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Are markets misreading economy’s strength?

In April, volatility became the most visible characteristic of the markets, often fluctuating between gains and losses of 1 percent in a single session.

Clearly, markets are confused and participants have low future visibility. Some participants worry about a slowdown in the U.S., others are concerned with China’s apparent growth problems, and still others point to high P/E ratios with little or no growth in top line revenues.

Falling equity values and rising bond prices represent either a periodic correction of an overvalued market, or the perception that economic growth is slowing or a recession is approaching.

We clearly aren’t anywhere near a recession, so the question is whether or not the recent market volatility is a signal that the economy is slowing or just one of those periodic episodes that cause a lot of consternation but turn out to be benign.

Weak winter data

The February data, while somewhat weak, were not devastatingly so, and most of March’s data came in at or slightly below expectations. Because Wall Street takes the data pronouncements of the various government departments as gospel, many pundits concluded that the lower than expected data indicated that the economy was slowing.

The Institute for Supply Management produces two monthly macroeconomic indicators, the Manufacturing Index and the Non-Manufacturing Index. Both of these are seasonally adjusted.

The Manufacturing Index was 53.2 in February (anything above 50 means expansion) and 53.7 in March, significantly higher that its 51.3 January reading. Nevertheless, this indicator was below the 55-57 levels of last summer and fall. The Non-Manufacturing Index showed a similar pattern, with March at 53.4, but well below the 59-62 range registered in the autumn.

Issues with adjustment

I believe that the seasonal adjustment process itself is an issue that is clouding the underlying strength of the economy.

The process uses historical data to try to “normalize” economic indicators to get rid of seasonal issues, like heavy holiday spending at year’s end, so that month to month sequential data is comparable.

As such, the seasonal factors measure an “average” seasonality over a period of time. We can think of the historical data as forming a normal distribution with the seasonal factor as the mean. If the distribution is tight, then the process does a good job in “normalizing” the data.

But if the distribution is wide with large tails, if events fall into one of those tails, then the seasonal adjustment process might, itself, be misleading. Since the winter was one of the worst ever recorded in many parts of the country and was, at least by anecdotal reports, likely two standard deviations away from “normal,” the data almost certainly understate the true underlying conditions. And so, it is not surprising that the ISM Indexes are showing up well below their levels of last fall.

The Department of Commerce puts out a monthly index of retail sales. The seasonal factors for “Retail and Food Services” for the last four Januarys are as follows:

2011: 0.901

2012: 0.900

2013: 0.915

2014: 0.918.

The Not Seasonally Adjusted (“NSA”) or raw data are divided by this factor to get the seasonal adjustment data. Note that the January ’14 seasonal factor is 2 percent different from that of 2011 or 2012.

This seems strange. Do buying habits really change that fast? Perhaps this changing seasonal pattern of buying has been caused by Internet shopping. But I digress. What is really important for this column is that we know that the weather had a huge impact, but it clearly isn’t showing up in the seasonal factor given that 2014’s factor is essentially equivalent to 2013’s. This indicates that the seasonally adjusted retail sales data for January could be significantly understated

The problem that the markets apparently had was that the seasonally adjusted December ($428.8) and January ($425.9) numbers were sequentially lower than October ($429.0) and November ($430.1). Remember, the adjustment process is supposed to make the month-to-month numbers comparable.

So to Wall Street, which takes these “guesses” as if they were scientifically precise, this looked like an economic slowdown.

Sales stronger than they appear

The $425.9 billion of January sales are 99.3 percent of that of December and, in fact, those seasonally adjusted sales are 2 percent above the seasonally adjusted $417.9 billion of January 2013.

Given the winter, to me, January 2014 seasonally adjusted sales look pretty strong. To show the sensitivity of the data to the seasonal adjustment factor, what if the seasonal factor for January was the same as that used in 2012? If that were the case, adjusted sales would have been $434.4 billion, a 1.3 percent increase from December and a 1.0 percent increase from the November peak.

Even the recently released March data, which appeared to calm the nerves of the growth skeptics (seasonally adjusted $433.9 billion), appears somewhat light given that winter still impacted the month in some parts of the country.

It should now be quite clear that the seasonally adjusted data can be misleading when the “season” significantly deviates from its norm — in this case winter weather. Data for April and May (weather permitting) will confirm whether the winter month’s data, which appeared to be weak and did not meet expectations, were due to the harsh winter and seasonal adjustment issues, or to an emerging economic slowdown. In my view, the odds favor the former.

Historically, market corrections that are not accompanied by a growth slowdown, a recession or an exogenous disruptive event are generally short-lived. Today, with the Fed bending over backward to tell markets that interest rates are not going to rise anytime soon, there may be an emerging opportunity to take advantage of lower equity pricing.

Robert Barone (Ph.D., economics, Georgetown University) is a principal of Universal Value Advisors, Reno, a registered investment adviser. Barone is a former director of the Federal Home Loan Bank of San Francisco and is currently a director of Allied Mineral Products, Columbus, Ohio, AAA Northern California, Nevada, Utah Auto Club, and the associated AAA Insurance Co., where he chairs the investment committee.

Contact Robert Barone or the professionals at UVA (Joshua Barone and Andrea Knapp) who are available to discuss client investment needs. Call them at 775-284-7778.

Statistics and other information have been compiled from various sources. Universal Value Advisors believes the facts and information to be accurate and credible but makes no guarantee to the complete accuracy of this information.

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