From the Archives: The Math Behind Manager Selection

May 31, 2012

Hiring and firing money managers is a tricky business.  Institutions do it poorly (see background post here ), and retail investors do it horribly (see article on DALBAR  ).  Why is it so difficult?

This white paper on manager selection from Intech/Janus goes into the mathematics of manager selection.  Very quickly it becomes clear why it is so hard to do well.

Many investors believe that a ten-year performance record for a group of managers is sufficiently long to make it easy to spot the good managers. In fact, it is unlikely that the good managers will stand out.  Posit a good manager whose true average relative return is 200 basis points (bps) annually and true tracking error (standard deviation of relative return) is 800 bps annually. This manager’s information ratio is 0.25. To put this in perspective, an information ratio of 0.25 typically puts a manager near or into the top quartile of managers in popular manager universes.

Posit twenty bad managers with true average relative returns of 0 bps annually, true tracking error of 1000 bps annually, hence an information ratio of 0.00.

There is a dramatic difference between the good manager and the bad managers.

The probability that the good manager beats all twenty bad managers over a ten-year period is only about 9.6%.  This implies that chasing performance leaves the investor with the good manager only about 9.6% of the time and with a bad manager about 90.4% of the time.

In other words, 90% of the time the manager with the top 10-year track record in the group will be a bad manager!  Maybe a longer track record would help?

A practical approach is to ask how long a historical performance record is necessary to be 75% sure that the good manager will beat all the bad managers, i.e., have the highest historical relative return. Assuming the same good manager as before and twenty of the same bad managers as before, a 157 year historical performance record is required to achieve a 75% probability that the good manager will beat all the bad managers.

It turns out that it would help, but since none of the manager databases have 150-year track records, in practice it is useless.  The required disclaimer that past performance is no guarantee of future results turns out to be true.

There is still an important practical problem to be solved here.  Assuming that bad managers outnumber good ones and assuming that we don’t have 150 years to wait around for better odds, how can we increase our probability of identifying one of the good money managers?

The researchers show mathematically how combining an examination of the investment process with historical returns makes the decision much simpler.  If the investor can make a reasonable assumption about a manager’s investment process leading to outperformance, the math is straightforward and can be done using Bayes’ Theorem to combine probabilities.

…the answer changes based on the investor’s assessment of the a priori credibility of the manager’s investment process.

It turns out that the big swing factor in the answer is the credibility of the underlying investment process.  What are the odds that an investment process using Fibonacci retracements and phases of the moon will generate outperformance over time?  What are the odds that relative strength or deep value will generate outperformance over time?

The research paper concludes with the following words of wisdom:

A careful examination of almost any investor’s investment manager hiring and firing process is likely to reveal that there is a substantial component of performance chasing. Sometimes it is obvious, e.g., when there is a policy of firing a manager if he has negative performance after three years. Other times it is subtle, e.g., when the initial phase of the manager search process strongly weights attractive historical performance. No matter the form that performance chasing takes, it tends to produce future relative returns that are disappointing compared to expectations.

Historical performance alone is not an effective basis for identifying a good manager among a group of bad managers. This does not mean that historical performance is useless. Rather, it means that it must be combined efficiently with other information. The correct use of historical performance relegates it to a secondary role. The primary focus in manager choice should be an analysis of the investment process.  [emphasis added]

This research paper is eye-opening in several respects.

1) It shows pretty clearly that historical performance alone–despite what our intuition tells us–is not sufficient to select managers.  This probably accounts for a great deal of the poor manager selection, the subsequent disappointment, and rapid manager turnover that goes on.

2) It is very clear from the math that only credible investment processes are likely to generate long-term outperformance.  Fortunately, lots of substantive academic and practitioner research has been done on factor analysis leading to outperformance.  The only two broadly robust factors discovered so far have been relative strength and value, both in various formulations–and, obviously, they have to be implemented in a disciplined and systematic fashion.  If your investment process is based on something else, there’s a decent chance you’re going to be disappointed.

3) Significant time is required for the best managers to stand out from the much larger pack of mediocre managers.

This is a demanding process for consultants and clients.  They have to willfully reduce their focus on even 10-year track records, limit their selection to rigorous managers using proven factors for outperformance, and then exercise a great deal of patience to allow enough time for the cream to rise to the top.  The rewards for doing so, however, might be quite large–especially since almost all of your competition will ignore the correct process and and simply chase performance.

—-this article originally appeared 1/28/2010.  I have seen no evidence since then that most consultants have improved their manager selection process, which is a shame.

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From the Archives: Is Modern Portfolio Theory Obsolete?

May 29, 2012

It all depends on who you ask.  Apologists for MPT will say that diversification worked, but that it just didn’t work very well last go round.  That’s a judgment call, I suppose.  Correlations between assets are notoriously unstable and nearly went to 1.0 during the last decline, but not quite.  So I guess you could say that diversification “worked,” although it certainly didn’t deliver the kind of results that investors were expecting.

Now even Ibbotson Associates is saying that certain aspects of modern portfolio theory are flawed, in particular using standard deviation as a measurement of risk.  In a recent Morningstar interview, Peng Chen, the president of Ibbotsen Associates, addresses the problem.

It’s one thing to say modern portfolio theory, the principle, remained to work. It’s another thing to examine the measures. So when we started looking at the measures, we realized, and this has been documented by many academics and practitioners, we also realized that one of the traditional measures in modern portfolio theory, in particular on the risk side, standard deviation, does not work very well to measure and present the tail risks in the return distribution.

Meaning that, when you have really, really bad market outcomes, modern portfolio theory purely using standard deviation underestimates the probability and severity of those tail risks, especially in short frequency time periods, such as monthly or quarterly.

Leaving aside the issue of how the theory could work if the components do not, this is a pretty surprising admission.  Ibbotson is finally getting around to dealing with the “fat tails” problem.  It’s a known problem but it makes the math much less tractable.  Essentially, however, Mr. Chen is arguing that market risk is actually much higher than modern portfolio theory would have you believe.

In my view, the debate about modern portfolio theory is pretty much done.  Stick a fork in it.  Rather than grasping about for a new theory, why not look at tactical asset allocation, which has been in plain view the entire time?

Tactical asset allocation, when executed systematically, can generate good returns and acceptable volatility without regard to any of the tenets of modern portfolio theory.  It does not require standard deviation as the measure of risk, and it makes no assumptions regarding the correlations between assets.  Instead it makes realistic assumptions: some assets will perform better than others, and you ought to consider owning the good assets and ditching the bad ones.  It’s the ultimate pragmatic solution.

—-this article originally appeared 1/21/2010.  As we gain distance from the 2008 meltdown, investors are beginning to forget how badly their optimized portfolios performed and are beginning to climb back on the MPT bandwagon.  Combining uncorrelated strategies always makes for a better portfolio, but the problem of understated risk remains.  The tails are still fat.  Let’s hope that we don’t get another chance to experience fat tails with the Eurozone crisis.  Tactical asset allocation, I think, may still be the most viable solution to the problem.

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From the Archives: Inflation Rears Its Ugly Head

May 25, 2012

Howard Marks is chairman of Oaktree Capital, a large and well-known institutional alternative fixed income manager.  Mr. Marks’s memos are always thoughtful and worth reading.  This go round he has a discussion of all of the things that could go wrong with the world economy—essentially a list of all of the things that could go wrong.  One of the things that could go wrong is inflation.

He believes rates are more likely to go higher than lower, and that inflation, long forgotten as a risk factor, might return.  In addition, he has a list of suggestions on how to deal with inflation including TIPs, floating rate debt, gold, real assets like commodities, oil, and real estate, and foreign currencies.  His catalog of alternatives is even longer, but you get the idea.  (If you want to read the whole memo, you can find it here.)

That’s quite a list, but the first thing that I noticed about it is that not one of these items is generally considered as an investment option by retail investors.  Most investors are mentally stuck in the domestic stocks/domestic bonds arena.  Diversification consists of hitting more than one Morningstar style box.  If inflation does come back, that’s not going to cut it.  In fact, Mr. Marks asks investors, “How much of your portfolio are you willing to devote to protect against these macro forces?”  He says if the answer is 5%, or 10%, or 15% that those levels are pretty close to doing nothing.  He thinks a portfolio will need to devote at least 30-40% of assets toward inflation protection if it recurs.

Investment flexibility and risk diversification were the primary reasons that we launched the Systematic RS Global Macro account as a retail product last year.  Many of the inflation hedges in Mr. Marks’ list are asset classes that are available in the Global Macro portfolio, including TIPs, gold, commodities, oil, real estate, and foreign currencies.  Given our basket rotation strategy and our adherence to relative strength, the Global Macro portfolio could easily have 40% of its assets, or more, in inflation hedges if inflation were to recur.  I think the jury is still out about how the world economy will respond to decreased levels of fiscal stimulus, but it’s good to know that you have options.

—-this article originally appeared 1/25/2010.  We have not seen runaway inflation so far, but the point Howard Marks makes is valid.  If/when inflation does occur, you might need to devote a lot of your portfolio to inflation protection.  Is your investment process up for the challenge?

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From the Archives: Essence of Relative Strength

March 27, 2012

“I can’t change the direction of the wind, but I can adjust my sails to always reach my destination.” – Jimmy Dean

—-this article originally appeared 12/11/2009.  Who knew the sausage king knew anything about relative strength?

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From the Archives: Ken French Should Check His Website

March 26, 2012

A new paper from Eugene Fama and Ken French is circulating, suggesting that active mutual fund managers don’t add value.  Articles, like the one here at MarketWatch, have been appearing and the typical editorial slant is that you should just buy an index fund.

I have a bone to pick with this article and its conclusions, but certain things are not in dispute.  Fama and French, in their article Luck versus Skill in the Cross Section of Mutual Fund Returns, look at the performance of domestic equity funds from 1984 to 2006.  (You can find a summary of the paper here.)  They discover that the funds, in aggregate, are worse than the market by 80 basis points per year–basically the amount of the fees and expenses.  (After backing out fees and expenses, the funds are 10 basis points per year above the market.)  After that, Fama and French run 10,000 simulations with alpha set to zero to see if the distribution of returns from actual fund managers is any different from the distribution of returns from the random simulations.  They conclude it is not very different and suggest that any fund manager that outperforms is simply lucky.

Let me start my critique by pointing out that, based on their sample and their goofy experimental design, their conclusions are probably correct.  Existing mutual funds in aggregate pretty much own the market portfolio and underperform by the amount of fees and expenses.  There clearly are some above-average mutual fund managers, but as Fama and French point out, it’s difficult to tell statistically from just performance data if they are good or simply lucky.  Within a big sample of funds like they had, after all, a few are bound to have good performance just because the sample is so large.

This is quite a quandary for the individual investor, so let’s think about the realistic scenarios and their outcomes–in other words, let’s take actual investor behavior into account.

Scenario 1.  Buy a mutual fund after its good performance is advertised somewhere and bail out when it has a bad year.  Continue this behavior throughout your investment lifetime.  According to Dalbar’s QAIB and other data, this is what actually happens most of the time.  Not a good outcome–underperformance by a large margin, often 500 basis points or more annually.

Scenario 2.  Buy a decent mutual fund and make the radical decision to leave it alone, come hell or high water.  Do not be tempted by the blandishments of currently hot funds or panicked by underperformance in your fund when it inevitably happens.  Close eyes and hold on for dear life.  Continue your ostrich-with-its-head-in-the-sand routine throughout your investment lifetime.  Your outcome, as Fama and French point out, will probably be market returns less the 80 basis point per year in fees.  Your returns will probably be 400 basis points annually or more better than Scenario 1.

Scenario 3. Throw active management overboard entirely.  Buy an S&P 500 index fund or a total market index fund and proceed as in Scenario 2.  Your outcome might be 60-70 basis points per year better from reduced costs than the investor in Scenario 2.  (Your cost is that you don’t get to brag at cocktail parties on the occasions when your actively managed fund has a good year.)  On the other hand, you are no less likely to succumb to Scenario 1 than an actively managed mutual fund investor.  Unfortunately, index mutual funds tend to show the same pattern of lagging returns due to investor behavior as actively managed funds.

Scenario 4. Visit Ken French’s own website.  Look for factors that are tested and that have outperformed consistently over time.  Hint: relative strength.  (Academics tend to call it ”momentum,” I suspect because it would be very deflating to have to admit that anything related to technical analysis actually works.)  Find a manager that exposes a portfolio to the relative strength factor in a disciplined fashion over time.  Buy it and pretend you are Rip Van Winkle.  Continue this dolt-like behavior for your entire investment lifetime.  Your outcome, according to Ken French’s own website, is likely to be market outperformance on the magnitude of 500 basis points per year or more.  (You can link to an article showing a performance chart back to 1927 here, and the article also includes the link to Ken French’s database at Dartmouth University.)

I prefer Scenario 4, but maybe that’s just me.  Since it is well-known even to Eugene Fama and Ken French that momentum has outperformed over time, what is their study really saying?  It’s saying that essentially no one in the mutual fund industry is employing this approach.  That’s more a problem with the mutual fund industry than it is with anything else.  (Mutual fund firms are businesses and they have their reasons for running the business the way they do.)  One option, I guess, is to throw up your hands and buy an index fund, but maybe it would make more sense to seek out the rare firms that are employing a disciplined relative strength approach and shoot for Scenario 4.

Their flawed experimental design makes no sense to me.  Although I am still 6’5″, I can no longer dunk a basketball like I could in college.  I imagine that if I ran a sample of 10,000 random Americans and measured how close they could get to the rim, very few of them could dunk a basketball either.  If I created a distribution of jumping ability, would I conclude that, because I had a large sample size, the 300 people would could dunk were just lucky?  Since I know that dunking a basketball consistently is possible–just as Fama and French know that consistent outperformance is possible–does that really make any sense?  If I want to increase my odds of finding a portfolio of people who could dunk, wouldn’t it make more sense to expose my portfolio to dunking-related factors–like, say, only recruiting people who were 18 to 25 years old and 6’8″ or taller?  In the same fashion, if I am looking for portfolio outperformance, doesn’t it make a lot more sense to expose my portfolio to factors related to outperformance, like relative strength or deep value, rather than to conclude that managers who add value are just lucky?  No investigation of possible sub-groups that were consistently following relative strength or deep value strategies was done, so it is impossible to tell.  Fama and French are right, I think, in their assertion that plenty of luck is involved in year-to-year performance, but their overall conclusion is questionable.

In short, I think a questionable experimental design and possible sub-groups buried in the aggregate data (see this post for more information on tricks with aggregate data) make their conclusions rather suspect.

—-this article originally appeared 12/3/2009.  It turned out to be one of the blog readers’ favorite rants, so I am reprising it here.  I still think active management can add value over time through disciplined exposure to a reliable return factor.

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From the Archives: Why Systematic Models Are Great

March 22, 2012

James Montier wrote this piece in 2006, but it is so great that I have to bring it up again!  This article is a gem, worth reading over and over again.

What could baseball, wine pricing, medical diagnosis, university admissions, criminal recidivism and I have in common? They are examples of simple quant models consistently outperforming so-called experts. Why should financial markets be any different? So why aren’t there more quant funds? Hubristic self belief, self-serving bias and inertia combine to maintain the status quo.

Montier gives numerous examples of situations in which the models outperform both experts and experts using the models as additional input.  Using your “expert knowledge” just makes it worse most of the time.  In fact, in a study of over 130 papers comparing systematic models with human decision-making, the models won out in 122 events.

So why don’t we see more quant funds in the market? The first reason is overconfidence. We all think we can add something to a quant model. However, the quant model has the advantage of a known error rate, whilst our own error rate remains unknown. Secondly, self-serving bias kicks in, after all what a mess our industry would look if 18 out of every 20 of us were replaced by computers. Thirdly, inertia plays a part. It is hard to imagine a large fund management firm turning around and scrapping most of the process they have used for the last 20 years. Finally, quant is often a much harder sell, terms like ‘black box’ get bandied around, and consultants may question why they are employing you at all, if ‘all’ you do is turn up and crank the handle of the model. It is for reasons like these that quant investing will remain a fringe activity, no matter how successful it may be.

Lack of competition may be the best reason of all to use a systematic approach.  How many investors are willing to go through a thorough and rigorous testing process to build a robust model—and are then willing to stick with the model through thick and thin?  As Montier points out, it may remain a “fringe activity” no matter how successful it is.

—-this article originally appeared 12/22/2009.  This is a powerful, powerful argument in favor of using a systematic model.  Montier’s discussion of why investors resist using models is still very true.

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From the Archives: Sorry, No Correlation

March 21, 2012

How should today’s news, that the nation’s gross domestic product rose at a lower annual rate in the third quarter than previously estimated, factor into your investment decisions?  Bad news for stocks?

Recently, Brandes issued a report, Gross Domestic Product: A Poor Predictor of Stock Market Returns, that points out that stock market performance has not been correlated with GDP performance.  Note this research covers an 80 year period of time.

Exhibit 1 shows the predictive power of changes in GDP (in explaining concurrent equity returns) was not statistically significant.  The coefficient of determination, or the portion of the stock market performance, explained by GDP changes, is only 0.1619, and the regression line is a poor fit.

(Click to Enlarge)

In addition, Exhibit 2 reveals that predictive power for changes in GDP in explaining subsequent equity returns is not statistically significant. The coefficient of determination for this relationship is 0.0225, and again, the fit of the regression line is poor.

(Click to Enlarge)

It may seem logical to you to try to link GDP growth with stock market performance, but the results just don’t back that thesis up.  I believe that these results confirm that investors are best served  by focusing on the price movement of a security/market itself when evaluating the merits of an investment.

—-this article originally appeared 12/22/2009.  It’s a very good reminder to stay focused on the relative strength of the individual security and not on all of the surrounding economic noise.  The fact is that there is no correlation, and where there is some relationship, it is usually the stock market that leads.

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From the Archives: Capturing Trends

March 19, 2012

Intuitively, investors feel like the more nimble they are, the better they will do.  They put tremendous pressure of themselves to capture every wiggle in the market.  Yet, much of the time, going faster is counterproductive.

In this blog post, “Understanding How Markets Move,” noted psychologist and trader Brett Steenbarger uses the simple example of a moving average system applied to the S&P 500.  The more you speed up the moving average, the worse it does.  That seems counter-intuitive, but you have to keep in mind that trends are what make money and trends  are often slowThe faster you go, the more noise you capture, and thus, the worse you do.

We find exactly the same process at work when using relative strength.  Reacting to short-term relative strength does not perform well over time.  The best-performing models follow intermediate to long-term relative strength—and just tough out the periods that are rocky.  Many clients have trouble sitting still when going through a rocky period, but as Steenbarger points out in his post, you have to deal with the asset you’re trading.  Stocks have their own time frames for trends and an impatient investor isn’t going to speed it up.  If you want to trade financial assets, you have to work with them on their own terms.

—-this article originally appeared 12/16/2009.  Repeat after me: going faster is counterproductive.  The last nine months or so have been lousy for trends, so it’s prime time for thinking that trends could be captured if only one were more nimble.  Tough periods don’t last.  The market will trend again when it feels like it!

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From the Archives: Beating Buy-and-Hold, Again

March 16, 2012

Although it always seems counterintuitive for incredibly simple momentum strategies to be able to beat the market, yet more evidence is provided in a brief article from CXO Advisory.  (Relative strength is often called “momentum” in academic literature.)

Their method was simple.  They used the nine domestic sector SPDRs, held the top one based on a simple momentum ranking, and revisited the ranks monthly, switching if necessary.  Three simple models were used: 1) top 6-month return, 2) top 6-month return ending 1 month ago, and 3) top 6-month return or cash if the top sector SPDR was below its 10-month moving average (a la Mebane Faber’s paper).

You can see the equity curve below, although there is better detail in the original article.  (The model that can go to cash was obviously helped by two big bear markets in the last ten years; in an up market decade it might be different.)

Now, I’m not sure any compliance department would sign off on a strategy that only held one sector at a time, but it is certainly eye-opening that all three strategies outperformed the market.  This finding is rampant throughout many, many academic and practitioner studies, including ones archived on our website.  Systematic use of relative strength works.

—-this article was originally published 12/22/2012.  Evidence for the effectiveness of relative strength continues to pile up, most recently in the five-year performance of PDP.

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From the Archives: Anti-Equity Sentiment

March 15, 2012

Time will tell whether Institutional Investor’s Julie Segal was prophetic or just susceptible to well-know behavioral finance tendencies in her article, The Equity Culture Loses Its Bloom, in which she gives a host of reasons why there is no hope for equities going forward.  However, I think she has accurately captured the current fears of many investors.

As investment moves away from equities, speculation will likewise shift from stocks to other investments, including real estate, commodities and currencies. “The money supply won’t shrink, and those dollars will need a home,” says Bove. Alternatives will continue to attract money from investors’ erstwhile equity allocations.

Surely, the mindset explained in the article goes a long ways toward explaining why there has been so much demand for our Global Macro strategy this year, which can invest in U.S. equities (long & inverse), international equities (long & inverse), currencies, commodities, real estate, and fixed income.  Global Macro is available as a separate account and through the Arrow DWA Tactical Fund (DWTFX).  The Global Macro portfolio comes along with a systematic method for determining when and how much exposure to take in various asset classes as conditions change.

Click here to visit ArrowFunds.com for a prospectus & disclosures.  Click here for disclosures from Dorsey Wright Money Management.

—-this article originally appeared 12/21/2009.  It’s clearly true that investors still don’t like equities!  Many advisors are also quite leary of piling into bonds at this stage in the recovery.  Global Macro might still be a useful way of easing clients back into the financial markets.

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From the Archives: Diversification Mixup

March 13, 2012

One of the principles of strategic asset allocation is that you can reduce your risk by combining assets that have low or negative correlations.  It requires the correlations between asset classes to be stable.  Unfortunately, that is not the case.  As a recent article in the Wall Street Journal points out:

As stocks retreated and recovered in the past 15 months, commodities investments moved in step with the U.S. market.

That wasn’t supposed to happen.

Investing in commodities long has been pushed as a useful way to cushion portfolio risk. “We haven’t seen the independence [in commodities returns] that you’d hope for in a diversified portfolio,” says Jay Feuerstein, chief executive of Chicago commodity-trading adviser 2100 Xenon Group.

This time, instead of moving independently of stocks, commodities have moved almost in lockstep with equities.  The diversified portfolio you thought you built really isn’t diversified at all.  To my way of thinking, this argues strongly in favor of tactical asset allocation where the portfolio is based on the current behavior of the individual components and not on some pretend correlation.

—-this article was originally published 12/29/2009.  Tactical asset allocation is still a good way to deal with some of the problems created by changing correlations.

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From the Archives: RS Primer

March 9, 2012

Good primer on relative strength by CSS Analytics:

I have done a lot of research in this area and the first conclusion I can make is that it should be a major portion of any trader or investor’s portfolio strictly because it is so durable and robust. Whether it’s asset classes, sectors, stocks, commodities, currencies—-you pick a time frame over the last 40-50 years and this simple method of buying strength and selling weakness has outperformed traditional buy and hold strategies. This outperformance or alpha is also robust to most transaction cost assumptions.

Four-stage model depicting how relative strength occurs:

Based on my own observation and theory I feel that a simple four-stage model best depicts how relative strength occurs and why it takes time to develop rather than occuring instantaneously. The relative strength effect is driven by behavioural feedback loops where investors sequentially pour money into the asset du jour for a plethora of reasons including positive perceived fundamentals, psychological beliefs such as fear or greed, or for positive economic or default risk factor sensitivity. Essentially it starts when certain investors create a theory such as: “emerging markets will outperform because of the accelerated pace of development” and begin to accumulate investments in assets tied to this theory (Stage 1: the early adopters). As time goes on the theory itself becomes more widely known and the rationale becomes more widely accepted. Others quickly catch on and start investing in the same idea (Stage 2: recognition and acceptance). The next stage (and longest stage) is where initial investors wait for hard proof that the idea or theory is supported by tangible evidence in a variety of forms whether economic indicators, qualitative or anecdotal accounts to mention a few. (Stage 3: validation). The “Validation Stage”  tends to last long as the early investors are looking for ongoing proof that supports or refutes their theory. The nature of economic data and other information sources is that they require multiple readings to establish that a trend is in fact statistically valid.  This is why it is impossible for markets to adjust instantaneously even with purely rational investors. There are two paths the validation stage can take—either the evidence to refute the theory is strong, and as a consequence momentum will fail as early investors bail out. Or if the evidence continues to support and even exceed expectations, the early investors will add to their positions alongside the second stage investors. This added money flow cements the trend and the relative strength begins to really accelerate. At this point we reach the final stage where everyone agrees that a given market is and should go up and people are hopping on the bandwagon simply because the market is going up. This is both the fastest stage and the most rewarding per unit of time (Stage 4: mania).

—-this article originally appeared 12/29/2009.  It’s still a good reminder of how robust and durable relative strength is.  Human nature doesn’t change much.

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From the Archives: Constancy of Human Behavior

March 8, 2012

NY Magazine recently interviewed James Grant, well-known financial philosopher, to get his take on the economy and financial markets.  The article is full of nuggets of wisdom, including the following:

Grant’s second cause for optimism is an observation about human nature, summed up by an epigram he borrowed from the late British economist Arthur C. Pigou: “The error of optimism dies in the crisis, but in dying it gives birth to an error of pessimism. This new error is born not an infant, but a giant.” As peculiar as our economic circumstances may seem to us right now, the way people behave has a certain reassuring constancy—which is to say, we freak out and then we get over it.

Human behavior, if left unchecked, makes it virtually impossible to generate superior investment results over time.  The wide swings in optimism and pessimism that are part of the human condition present a serious challenge to the flexibility required to capitalize on investment opportunities.  Rather than trying to train ourselves to be emotionless (which won’t happen), our solution is to rely on systematic relative strength models (which are emotionless.)

The reality is that there are times when we should be pessimistic and times when we should be optimistic, but without a system to overcome behavioral tendencies, we are likely to be unable to capitalize on those opportunities.

—-this article was originally published 12/29/2009.  We are about three years from the market bottom in March 2009 now and it’s very clear that the error of pessimism was born a giant!  Investors have continued to pile into bonds that are now trading at 50x their coupon rate, while a 100% gain in the broad market indexes has gone unnoticed.  That Pigou was a pretty smart guy.

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From the Archives: Chaotic Evolution

February 6, 2012

John Kay of the Financial Times has recently written a nice article explaining why the chaos of free markets leads to significantly better results than centrally-planned economies, as has been tried and failed in the Soviet Union, East Germany, Nigeria,  and Haiti (and periodically makes inroads in economies found in Great Britain, the United States, and others.)

Kay explains that free markets generate superior results because:

Prices act as signals – the price mechanism is a guide to resource allocation rather than central planning. Markets are a process of discovery – an economy adapts to change through a chaotic process of experimentation. The third element is the capacity of the market to bring about diffusion of political and economic power. This is the most effective way to protect society from rent-seeking – a culture in which the principal route to wealth is not creating wealth, but attaching oneself to wealth created by others…

… Centralized systems experiment too little. They find reasons why new proposals will fail – and mostly they are right. But market economies thrive on a continued supply of unreasonable optimism. And when, occasionally, experiments succeed, they are quickly imitated.

If market economies are better at originating and diffusing new ideas, they are also better at disposing of failed ones. Honest feedback is not welcome in large bureaucracies, as the UK government’s drug advisers can testify. In authoritarian regimes, such reporting can be fatal to the person who delivers it.

Disruptive innovations most often come to market through new entrants. The health of the market economy depends on constant replenishment of ideas, often from unpredicted sources. If you had been planning the future of the computer industry in the 1970s, would you have asked Bill Gates and Paul Allen? If you had been planning the future of European aviation in the 1980s, would you have asked Michael O’Leary or Stelios Haji-Ioannou? If you had been planning the future of retailing in the 1990s would you have asked Jeff Bezos? Of course not: members of the politburo, cabinet or large company board would have consulted grey men in suits like themselves.

I wholeheartedly agree with Kay’s macro-economic analysis.

Furthermore, this line of logic also underpins the process that we employ to manage money.  Price (specifically relative price performance) acts as a signal to guide portfolio allocation.  We rely on rules-based relative strength models to sort out the winners from the losers from a given investment universe.  We buy any security that meets our criteria and sell every security out of the portfolio that fails to maintain strong relative strength.  There are no committee meetings where the portfolio managers debate the merits of the stocks before making a decision.  There is no emotional attachment to current holdings.  Rather, the models, which we have designed,  execute a plan that is based on a method with a track record of generating superior investment results over time.  A large percentage of our trades turn out to be either losers or just market performers.  To the uninitiated, the process can indeed appear to be chaotic.  It certainly leads to inferior investment results over certain periods of time (just like free-market economies periodically experience difficulty.)  It is only a minority of our trades that turn out to be the big long-term winners.  Frequently, the trades that end up generating the biggest gains are trades that made us scratch our heads when they were added to the portfolio.

It turns out that perceived chaos, on both the macro-economic level and on the portfolio management level, leads to very desirable outcomes over time.

—-this article was originally published 11/4/2009.  Price acts as a signal in portfolios too.

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From the Archives: Thinking of Relying on an Expert?

February 3, 2012

From The Frontal Cortex:

In the early 1980s, Philip Tetlock at UC Berkeley picked two hundred and eighty-four people who made their living “commenting or offering advice on political and economic trends” and began asking them to make predictions about future events. He had a long list of pertinent questions. Would George Bush be re-elected? Would there be a peaceful end to apartheid in South Africa? Would Quebec secede from Canada? Would the dot-com bubble burst? In each case, the pundits were asked to rate the probability of several possible outcomes. Tetlock then interrogated the pundits about their thought process, so that he could better understand how they made up their minds. By the end of the study, Tetlock had quantified 82,361 different predictions.

After Tetlock tallied up the data, the predictive failures of the pundits became obvious. Although they were paid for their keen insights into world affairs, they tended to perform worse than random chance. Most of Tetlock’s questions had three possible answers; the pundits, on average, selected the right answer less than 33 percent of the time. In other words, a dart-throwing chimp would have beaten the vast majority of professionals. Tetlock also found that the most famous pundits in Tetlock’s study tended to be the least accurate, consistently churning out overblown and overconfident forecasts. Eminence was a handicap.

This is the very reason that we rely on systematic trend following. Experts may sound convincing, but don’t count on their predictions.

—-this article was originally published 11/17/2009.  Expert opinion is still worse than random chance.  Improve your odds with a systematic investment process.

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From the Archives: Supply & Demand is Everywhere

February 1, 2012

NPR has a great story about monkey economics and how special skills in short supply translate into higher monkey income.  I first saw this on Greg Mankiw’s blog.  Even monkeys bow down to supply and demand!

—-this article was originally published 11/12/2009.  Human economics and monkey economics are exactly the same–scarcity creates value.  The story is quite funny too.

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From the Archives: Another Way To Look at Modern Portfolio Theory

January 27, 2012

This week the noted management consultant, Russell Ackoff, passed away.  He was famous for gathering data and trying to use it to make the correct decision.  His fundamental theory was this:

All of our social problems arise out of doing the wrong thing righter. The more efficient you are at doing the wrong thing, the wronger you become. It is much better to do the right thing wronger than the wrong thing righter! If you do the right thing wrong and correct it, you get better!

Since the origination of Modern Portfolio Theory in the 1950s, academics and practitioners have been polishing it up and implementing in better and better ways.  It may just have been a case of getting more efficient at doing the wrong thing—and the wronger it got.  After 2008, even many of its supporters began to acknowledge that there were problems with its implementation.

This recognition has fueled a rush to the new magic potion, tactical asset allocation.  If tactical asset allocation is indeed the “right” thing, it should work out better than doing something wrong.  Yet there are significant challenges in the design and execution of a systematic tactical asset allocation process as well.  I think going forward, it’s going to be important to distinguish between marketers who are trying to exploit the latest fad and practitioners who have a well-thought-out and well-executed process for tactical asset allocation.

—-this article was originally published 11/13/2009.  It’s hard to do the right thing right, but don’t settle for doing the wrong thing righter!

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From the Archives: Will I run out of money?

January 25, 2012

The number one concern among many investors approaching retirement is, “Will I run out of money?” This question is causing sleepless nights for many approaching retirement.  In fact, at the end of October, the U.S. Center for Retirement Research released a report that 51% of Americans are at risk of reduced living standards in retirement – including 42% of those in high income households. And if the cost of health care and long-term care were included, these numbers would be even higher.  It is just a fact that many people, including high-income earners, will enjoy a reduced standard of living in retirement due to inadequate savings.

However, simply pointing this reality out to a client with inadequate savings who is approaching retirement doesn’t do them a lot of good.  That information may be motivational to younger people who still have the time to increase their savings, but those approaching retirement need two things.  First, they need financial planning help to determine a prudent withdrawal rate on their portfolio to minimize the risk that they actually do run out of money.  Second, they need help determining a prudent approach to asset allocation to take them through the next 30 plus years.

One of the most influential studies on withdrawal rates and asset allocations in retirement was a 1998 paper by three professors of finance at Trinity University.

Its conclusions are often encapsulated in a “4% safe withdrawal rate rule-of-thumb.” It refers to one of the scenarios examined by the authors. The context is one of annual withdrawals from a retirement portfolio containing a mix of stocks and bonds. The 4% refers to the portion of the portfolio withdrawn during the first year; it’s assumed that the portion withdrawn in subsequent years will increase with the CPI index to keep pace with the cost of living. The withdrawals may exceed the income earned by the portfolio, and the total value of the portfolio may well shrink during periods when the stock market performs poorly. It’s assumed that the portfolio needs to last thirty years. The withdrawal regime is deemed to have failed if the portfolio is exhausted in less than thirty years and to have succeeded if there are unspent assets at the end of the period.

The authors backtested a number of stock/bond mixes and withdrawal rates against market data compiled by Ibbotson Associates covering the period from 1925 to 1995. They examined payout periods from 15 to 30 years, and withdrawals that stayed level or increased with inflation.   The table below shows the percentage of trials in which the portfolios survived for the entire testing period.

Table: Portfolio Success Rate: Percentage of all Past Payout Periods From 1926 to 1995 that are Supported by the Portfolio After Adjusting Withdrawals for Inflation and Deflation

Note: Numbers in the table are rounded to the nearest whole percentage. The number of overlapping 15-year payout periods from 1926 to 1995, inclusively, is 56; 20-year periods, 51; 25-year periods, 46; 30-year periods, 41. Stocks are represented by Standard and Poor’s 500 Index, bonds are represented by long-term, high-grade corporates, and inflation (deflation) rates are based on the Consumer Price Index (CPI). Data source: Calculations based on data from Ibbotson Associates.

Source: Retirement-Income.net

It becomes clear from reviewing this table that being “conservative” and allocating heavily to bonds may be safe in the short run, but it may very well lead to eating dog food over the long term.  Furthermore, any withdrawal rate over 3-4% is likely to be disastrous over a 30 year period of time.

The biggest opportunity for a financial advisor to be able to add value to their client’s dilemma is to be able to help them commit to an appropriate withdrawal rate and then to focus on the asset allocation.  The financial advisor who is able to clearly explain how a global tactical asset allocation strategy may be able to address the weakness of static asset allocation or strategic asset allocation and potentially decrease the probability of running out of money is the financial advisor who can make a real difference for their clients.

—-this article was originally published 11/24/2009.  The payout tables are based on 1926-1995 returns and suggest real conservatism in withdrawal rate assumptions.  Returns since 1995, and especially since 2000, have been lower than the long-term averages.  If you had opted for a high withdrawal rate, things would be tough right now.  Investors need to save more and invest intelligently and patiently to have retirement success.  Consider incorporating portfolio fecundity into your withdrawal assumptions because it will better reflect the current investing environment.

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From the Archives: Why Americans Are in Debt

January 24, 2012

James Surowiecki has a fantastic article in the New Yorker about why Americans take on so much debt.  Incentives work and we have incentives to use debt embedded in our financial structure.  I’m a big fan of his writing anyway, but this short piece explains a lot.

John Kenneth Galbraith wrote that all financial crises are the result of “debt that, in one fashion or another, has become dangerously out of scale.”

That’s his thesis and in a couple of paragraphs he explains how we got there so efficiently.

—-this article was originally published 11/16/2009.  This article has a fantastic explanation of how effectively incentives work.  And a couple of years down the road we can see even more clearly how debt has saddled Western economies.

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From the Archives: A Shocking U-Turn

January 13, 2012

After decades of some consultants and institutions ridiculing proponents of tactical asset allocation or deriding it as “market timing,” some have now apparently become convinced of its benefits as a risk diversifier and return enhancer.  OMG!  According to this article in Pensions & Investments, a number of firms are now poised to roll out their own tactical asset allocation solutions.  Bar the door and hide the children.

—-this article originally appeared 10/7/2009.  In the last couple of years, tactical asset allocation has actually become fashionable—because buy-and-hold isn’t working.  Of course, I don’t think buy-and-hold proponents are dead.  Like Monty Python’s parrot, they’re just resting.

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From the Archives: The Brave New World of Asset Allocation

January 11, 2012

“We think asset allocation, certainly over the next five to 10 years, begs for a tactical component that is very hard for many investors to deal with because they aren’t structured to think about macro things like equity exposure…”  Ah, yes. Now everyone is singing the praises of tactical asset allocation.  The quotation above is from a major article in Barron’s over the weekend, which is an interview with Mark Taborsky, the head of asset allocation at PIMCO. (subscription required)  If you don’t get Barron’s, at the very least you might want to borrow a friend’s copy and take a look at the interview.

Tactical asset allocation is gaining notice because it is a very useful way to navigate what markets are actually doing, instead of what they should be doing in theory.  Taborsky says, “The majority of people who use the modern-portfolio-theory approach — and it has been with us for more than 50 years — recognize that it has many shortcomings. Anyone who has done it more than a year recognizes how far off their estimates of expected returns are by asset class and how far off their expectations of volatilities and correlations are. It is a very elegant approach, but it doesn’t really work that well.”  It’s refreshing to hear someone else make these points for a change!

Mr. Taborsky sums up the shortcomings of traditional strategic asset allocation very concisely:  ”The traditional approach to asset allocation relies on looking back in history to what asset classes returned. There is a huge reliance on mean reversion. There is a huge reliance on historic volatilities and correlations.”  The problem with reliance on historical norms is that when there is a regime change, and the norms change, you are completely at sea.  PIMCO believes that we have had a regime change, which they call the “new normal.”  If they are correct, strategic asset allocation could have a rough go of it for a while.

Tactical asset allocation seems to be the only logical way to respond systematically to the constantly changing relationships between asset classes.  Our Systematic RS Global Macro strategy (in separate account form or in mutual fund form in the Arrow DWA Tactical Fund) is designed to handle the rotation among asset classes for investors.  Given the fear that retail investors still harbor, it might be just the thing to consider when moving cash from the sidelines back into the markets.

Click here to visit ArrowFunds.com for a prospectus & disclosures.  Click here for disclosures from Dorsey Wright Money Management.

—-this article originally appeared 10/5/2009.  It’s amazing that retail investors are still as nervous now as they were then!  Strategic asset allocation is still subject to breakage every time there is a regime change.  Tactical asset allocation won’t always have smooth sailing either, but it has the prospect of being able to adapt to new conditions.

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From the Archives: Prices are “Objective Reality”

January 9, 2012

Barry Ritholtz succinctly makes the case for relative strength (without actually using the term relative strength.)

—-this article originally appeared 10/7/2009.  My favorite quote from Barry’s piece:  “Indeed, prices matter a great deal more to traders than theories or annoying things like ‘Objective Reality.’ To a trader, prices ARE the objective reality; to them economic theorists are peripheral players trying to rationalize reality.”  Price is what matters, and relative strength uses only price.

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From the Archives: Investor Overreaction

January 4, 2012

Investors overreact to good and bad short-term results.  So says Morningstar in their article “Why Your Results Stink.”  A quote from the article:

Why do investors make such a mess of things? In short, because of volatility, emotion, and a focus on short-term results. Volatile funds push all the wrong emotional buttons. When they go way up, we get greedy and buy. When they go way down, we despair and bail out. And we read too much into recent performance.

Destructive investor behavior has been well-documented and yet it persists.  Why?  My guess is that it is because most investors are operating without any kind of systematic framework for decision-making.  Creating a systematic process demands much more work.  You have to start with a theory and then do extensive, rigorous testing to see if your hypothesis holds up.  Even when it does, you will see quite clearly that your strategy is not always optimal–there will be certain quarters and/or certain market conditions in which it will perform poorly.

For some reason, investors have a hard time with this.  They don’t just want to win over time; they want to win all the time.  In their quest to avoid the psychic pain of occasional losses, they react emotionally with predictable long-term results.

With a systematic process in place, on the other hand, you’re not a loser just because you will lose periodically; you tend to be a loser if you quit before giving the process adequate time to work.  There are no guarantees in investing, but reacting emotionally is usually a route to poor results.

—-this article was originally published 10/13/2009.  With year-end performance results coming out shortly from many managers and mutual funds, this is the prime season for overreaction.  Bad year, dump the manager.  Good year, double up.  That’s how investors pile into the hot asset classes right before they blow up—or bail out of the styles that are poised for good performance going forward.

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From the Archives: What It Takes to Manage Money

December 8, 2011

William Bernstein has an eclectic background and is well-known in the world of finance.  He’s done a lot of thinking about asset allocation and runs the Efficient Frontier website as well.  An excerpt from the foreword of his new book has a discussion of the qualities it takes to manage money well.  The emphasis is mine.

Successful investors need four abilities. First, they must possess an interest in the process. It is no different from carpentry, gardening, or parenting. If money management is not enjoyable, then a lousy job inevitably results, and, unfortunately, most people enjoy finance about as much as they do root canal work.

Second, investors need more than a bit of math horsepower, far beyond simple arithmetic and algebra, or even the ability to manipulate a spreadsheet. Mastering the basics of investment theory requires an understanding of the laws of probability and a working knowledge of statistics. Sadly, as one financial columnist explained to me more than a decade ago, fractions are a stretch for 90 percent of the population.

Third, investors need a firm grasp of financial history, from the South Sea Bubble to the Great Depression. Alas, as we shall soon see, this is something that even professionals have real trouble with.

Even if investors possess all three of these abilities, it will all be for naught if they do not have a fourth one: the emotional discipline to execute their planned strategy faithfully, come hell, high water, or the apparent end of capitalism as we know it. “ Stay the course ” : It sounds so easy when uttered at high tide. Unfortunately, when the water recedes, it is not. I expect no more than 10 percent of the population passes muster on each of the above counts. This suggests that as few as one person in ten thousand (10 percent to the fourth power) has the full skill set. Perhaps I am being overly pessimistic. After all, these four abilities may not be entirely independent: if someone is smart enough, it is also more likely he or she will be interested in finance and be driven to delve into financial history.

But even the most optimistic assumptions — increase the odds at any of the four steps to 30 percent and link them — suggests that no more than a few percent of the population is qualified to manage their own money. And even with the requisite skill set, more than a little moxie is involved. This last requirement — the ability to deploy what legendary investor Charley Ellis calls “ the emotional game ” — is completely independent of the other three; Wall Street is littered with the bones of those who knew just what to do, but could not bring themselves to do it.

I am most interested in the emotional game.  We use a systematic investment process that is objective and unemotional for just that reason, but our firm is rare in the industry.  Most everyone else flies by the seat of their pants for security selection and asset allocation.  It’s very possible to have some remarkable successes that way when you hit something just right, but it’s very difficult to sustain the success, especially when, as Bernstein phrases it, the tide goes out.

I was working late last night on proxies (fun, fun) and happened to answer a call from an investor interested in using our services.  He talked a good game, told me all about his views on the dollar and the market, and told me that he was a “sophisticated investor.”  But what had he done?  He was invested with a value manager and hung in until November 2008, when he finally lost his nerve and sold out.  He mocked the value manager for continuing to buy on the way down because securities were perceived bargains, although that is pretty much the job description for a value manager.  He felt good that he had missed a few months of the bear market, from November to March 2009.  But he never had the nerve to get back in, and railed against the rise in the market as a “false rally.”  I’m sure that characterizing market action that way helped ease the sting of completely missing the boat.  Since the S&P 500 is now higher than it was in November, his emotions have cost him a fair amount of money.  This is a very typical investor and a very typical sequence–the first story or impression you get is rarely the whole story.  The client was pretty sophisticated about markets, but totally lacking in emotional resilience.

Following the path of least emotional discomfort is a road to failure.  In my view, using a tested, systematic process is the only way to succeed in the very long run.

—-this article was originally published 10/23/2009.  Recent volatility and news sensitivity have caused investors to damage themselves again, just like 2008-2009.  Emotional resilience is still the key to long-term investment success.

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From the Archives: Commodities Can Burn Your Fingers

December 2, 2011

The Financial Times of London had an interesting article about commodities that pointed out that buy-and-hold is not a useful strategy to employ.  Commodities, because of the frequent lack of correlation with other asset classes, can be an outstanding tool for risk diversification in a portfolio, but they cry out for use in a tactical fashion.  For retail clients, being able to get commodity exposure through ETFs and ETNs has been extremely helpful, but it may be important to have some kind of systematic tactical process in place as well.  Holding positions for long periods of time just to have exposure may not be the optimal strategy.

—-this article was originally published 10/13/2009.  Buy-and-hold in the commodity futures world is just as dangerous as ever, what with contango waiting to jump up and bite you.  A rotational strategy makes sense for exposure to this asset class.

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