It simply engages a dollar cost averaging protocol – but only on the downside, which is where the real value of dollar cost averaging resides.

Very smart!  (I added the bold.)  It’s a form of dollar-cost averaging, but only kicks in when you can buy “shares” of your portfolio below trend.  He used an 8% target for purposes of the article, but an investor could use any reasonable number.  In fact, there might be substantial value in using a higher number like 15%.  (You could also use a different time frame, like monthly, if that fit the client’s contribution schedule better.)  Obviously you wouldn’t expect a 15% portfolio return every year, but it would get clients in the habit of making contributions to their account in most years.  Great years like 2013 would result in the fancy dinner reward, while lousy market years would result in maximum contributions—hopefully near relative lows where they would do the most good.

This is an immensely practical method for getting clients to contribute toward some kind of goal return—and his 15-year test shows good results.  In six of the 15 years, portfolio results were below the yardstick and additional contributions were made totalling $13,802.  Making those additional investments added an extra $12,501 to what the balance would have been otherwise, resulting in a 7.7% boost in the portfolio total.  Looked at another way, over time you ended up with nearly a 100% return on the extra money added in poor years.

Of course, Israelsen points out that although his proposed method is extremely simple, client psychology may still make it challenging to implement.  Clients are naturally resistant to committing money to an underperforming market or during a period of time when there is significant uncertainty.  Still, this is one of the better proposals I have seen on how to motivate clients to save, to invest at reasonable times, and to focus on a return goal rather than on how they might be doing relative to “the market.”  You might consider adding this method to your repertoire.

Buy pullbacks and use the rollercoaster ride of the market to your advantage.

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High RS Diffusion Index

February 5, 2014

The chart below measures the percentage of high relative strength stocks that are trading above their 50-day moving average (universe of mid and large cap stocks.)  As of 2/4/14.

diffusion 02.05.14

The 10-day moving average of this indicator is 49% and the one-day reading is 33%.  Dips in this indicator have often provided good opportunities to add money to relative strength strategies.

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Quote of the Week

February 4, 2014

The elements of good trading are: (1) cutting losses, (2) cutting losses, and (3) cutting losses. If you can follow these three rules, you may have a chance.—-Ed Seykota

Although this sounds tongue-in-cheek (and probably is to some extent), it’s also true.  Almost nothing is more ruinous than being risk-seeking with respect to losses, yet that is the way most individual investors behave.  According to research, individual investors tend to take profits quickly and let their losses run—no doubt hoping for a recovery.  While this may be enjoyable for one’s ego, it is a poor way to handle a portfolio.  With enough transactions, the unwitting investor finds himself holding a diversified portfolio of losing positions!

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Relative Strength Spread

February 4, 2014

The chart below is the spread between the relative strength leaders and relative strength laggards (universe of mid and large cap stocks).  When the chart is rising, relative strength leaders are performing better than relative strength laggards.    As of 2/3/2014:

spread 02.04.14

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It’s All At The Upper End

February 3, 2014

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 earlier this week.  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.  The “Univ” line is a monthly equal-weighted portfolio of all the GICS sub-sectors.  The next quintile (ranks 60-80) barely beats the universe return and probably adds no value after you are done with trading costs, taxes, etc…  Keep in mind that these sectors are still well within the top half of the ranks and they still add minimal value.  The other three quintiles are underperformers.  They are all clustered together well below the universe return.

 (Click on image to enlarge)

The overall performance numbers aren’t as good, but you get the exact same pattern of results if you use a 12-Month Trailing Return to rank the sub-sectors instead of a point & figure matrix:

 (click on image to enlarge)

Same deal if you use a 6-Month Trailing Return:

(click on image to enlarge)

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.

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Weekly RS Recap

February 3, 2014

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 (1/27/14 – 1/31/14) is as follows:

ranks 02.03.14

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