When testing a model it is always difficult to determine if the results you are achieving are repeatable or not.  If you are testing a high relative strength model, for example, are the results coming from one or two stocks that make the whole test look fantastic?  If that is the case I would have my doubts about how that strategy would perform in real-time.  But if the results are truly from an underlying factor performance (regardless of the individual securities in the portfolio) then you have something you can work with.

The way we determine if a model is lucky or not is to run multiple simulations based on a random draw of securities.  In a relative strength model we might break our universe into ten different buckets.  Out of the highest bucket we might draw 50 stocks at random.  We hold those stocks until they are no longer classified as high relative strength securities.  Once they fall below a specific rank we sell the security and buy another one at random.  If we run 100 trials we get 100 different portfolios over time.  What we are trying to determine is if the individual securities in the test really matter, or is just the concept of buying high relative strength securities over time what causes the outperformance.

As it turns out, what stocks go in to the portfolio aren’t as important as exploiting the factor.  A disciplined approach is that consistently drives the portfolio to strength is what drives the returns over time.

(Click To Enlarge)

The table shows the results from one of the factors tested in the paper.  You can see the range of outcomes each year as well as how each model did over the 16 year test period.  Sometimes the models outperform, sometimes the underperform, and some years you have mixed results.  But over 16 years, all of the models outperformed!  All we did was pick stocks at random out of a high relative strength basket.  There is nothing complicated about it.  The main thing is that the process is systematic and extremely disciplined.

More details about the testing process and results can be found in the paper (click here).

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.

The fact that interest rates tell us the truth about ourselves is intolerable to the political class. They don’t want us to be told the truth. They want low interest rates to foster the illusion that inflation is low in order to create the perception that capital is abundant, and to enable their governments to borrow more than they should by subsidizing the interest rates through money creation; the latter necessary to muffle the alarm bells of rising default risk.

But if the interest rate is the basis on which all investments, or for that matter, all spending decisions are made, and the interest rates are being distorted by central banks, then that means that all valuation is plunged into chaos. That is exactly what is happening right now. Nobody knows how to value anything. (emphasis added)

Valuation models are vulnerable to paradigm shifts.  Interest rates are arguably being manipulated to a much greater degree than has been seen in the past.  Price, on the other hand, will always be the intersection of supply and demand.  Trend following models should do just fine in an era of highly manipulated interest rates and are likely to effectively capitalize on the resultant bubbles.

The Conference Board has made the first major overhaul of the components of the LEI since it assumed responsibility of the index in 1996. It replaced real money supply with its proprietary leading credit index, and the ISM supplier delivery index with the new orders index. In place of the Thomson Reuters/University of Michigan consumer expectations measure, it will now use an equally weighted average of its own consumer expectations index and the current measure. Also, the nondefense capital goods gauge was tweaked to exclude commercial aircraft.

The impact of these changes has been shocking, and really questions the credibility of constructing LEIs. The old LEI rose to a new record high in November, exceeding the previous cyclical peak (where it hovered during 2006 and 2007) by 12.7%. The new LEI edged back up in December to its previous high for the year during July, but that’s 13.1% below the previous cyclical peak!

I added the bold, but you can see why economists are shocked when you see the visual difference in the chart reproduced below (I think Dr. Yardeni included the ECRI leading indicator for good measure):

Source: Ed Yardeni/Conference Board/Haver Analytics (click on chart to enlarge)

The old LEI is blasting off into the stratosphere, but the new LEI is still way, way below the old highs.  In addition, the old LEI showed a very modest decline from the 2006 peak, while the new version shows a bloodbath that took out the 2000-2002 recession lows!

Mr. Yardeni has a very apt comment on the problems with indicators that are revised:

These man-made indexes combine a bunch of indicators that purportedly lead the business cycle. When they fail to do so, the men and women who made these indexes recall them, retool them, and send them back out for all of us to marvel at how well these new improved versions would have worked in the past. I can accurately predict that when they fail in the future, they will be recalled and redesigned yet again.

Of course, it’s not just the US LEI that economists revise.  They revise GDP, CPI, employment data, and virtually everything else.  Analysts revise earnings estimates with regularity, which I suppose is a good way to avoid saying “Our old estimate turned out to be wrong.”

Here we see one of the benefits of using relative strength: since it uses only market prices, it is not subject to revision.  Prices reflect true supply and demand.  No one can come back to you and say, “You know those IBM shares you sold in 2010 for $141?  We’ve revised the data and it was really only $123, so you need to send us a check.  Of course, we might revise it again later, so keep your address current.”  It is difficult to make good investment decisions even when using good data!  It’s got to be near impossible using data that turns out to have been completely wrong.

The degree to which central banks around the world are printing money is unprecedented.

He proceeds to show the balance sheets for each of the large central banks, converted back into dollars.  Your eyes will bug out when you see the original article.  For the sake of brevity, all I show here is his graphic of the composite of eight large central banks.

Source: Bianco Research/The Big Picture  (click on image for a sharper version)

Jim points out that:

The combined size of  these eight central banks’ balance sheets has almost tripled in the last  six years from $5.42 trillion to more than $15 trillion and is still on  the rise!

I have no idea if this is a good or bad thing.  How you interpret it probably depends on which group of economists you put your faith in.  My guess—and this is only a guess—is that huge increases in the money supply will eventually result in some inflation.  Commodities generally respond fairly well to inflation, while fixed income may be gasping for air.  (This sort of fits the ”retail investor is always wrong” template, given the huge amounts poured into bonds over the last couple of years.)  Inflation might be a good thing from the Federal government’s point of view, as it will make paying off debt a lot less expensive in real terms.  It might not be so good for investors, depending on how their portfolio is constructed.

The one thing I don’t have to guess at is that quantitative easing, whether it continues to accelerate to ever-giddier heights or starts to wind down, will lead to trends of some kind.  When that happens, relative strength will be a useful guide to sort out where the investment opportunities lie.

In the past, when I’ve tried to schedule our window cleaners they have always been able to come within two days. Despite the still-slow economy, the first available appointment this time is not for three weeks.

“Why?” I ask. The owner says that during the worst of the recession his firm had enough clients to survive, but barely; smaller, less efficient companies died off. Now that demand for cleaning has increased, his own customers are coming back; and the customers of the now-defunct companies are hiring him too, so he’s swamped with business. Recessions kill off inefficient firms; but at least in this case, those that survive come out stronger than before.

Relative strength is a good tool for sorting out the winners from the losers.  Companies that have been hit hard from the lingering recession often show weak relative strength, while companies that have managed to power through tough times and grow despite it are often leaders.

Source: Calculated Risk  (click on chart to expand)

Maybe the world isn’t ending after all.  One never knows exactly how investors will respond to economic data, but movement from low levels to consumer sentiment to high levels of consumer sentiment is usually associated with decent equity markets.  The best entries tend to occur when sentiment is very poor—i.e., investors are perhaps overly pessimistic.

Numerous academic studies have confirmed that, when measured in periods of approximately three to 12 months, past investment winners tend to keep on outperforming while past losers tend to keep underperforming.

Momentum is not simply a US phenomenon. A recent study² covering equities in 23 countries from November 1989 to September 2010 found evidence of strong momentum returns in North America, Europe and Asia Pacific; only Japan was an exception. Another study tracking the largest 100 stocks in the British market from 1900 to 2009 found that a portfolio comprised of the 20 best performers over the prior 12 months outperformed the worst performers by 10.3% annually³.  The same authors found momentum in 18 out of 19 markets, dating back to 1975 in larger European markets and 1926 in the US.

Momentum is not confined to portfolios of individual stocks – it exists in a variety of asset classes. A recent study⁴ has found that momentum exists in government bonds, commodities and currencies as well as country equity indexes. Momentum has also been found in corporate bonds⁵ as well as the financial futures market⁶.

The article is well-footnoted.  I recommend you read the original, which I linked to above.  The article does a good job discussing both the pros and cons of relative strength.  For example, the author points out that:

…there are prolonged periods where stocks with positive momentum underperform the market.  Despite an overall annualized premium of 3.9%, there have 22 periods where stocks with positive momentum have underperformed the market by greater than 5%, with durations as long as several years.

Although investors have a marked tendency to abandon strategies when they underperform for a period of time, that might not be a good idea with relative strength.  Despite periods of underperformance, long-term results have been remarkable:

The $1.00 investment in momentum stocks grew to $67,309, nearly 30-times larger than the $2,321 earned in the S&P 500. [August 1927 to July 2011]  For long-term investors, this outperformance has been remarkably enduring. In 99.6% of the 10-year rolling periods since July 1937, momentum stocks have outperformed the S&P 500. [my emphasis]

Investors have a lot of choices when it comes to selecting an investment strategy, but not many have been as well validated over as long a period of time in multiple markets as relative strength.

Source: Ed Yardeni   (click on image to expand)

Ok, so the developed world isn’t really boosting oil demand.  There could be a lot of reasons for that besides a lack of economic growth: conservation, increased efficiency, substitution of other energy sources, etc.  But emerging markets—wow!  The financial crisis was barely a blip in oil demand.

Money will go wherever it is treated best–and it tends to seek out growth.  Markets are global and your portfolio should be too.

First, let me set the scene for you.  Mr. Veres indicated that he had spent a month doing data analysis of a survey of over 1000 financial planners.  One of the most interesting takeaways:

Perhaps the most striking thing I learned is that, post-2008, activities once labeled “market timing” are now solidly in the mainstream.  No, planners are not moving into or out of the market based on reading the entrails of animal sacrifices. But they seem to be taking a much more active approach to protecting clients from downside risk. The survey asked whether advisors planned to raise or lower their allocations to each of 35 different investment classes or vehicles in the next three months. A remarkable 83% are anticipating at least one tactical adjustment – and the great majority expects to make several.

Mr. Veres raises a legitimate question about how accurate planner’s forecasts are, and what the possible consequences of poor forecasts could be.  As an example, he cites inflation forecasts:

One of the most provocative set of responses came when advisors were asked to forecast the inflation rate and the real (after-inflation) return of both equities and 10-year Treasuries over the next 10 years. On inflation, the majority of responses clustered between 3% and 5%, and the remaining responses had a center of gravity on the 6% to 7% part of the chart. If there is wisdom in the crowd, the crowd of advisors seems to believe we will experience above-average inflation for at least the remainder of this decade.

But we also had responses as low as -4% a year (projecting severe Japanese-style deflation), several as high as 10% and one advisor who anticipates annual inflation of 13% over the coming decade. One or the other group on the fringes is going to be spectacularly wrong (or both will), and I suspect that damaging consequences will show up in the portfolios they recommend.

He is absolutely correct in his belief that a strategic allocation based on a wildly incorrect forecast will be damaging to a client.  And, he indicated that expectations for real returns were even more widely dispersed.  It’s where he goes next that made me think.  He writes:

Say what you will about the buy-and-hold ethos that lasted until September 2008. It may not have been an ideal strategy during the worst of the bear markets, but it did keep the members of the herd from straying too far from the center – and, more important, it kept the profession from getting the kinds of black eyes I think advisors are going to encounter in the future.

I think there is a critical error in this line of thinking.  Buy-and-hold strategic allocations are typically based on historic returns.  Those historic returns, of course, are the same for everybody and they do have the effect of keeping everyone in the middle of the herd.

This is the critical error: basing your allocation on historic returns is also a forecast–it’s simply an implicit forecast that historic returns will continue along the same path!  If that doesn’t happen, you will end up just as horribly wrong as the advisors on the forecasting fringes!  Yes, you will fail conventionally along with everyone else in the middle of the herd, but you will fail nonetheless.  (How do you think most clients feel right now, with their equity allocations based for the last decade on an 8-10% historic return, a return that has not materialized?  And there’s always Japan.)

Frankly, if you’re going to do strategic asset allocation at all, research shows that naive equal-weighting performs as well as anything else.  The reason advisors are gravitating toward tactical management in the first place is because traditional strategic asset allocation has so much trouble with tail events, and 2008-2009 was a big tail event.  Clients have memories, and advisors are simply responding to client demand for a more active form of risk management.  Now, like Mr. Veres, I’m not very confident in the forecasting abilities of financial planners.  I’m not very confident in the forecasting abilities of anyone, for that matter, including me.

All forecasting is flawed, whether it is explicit or implicit.  To me, there are only two realistic choices for asset allocation.  Either 1) equal-weight a large number of asset classes and rebalance periodically or 2) commit to a systematic method of tactical asset allocation.  There are funds that use valuation triggers and funds that use relative strength to rotate among asset classes–and I suspect either will perform acceptably over time if it is systematic and disciplined.