dshort.com - Financial Life Cycle Planning

Note from dshort: Highly recommended is the latest of the Institute's public commentaries, Viewing the "Great Recession" in Hi-Def. Scroll down to the entry dated September 1. I've reprinted the concluding two paragraphs below as an inducement to read it in its entirety.

There probably hasn't been two separate recessions in three years, simply one that has evolved in significant ways. But if this really is a "double dip" recession, then our data indicates that the "Great Recession" of 2008 was merely the precursor, and not the main event. It is this current dip that we should be really concerned about; the current contraction in consumer demand is about structural changes in consumer behavior, whereas the "first dip" was about short term loss of consumer confidence.

"This recession has been complex and constantly evolving in ways that policy makers have not been able to understand through their low resolution lenses. As a consequence their policy responses have been misguided, ineffective and wasteful. The Federal Reserve may be able to save the banking system by being the "lender of last resort", but it is powerless to change perhaps the one thing that John Maynard Keynes got right -- and what he mischaracterized as a "Paradox of Thrift" -- as over 100 million U.S. households become economic "loose cannons", acting exclusively in their own best interests in 100 million different ways.

For the past several months, the Consumer Metrics Institute's Daily Growth Index has been one of the most interesting data series I follow, and I recommend bookmarking the Institute's website. Their page of frequently asked questions is an excellent introduction to the servicc.

The charts below focus on the 'Trailing Quarter' Growth Index, which is computed as a 91-day moving average for the year-over-year growth/contraction of the Weighted Composite Index, an index that tracks near real-time consumer behavior in a wide range of consumption categories. The Growth Index is a calculated metric that smooths the volatility and gives a better sense of expansions and contractions in consumption.

The 91-day period is useful for comparison with key quarterly metrics such as GDP. Since the consumer accounts for over two-thirds of the US economy, one would expect that a well-crafted index of consumer behavior would serve as a leading indicator. As the chart suggests, during the five-year history of the index, it has generally lived up to that expectation. Actually, the chart understates the degree to which the Growth Index leads GDP. Why? Because the advance estimates for GDP are released a month after the end of the quarter in question, so the Growth Index lead time has been substantial.

Has the Growth Index also served as a leading indicator of the stock market? The next chart is an overlay of the index and the S&P 500. The Growth Index clearly peaked before the market in 2007 and bottomed in late August of 2008, over six months before the market low in March 2009.

The most recent peak in the Growth Index was around the first of September, 2009, almost eight months before the interim high in the S&P 500 on April 23rd. Since its peak, the Growth Index has declined dramatically and is now deep into contraction territory.

It's important to remember that the Growth Index is a moving average of year-over-year expansion/contraction whereas the market is a continuous record of value. Even so, the pattern is remarkable. The question is whether the latest dip in the Growth Index is signaling a substantial market decline like in 2008-2009 or a buying opportunity like in June 2006. I've also highlighted the recession that officially began in December 2007 and unofficially ended last summer. As a leading indicator for GDP, the Growth Index also offers an early warning for possible recessions.

Perhaps the most astonishing chart is the one below, which compares the contraction that began in 2008 with the one that began in January of this year. I've reproduced a chart on the Institute's website and added annotations for the elapsed time and the relationship of the contractions to major market milestones.

Among other things, this chart illustrates the more subtle and pernicious nature of the current decline in consumption. The 2010 decline is has equaled the length of the complete 2008 contraction cycle — the combined contraction and recovery. Yet in the current cycle we're still trending down.

The Consumer Metrics Institute's Growth Index hasn't been in operation very long, but thus far it has been an effective leading indicator of GDP. As such, the prospect of a double-dip recession, something that's happened only once since the Great Depression, remains a distinct possibility. That earlier double dip was a 6-month recession from January 1980 to July 1980, a 12-month recovery, and a 16-month of recession from July 1981 to November 1982. The one bit of good news for that earlier period is that the second dip coincided with the end of a secular bear market and the beginning of an 18-year cycle of accelerating growth.

Note: The charts have been updated based on the latest data from Standard & Poor's and the latest monthly close of VTI, the Vanguard Total Market ETF.

I've plotted the S&P regression data as an area chart type rather than a line to make the comparisons a bit easier to read. It also reinforces the difference between the two line charts — both being simple ratios — and the regression series, which measures the distance from an exponential regression on a log chart (see this regular feature for more explanation).

The chart below differs from the one above in that the two valuation ratios (P/E and Q) are adjusted to their geometric mean rather than their arithmetic mean (which is what most people think of as the "average"). The geometric mean weights the central tendency of a series of numbers, thus calling attention to outliers. In my view, the first chart does a satisfactory job of illustrating these three approaches to market valuation, but I've included the geometric variant as an interesting alternative view for P/E and Q.

The S&P 500 closed the day up 2.95%. The year-to-date performance is -3.12%, and the correction since the interim high on April 23 is -11.25%. The index is 59.7% above the March 9 2009 closing low but 31.0% below the peak in October 2007.

Here is a StockCharts.com candlestick chart showing the relationship of the S&P 500 to its 50- and 200-day simple moving averages.

For a better sense of how these declines figure into a larger historical context, here's a long-term view of secular bull and bear markets in the S&P Composite since 1871.

For a bit of international flavor, here's a chart series that includes an overlay of the S&P 500, the Dow Crash of 1929 and Great Depression, and the so-called L-shaped "recovery" of the Nikkei 225. I update these weekly.

These charts are not intended as a forecast but rather as a way to study the current market in relation to historic market cycles.

Note from dshort: The charts below have been updated with estimates based on the August close of VTI. On September 17th the Federal Reserve will issue the Flow of Funds release for Q2, at which time I'll update the charts below. That will give us another opportunity to evaluate the accuracy of using the Vanguard Total Market ETF for extrapolating the Q Ratio for more recent months.

The first chart shows Q Ratio from 1900 through the first quarter of 2010. I've also extrapolated the ratio since April based on the price of VTI, the Vanguard Total Market ETF, to give a more up-to-date estimate.

The data since 1945 is a simple calculation using data from the Federal Reserve Z.1 Statistical Release, section B.102., Balance Sheet and Reconciliation Tables for Nonfinancial Corporate Business. Specifically it is the ratio of Line 35 (Market Value) divided by Line 32 (Replacement Cost). It might seem logical that fair value would be a 1:1 ratio. But that has not historically been the case. The explanation, according to Smithers & Co. (more about them later) is that "the replacement cost of company assets is overstated. This is because the long-term real return on corporate equity, according to the published data, is only 4.8%, while the long-term real return to investors is around 6.0%. Over the long-term and in equilibrium, the two must be the same."

The average (arithmetic mean) Q ratio is about 0.70. In the chart below I've adjusted the Q Ratio to an arithmetic mean of 1 (i.e., divided the ratio data points by the average). This gives a more intuitive sense to the numbers. For example, the all-time Q Ratio high at the peak of the Tech Bubble was 1.82 — which suggests that the market price was 158% above the historic average of replacement cost. The all-time lows in 1921, 1932 and 1982 were around 0.43, which is 57% below replacement cost. That's quite a range.

Smithers & Co., an investment firm in London, incorporates the Q Ratio in their analysis. In fact, CEO Andrew Smithers and economist Stephen Wright of the University of London coauthored a book on the Q Ratio, Valuing Wall Street. They prefer the geometric mean for standardizing the ratio, which has the effect of weighting the numbers toward the mean. The chart below is adjusted to the geometric mean, which, based on the same data as the two charts above, is 0.65. This analysis makes the Tech Bubble an even more dramatic outlier at 179% above the (geometric) mean.

John Mihaljevic, who was Dr. Tobin's research assistant at Yale and collaborated with Tobin in revising the ratio formula, uses a more complex formula based on the Flow of Funds data for calculating Q. The formula is explained in detail at Mihaljevic's Manual of Ideas website. The chart below uses the Mihaljevic/Tobin formula for the Q calculation.

I would make two points about the more intricate formula. First it produces results that are remarkably similar to the simple calculation (first chart above. Also, the chart here differs somewhat from the version posted at the Manual of Ideas website (reproduced here), even though my chart uses the Manual of Ideas calculation formula. I've corresponded with John about the differences, and he explained them as an artifact of undocumented revisions to the government's Flow of Funds data. The Manual of Ideas Q Ratio is updated quarterly when the latest Z.1 numbers are released, and no changes are made to the ratio for previous quarters. My charts were built from scratch with the historic Z.1 data with any undocumented revisions included.

Note: My calculations with the latest Z.1 release confirm John's explanation of undocumented Fed tinkering with the older data. My comparison of the March release for Q4 and the June release for Q1 shows changes to the raw data as far back as 1996! The changes are relatively minor, but they have resulted in 14 quarterly Q modifications ranging from -0.01 to +0.02, with the upward adjustments clustered toward the recent quarters.

Unfortunately, the Q Ratio isn't a very timely metric. The Flow of Funds data is over two months old when it's released, and three months will pass before the next release. To address this problem, I've been collaborating with Jacob Wolinsky to make preliminary estimates for the Q Ratio for use in his monthly valuation update. We've been experimenting with extrapolations for the more recent months based on changes in the market value of the VTI, the Vanguard Total Market ETF, which essentially becomes a surrogate for line 32 in the data. The latest Z.1 release has validated our approach. The Extrapolations for January through May were 0.95, 0.98, 1.04, 1.06 and 0.98, respectively. The new data gives a March number of 1.04 — exactly our forecast. The high of 1.06 is thus an extrapolation that matches the April interim high. Extrapolated ratios for May, June, July and August are 0.98, 0.92, 0.98 and 0.94 respectively.

The mean-adjusted charts above indicate that the market remains significantly overvalued by historical standards — by about 33% in the arithmetic-adjusted version and 44% in the geometric-adjusted version. Of course periods of over- and under-valuation can last for many years at a time.

Please see the companion article Three Market Valuation Indicators that features overlays of the Q Ratio, the P/E10 and the regression to trend in US Stocks since 1900. There we can see the extent to which these three indicators corroborate one another.

About the only certainty in the stock market is that, over the long haul, overperformance turns into underperformance and vice versa. Is there a pattern to this movement? Let's apply some simple regression analysis to the question.

The chart shows the real (inflation-adjusted) monthly average of daily closes. We're using a semi-log scale to equalize vertical distances for the same percentage change regardless of the index price range. The regression trendline drawn through the data clarifies the secular pattern of variance from the trend — those multi-year periods when the market trades above and below trend. That regression slope, incidentally, represents an annualized growth rate of 1.70%.

The Bearish View
The peak in 2000 marked an unprecedented 160% overshooting of the trend — about double the overshoot in 1929. The index had been above trend for nearly 18 years. It dipped about 6% below trend briefly in March of 2009, but at the beginning of September 2010 it is 28% above trend. In sharp contrast, the major troughs of the past saw declines in excess of 50% below the trend. If the current S&P 500 were sitting squarely on the regression, it would be hovering around 845. If the index should decline over the next year or two to a level comparable to previous major bottoms, it would fall to the low 400s.

The Bullish Alternative
A critical factor for the reliability of a regression analysis of stock prices over many decades is the accuracy of the inflation adjustment. The Bureau of Labor Statistics (BLS) has been actively tracking inflation since 1919 and has estimated inflation rates back to 1913 using data on food prices. In 1982, however, the BLS began incorporating changes to the Consumer Price Index (CPI), which is used to calculate inflation. These changes have resulted in much lower "official" inflation rates than would have been the case if the method of calculation had remained consistent.

At his www.shadowstats.com website, Economist John Williams publishes an "Alternate CPI" employing the earlier BLS method. Here is a chart that illustrates the significant difference between these two calculation methods.

The change is astonishing. The adjustments to post-1982 data alter the slope of the regression and impacts the variance from the trend across the entire time frame, dramatically so in the last two decades. The slope drops from an annualized growth rate of 1.70% with official CPI to 1.32% with the alternate CPI. In this view, the S&P 500 has been below trend since the end of 2007. The 2009 bear market low saw the monthly average index price drop to more than 50% below the trend, which puts us in the territory of those secular market troughs. The current price is about 39% below trend.

My opinion is that the optimum method for calculating consumer prices is probably somewhere between the revised BLS method and the historic method preserved by Williams. Ordinarily for a long-term regression analysis, consistency would be preferable, which may lend some credibility to the alternate CPI chart. However, government policy, the Federal Funds Rate, interest rates in general and decades of major business decisions have been fundamentally driven by the official BLS inflation data, not the alternate CPI. For this reason I think the bullish alternative is misleading.

My comment on this point is a bit more opinionated than I've expressed in the past. But the more I study long-term economic and market trends, the less I believe this alternate-adjusted regression analysis.

Here's the latest update of my preferred market valuation method using the most recent Standard & Poor's "as reported" earnings and earnings estimates and the index monthly averages of daily closes for August 2010, which is 1087.28. The ratios in parentheses use the August monthly close of 1049.33. For the latest earnings, see the accompanying table from Standard & Poor's.

TTM P/E Ratio
The "price" part of the P/E calculation is available in real time on TV and the Internet. The "earnings" part, however, is more difficult to find. The authoritative source is the Standard & Poor's website, where the latest numbers are posted on the earnings page. Free registration is now required to access the data. Once you've downloaded the spreadsheet, see the data in column D.

The table here shows the TTM earnings based on "as reported" earnings and a combination of "as reported" earnings and Standard & Poor's estimates for "as reported" earnings for the next few quarters. The values for the months between are linear interpolations from the quarterly numbers.

The average P/E ratio since the 1870's has been about 15. But the disconnect between price and TTM earnings during much of 2009 was so extreme that the P/E ratio was in triple digits — as high as the 120s — in the Spring of 2009. In 1999, a few months before the top of the Tech Bubble, the conventional P/E ratio hit 34. It peaked around 47 two years after the market topped out.

As these examples illustrate, in times of critical importance, the conventional P/E ratio often lags the index to the point of being useless as a value indicator. "Why the lag?" you may wonder. "How can the P/E be at a record high after the price has fallen so far?" The explanation is simple. Earnings fell faster than price. In fact, the negative earnings of 2008 Q4 (-$23.25) is something that has never happened before in the history of the S&P 500.

Let's look at a chart to illustrate the irrelevance of the TTM P/E for a consistent indicator of market valuation.

The P/E10 Ratio
Legendary economist and value investor Benjamin Graham noticed the same bizarre P/E behavior during the Roaring Twenties and subsequent market crash. Graham collaborated with David Dodd to devise a more accurate way to calculate the market's value, which they discussed in their 1934 classic book, Security Analysis. They attributed the illogical P/E ratios to temporary and sometimes extreme fluctuations in the business cycle. Their solution was to divide the price by a multi-year average of earnings and suggested 5, 7 or 1-years. In recent years, Yale professor Robert Shiller, the author of Irrational Exuberance, has reintroduced the concept to a wider audience of investors and has selected 10 years as the earnings denominator. As the accompanying chart illustrates, this ratio closely tracks the real (inflation-adjusted) price of the S&P Composite. The historic average is 16.35. Shiller refers to this ratio as the Cyclically Adjusted Price Earnings Ratio, abbreviated as CAPE, or the more precise P/E10, which is my preferred abbreviation.

The Current P/E10
After dropping to 13.4 in March 2009, the P/E10 rebounded above 20. The chart below gives us a historical context for these numbers. The ratio in this chart is doubly smoothed (10-year average of earnings and monthly averages of daily closing prices). Thus the fluctuations during the month aren't especially relevant (e.g., the difference between the monthly average and monthly close P/E10).

Of course, the historic P/E10 has never flat-lined on the average. On the contrary, over the long haul it swings dramatically between the over- and under-valued ranges. If we look at the major peaks and troughs in the P/E10, we see that the high during the Tech Bubble was the all-time high of 44 in December 1999. The 1929 high of 32 comes in at a distant second. The secular bottoms in 1921, 1932, 1942 and 1982 saw P/E10 ratios in the single digits.

Where does the current valuation put us?
For a more precise view of how today's P/E10 relates to the past, our chart includes horizontal bands to divide the monthly valuations into quintiles — five groups, each with 20% of the total. Ratios in the top 20% suggest a highly overvalued market, the bottom 20% a highly undervalued market. What can we learn from this analysis? The Financial Crisis of 2008 triggered an accelerated decline toward value territory, with the ratio dropping to the upper 4th quintile in March 2009. The price rebound since the 2009 low pushed the ratio back into the 1st quintile, and it is now positioned just below the lower boundary around 20. By this historic measure, the market is expensive.

A more cautionary observation is that every time the P/E10 has fallen from the first to the fourth quintile, it has ultimately declined to the fifth quintile and bottomed in single digits. Based on the latest 10-year earnings average, to reach a P/E10 in the high single digits would require an S&P 500 price decline below 540. Of course, a happier alternative would be for corporate earnings to make a strong and prolonged surge. When might we see the P/E10 bottom? These secular declines have ranged in length from over 19 years to as few as three. The current decline is now in its tenth year.

Or was March 2009 the beginning of a secular bull market? Perhaps, but the history of market valuations doesn't encourage optimism.

Additional Perspectives on the P/E10
In response to the occasional request I receive for a real P/E10 based on the ShadowStats Alternate CPI for the inflation adjustment, see this chart, which suggests that the current market is fairly priced. On a personal note, I find the Alternate CPI version of the P/E10 interesting, but I think it is unreliable for estimating market valuation. Government policy, interest rates, and business decisions in general have been fundamentally driven by the official BLS inflation data, not the alternate CPI.

Yet another approach, one which avoids the question of the "correct" inflation adjustment, is to use nominal values for calculating the P/E10. The is the method of analysis favored by by Bob Bronson, a market historian whose research is occasionally featured at dshort.com. For Bronson's rationale, see this post from May 5th. Thus I'm now including a monthly update of the nominal P/E10.

Was the March 2009 low the end of a secular bear market and the beginning of a secular bull? Or is there more downside to come? Without crystal ball, we simply don't know.

One thing we can do is examine the past to broaden our sense of the range of possibilities. An obvious feature of this inflation-adjusted chart of the S&P Composite is the pattern of long-term alternations between up- and down-trends. Market historians call these "secular" bull and bear markets from the Latin word saeculum "long period of time" (in contrast to aeternus "eternal" — the type of bull market we fantasize about).

If we study the data underlying the chart, we can extract a number of interesting facts about these secular patterns:

The annualized rate of growth since 1871 is 1.91%. If that seems incredibly low, remember that the chart shows "real" price growth, excluding inflation and dividends. If we factor in the dividend yield, we get an annualized return of 6.58%. Yes, dividends make a difference. Unfortunately that has been less true during the past three decades than in earlier times. When we let Excel draw a regression through the data, the slope is an even lower annualized rate of 1.70% (see the regression section below for further explanation).

If we added in the value lost from inflation, the "nominal" annualized return comes to 8.79% — the number commonly reported in the popular press. But for an accurate view of the purchasing power of our returns, we'll stick to "real" numbers.

Based on the real S&P Composite monthly averages of daily closes, the S&P is 40% above the 2009 low, which is still 42% below the 2000 high. The 2009 low measures about 6% above the average decline for secular bear markets. Of course, this number is a bit skewed by the bottom in 1932, which saw a greater decline over a much shorter period (three years versus nine).

Let's review the same chart, this time with a regression trend line through the data.

This line essentially divides the monthly values so that the total distance of the data points above the line equals the total distance below. Remember that 1.91% annualized rate of growth since 1871? The slope of this line, an annualized rate of 1.70%, approximates that number. The 0.21% difference is largely a result of the rally over the past 16 months.

Regression to trend usually means overshooting to the other side. The latest monthly average of daily closes is 28% above trend after having fallen only 6% below trend in March of last year. Previous bottoms were considerably further below trend.

On this last day of August in anticipation of September (and in the spirit of market trivia), let's survey the behavior of the months in the S&P Composite since 1928. The Composite is a spliced index of the earlier S&P 90 with the S&P 500. Because of its greater breadth, I prefer it to the Dow for historic research of this sort.

Market lore is full of monthly associations: The January Effect, Sell in May and Go Away, Summer Rallies, the September Slump, Manic-Depressive October, December Rallies, etc. With August now on life support, a look at September's track record seems in order.

The first chart shows the average monthly gains/losses, excluding dividends, since 1928 for all twelve months. September is by far the worst performer. Incidentally, the monthly average of all months lumped together is 0.57%. So September underperforms the mean by 1.75%.

Has September consistently been a poor performer? The next three charts divvy up our 82-year period into three parts: 1928-1949, 1950-1981, and 1982-present. The rationale is that the first chart includes the Crash of 1929, Great Depression, WWII, and ends around the time of the secular market bottom in 1949. The second chart covers the cycle from the beginnings of the post-war rally through the Decade of Stagflation and market bottom in 1982. The third chart begins with the great Boomer market that followed and runs to the present.

Of course we could slice and dice the decades any number of ways, but an overview and three subsets (a four-chart total) about maxes out my energy and interest in this topic.

September has been a performance laggard in all three timeframes and the worst performer in two of the three. May (a chronically unimpressive month until the 1980s) takes the booby prize for the 1945-1981 time slice.

Lest the charts above give the false impression that September is a consistently poor performer, let's close with a distribution of performance over the past 82 years.

Let's hope September 2010 behaves more like it did in 1939 and not like in 1931.

The S&P 500 closed the month of August 4.74% below the July close. All three S&P 500 monthly moving averages we've been tracking are signaling a cash position. See the specifics here.

Here is a table with the current signal for the 10-month SMA for the five ETFs featured in The Ivy Portfolio. I've also included a table of 12-month SMAs for the same ETFs for this popular alternative strategy.

Over the past few years I've used Excel to track the performance of various moving-average timing strategies. But now I use the backtesting tools available on the ETFReplay.com website. Anyone who is interested in market timing with ETFs should have a look at this website. Here are the two tools I most frequently use:

Buying and selling based on a moving average of monthly closes can be an effective strategy for managing the risk of severe loss from major bear markets. In essence, when the monthly close of the index is above the moving average value, you hold the index. When the index closes below, you move to cash. The disadvantage is that it never gets you out at the precise top or back in at the very bottom. Also, it can produce the occasional whipsaw (short-term buy or sell signal), such as we've experienced this summer.

Nevertheless, a chart of the S&P 500 monthly closes since 1995 shows that a 10- or 12-month simple moving average (SMA) strategy would have insured participation in most of the upside price movement while dramatically reducing losses.

The 10-month exponential moving average (EMA) is a slight variant on the simple moving average. This version mathematically increases the weighting of newer data in the 10-month sequence. Since 1995 it has produced fewer whipsaws than the equivalent simple moving average, although it was a month slower to signal a sell after these two market tops.

A look back at the 10- and 12-month moving averages in the Dow during the Crash of 1929 and Great Depression shows the effectiveness of these strategies during those dangerous times.

For anyone who would like to see the 10- and 12-month simple moving averages and the equity-versus-cash positions since 1950, here's an Excel file (xls format) of the data. My source for the monthly closes (Column B) is Yahoo! Finance. Columns D and F shows the positions signaled by the month-end close for the two SMA strategies.

Timing works because of a basic human trait. People imitate successful behavior. When they hear of others making money in the market, they buy in. Eventually the trend reverses. It may be merely the normal expansions and contractions of the business cycle. Sometimes the cause is more dramatic — an asset bubble, a major war, a pandemic, or an unexpected financial shock. When the trend reverses, successful investors sell early. The imitation of success gradually turns the previous buying momentum into selling momentum.

Our illustrations from the S&P 500 are just that — illustrations. I use the S&P because of the extensive historical data that's readily available. However, followers of a moving average strategy should make buy/sell decisions on the signals for the each specific investment, not a broad index. Even if you're investing in a fund that tracks the S&P 500 (e.g., Vanguard's VFINX or the SPY ETF) the moving average signals for the funds will occasionally differ from the underlying index because of dividend reinvestment. The S&P 500 numbers in our illustrations exclude dividends.

The strategy is most effective in a tax-advantaged account with a low-cost brokerage service. You want the gains for yourself, not your broker or your Uncle Sam.

In the past we've recommended Mebane Faber's thoughtful article A Quantitative Approach to Tactical Asset Allocation. The article has now been updated and expanded as Part Three: Active Management his book The Ivy Portfolio, coauthored with Eric Richardson. This is a "must read" for anyone contemplating the use of a timing signal for investment decisions.

The book analyzes the application of moving averages the S&P 500 and four additional asset classes: the Morgan Stanley Capital International EAFE Index (MSCI EAFE), Goldman Sachs Commodity Index (GSCI), National Association of Real Estate Investment Trusts Index (NAREIT), and United States government 10-year Treasury bonds.

As a regular feature of this website, I try to update the signals at the end of each month. However, my retirement flexibility and life's unpredictability preclude a firm commitment.

The Latest Conference Board Consumer Confidence Index® was released this morning (August 31). Here is the introductory paragraph of the press release:

The Conference Board Consumer Confidence Index® which had declined in July, improved moderately in August. The Index now stands at 53.5 (1985=100), up from 51.0 in July. The Present Situation Index decreased to 24.9 from 26.4. The Expectations Index increased to 72.5 from 67.5 last month.

The chart below is intended to help evaluate the historical performance of this index as a leading indicator of the economy, particularly recessions. Toward this end I have included recessions and GDP. Note: I'm showing mid 2009 as the estimated end of the latest recession, following the lead of the St. Louis Federal Reserve.

Note that I characterized the latest index number as "up slightly" versus the "improved moderately" in the Conference Board press release. Which is the more accurate spin? Let the chart help you decide.

For an interesting comparison, see this post from last week on the University of Michigan's Consumer Sentiment Index. Here is the chart from that post.

Yesterday I posted comments by Rick Davis of the Consumer Metrics Institute about the latest BEA release on Personal Income and Outlays. One of Rick's observations triggered an interesting email from Paul Hanly, a 20-year veteran in banking and finance in Australia. Paul had experience in major corporate workouts after the 1992 recession and commercial real estate bust in Australia.

First Rick Davis's comment on U.S. personal savings:

The U.S. personal savings rate (as a % of Disposable Personal Income in the NIPA tables) was 5.9% in July, down from 6.2% in June but still above year-to-August 30, 2010 averages and likely to cause personal savings for 2010 to be at the highest rate since 1992. This is in spite of Vanguard's Prime Money Market Fund yielding 0.03% YTD, two orders of magnitude less than the rates available during the summer of 1992.

Now here is Paul's speculation on the underlying motives for personal savings:

The relevant interest rate to most borrowers isn't what a money market fund is offering. Consider the people in these three categories:

Most people in the US have personal debt including an average of about USD 5,000 credit card debt. In Australia this debt would be at about 18% and would not be tax deductible. Savings includes debt repayment.

The effective pretax interest rate for credit card payment (18% not deductible) is about 25% pretax. That is the best return on investment virtually anyone can get — and with absolute security! Then there are the personal loans, car loans, store cards, mortgage loans, including home equity loans, business overdrafts, etc. These interest rates are the incentives for people to save.
Small business owners illustrate another situation. They are solvent but under pressure from banks to reduce gearing. They don't have any option but to save (by repaying debt) with most free cash flow from their businesses.

If they don't repay, the bank puts them in default (maybe they are already in default paying a default rate, or their loan has expired, not been rolled over and been transferred to being an overdraft. Their default may be because their home was used as security and the drop in home market value for borrowing purposes has put them in breach of borrowing covenants and forced them into default and paying say 2% higher than say 8 or 10% whatever their small business loan rate was.
Another important group are those with college loans. I don't know the tax deductibility or interest rates on these, but they would be motivating anyone with college loan, or a housing loan taken to pay college fees.

These are the key situations that are driving saving by debt repayment for, I would say, 80% or more of people.

Thanks, Paul, for your thoughtful response!

Preface from dshort: Today's Bureau of Economic Analysis release on Personal Income and Outlays reported that consumer spending increased by .4 percent in July, which was more than analysts expected. I read the release shortly after posting the latest update from the Consumer Metrics Institute.

The BEA release is, of course, a rear-view look at the data with relatively little fine detail. But the claim that consumer spending increased in July runs counter to the virtually real-time insight into consumer behavior provided by the Consumer Metrics Institute for this period.

So I emailed Rick Davis, the President of the Institute, for his perspective on how the BEA consumer data relates to the Institute's data. Here is his response.

Rick Davis: I do look at the BEA's Personal Income and Outlays reports, but it is very hard to make a coherent story out of the data — which also suffers from all the usual BEA problems: seasonal adjustments and revisions, revisions and more revisions. It's really hard to "get your arms around" the data, and a half dozen conflicting inferences could be made from each new report.

When I really study the BEA tables my eyes glaze over, and I probably end up doing something that everyone does: selectively pulling data that confirms existing biases about what the data "should" be saying. For example, in the most recent report the seasonally adjusted "Real disposable personal income" was (just barely) contracting by .1% in July, after growing at a .6% rate as recently as April. In general, to my eyes the July data looked much weaker than 2nd quarter data. That is exactly what I expected to see — hence my suspicion that these kinds of reports can tell you anything you want them to say.

One thing that is less ambiguous in the data is the longer term trend in personal savings — again confirming the one (and possibly only) thing that John Maynard Keynes got right: the "Paradox of Thrift". The U.S. personal savings rate (as a % of Disposable Personal Income in the NIPA tables) was 5.9% in July, down from 6.2% in June but still above year-to-August 30, 2010 averages and likely to cause personal savings for 2010 to be at the highest rate since 1992. This is in spite of Vanguard's Prime Money Market Fund yielding 0.03% YTD, two orders of magnitude less than the rates available during the summer of 1992.

Looking back, the same savings rate was 1.4% in 2005, and 2.1% as recently as 2007. If the rate for 2010 turns out to be 5.9%, where did the extra 3.8% or more in savings come from? And can consumers continue to be frugal at that same rate? And why would they change behavior between now and November 2nd? All of the above answers probably do not bode well for third quarter GDP.

For the most up-to-date insight into consumer behavior, visit Rick Davis's Consumer Metrics Institute.

Here's a weekly view of the S&P 500 from veteran technical analyst and frequent contributor Chris Kimble.

On a weekly basis the S&P 500 is hanging on to a thread of support.

Sentiment often plays a funny role in investing, in that the majority is often wrong. Currently bullish sentiment has dropped to its lowest level since the March of 2009 lows.

Will this support line with so few of bulls on board hold right now? If not, the drop below this support is a long way down.

Regular visitors to dshort.com know I follow Howard Silverblatt's earnings spreadsheet on the Standard & Poor's website. Free registration is required to access this data. I've received several requests for more specific details on where to find the spreadsheet. It is fairly well hidden. Here are two links to help frustrated seekers: step one and step two.

I follow the "As-Reported" earnings and top-down estimates for future earnings (see column D in the spreadsheet). The chart below shows the higher estimates of future earnings from the most recent spreadsheet, dated August 24th, and three earlier spreadsheets (February 17th, April 28th, and July 15th).

The latest earnings estimate for 2Q 2010 is 67.20. Friday's close gives us a P/E ratio of 15.84, which is close to the average trailing 12-month P/E of 15.48. Beyond the 2Q, the chart illustrates increasing optimism about next year's earnings. The August 24th estimate of $80.20 for 4Q 2011 at today's P/E would put the S&P 500 at 1,270 at the end of 2011. That's a gain of 19.3% from the latest close.

But will as-reported earnings really live up to these estimates? Last month Howard Silverblatt pinpointed the problem for earnings in a Bloomberg article No Sales Means No Jobs Means No Recovery. His concluding remarks are worth repeating here:

I look to sales as a future indicator. On this basis, earnings are running ahead of Q1 2010, but sales are flat, and that's the problem. It's great that companies have improving earnings, but those improvements are due to high margins, which were the product of cost cuts — specifically job reductions, the very thing that we need to improve now. Until companies and consumers start to spend more, the job front will not get better, but they won't spend more until they believe things are getting better. The stimulus programs were supposed to jump start the economy and break the downward cycle by convincing both groups that better times were here. But so far we're not seeing the sales or the jobs; but earnings are good, at least for now.

Companies in the S&P 500 sell across the world. But consumption in the US, which remains critical for sustained earnings growth, has been undergoing a sustained contraction &mdash, a fact that every new update of the Consumer Metrics Institute's Growth Index dramatically illustrates.

Here's a weekly update the major world indexes I've been tracking during the past few months. The table at right shows the performance over the past week.

The FTSE 100 was the top performer for the week, with a fractional gain. The other five indexes lost ground, with the Hang Seng and Nikkei 225 as the biggest losers.

The chart below illustrates the comparative performance of World Markets since March 9, 2009. The start date is arbitrary: The S&P 500 hit a low on March 9th, the Nikkei 225 on March 10th, the DAX on March 6th, the FTSE on March 3rd, the Shanghai Composite on November 4, 2008, and the Hang Seng 4.4 months earlier on October 27, 2008. However, by aligning on the same day, we get a better sense of the present-day synchronous behavior of the markets than if we align the lows.

Using the traditional metrics for cyclical bear markets and corrections, the Nikkei and Shanghai are experiencing bear markets. The Hang Seng, FTSE and S&P 500 are in correction territory.

Here's the same chart starting from the turn of 21st century. Since the bubble Shanghai Composite makes the spread between the other five indexes more difficult to see, I've included a second version with the Shanghai exluded.

It's time again for the weekend update of our "Real" Mega-Bears, an inflation-adjusted overlay of three secular bear markets. It aligns the current S&P 500 from the top of the Tech Bubble in March 2000, the Dow in of 1929, and the Nikkei 225 from its 1989 bubble high.

This chart is consistent with my preference for real (inflation-adjusted) analysis of long-term market behavior. The nominal all-time high in the index occurred in October 2007, but when we adjust for inflation, the "real" all-time high for the S&P 500 occurred in March 2000.

Here is a nominal version to help clarify the impact of inflation and deflation, which varied significantly across these three markets.

Note: These charts are not intended as a forecast but rather as a way to study the today's market in relation to historic market cycles.

Here's a follow-up weekend chart of the S&P 500 from Serge. This one is a monthly view over the past decade that focuses on the Rate of Change indicator. Serge explains:

Like in 2004 and 2008, ROC9 broke support before the index (see 1, 2 & 3). Watch also ROC24 to see if it will break its support at the same time as the index, like in 2008 (4). Take note too that the sideways trading range varied in length from 4 months currently to 9 months in 2008 and 11 months in 2004.

It's Friday, and right on schedule Chris "Just the Facts" Kimble does his Dragnet impersonation, this time with a focus on iShares Barclays 20+ Year Treasury Bonds (TLT).

Last week's technical analysis quiz presented a case that TLT was up against a crossroads of resistance.

As the chart above shows, TLT did break above resistance for a few days. But after today's large decline, it has broken all support!

Here's the latest weekend update from Serge Perreault, a Chartered Accountant and market technician located near Montreal, Canada. Serge has been following the S&P 500 index in a series of weekly charts. Serge explains:

This week, the S&P 500 "saved" its support (for the 3rd time since May 3), on 3.8% below-average volume and on weak but, near-support momentum. The index remains inside a downtrend from 2007 (log scale). It may be worth repeating that the longer the sideways trading range, the stronger the breakout (of the resistance) or the breakdown (of the support) will be.

Over the time frame shown below there has been a weak correlation between the two assets classes, with yields tending to lead changes in direction.

Yields have fallen dramatically since the 2010 high of 3.99 set on April 5th, three weeks before the S&P 500 2010 peak on April 23rd. Does the flight to treasuries over the past few months bode ill for the equities market this fall? Stay tuned.

The next chart shows the weekly performance of several Treasuries and the Fed Funds Rate since 2007. The source for the yields is the Daily Treasury Yield Curve Rates from the US Department of the Treasury.

For a long-term view of Treasury yields, also focusing on the 10-year, see my Treasury Yields in Perspective, which includes a chart series I update monthly or more frequently if warranted.

Note from dshort: The chart below includes today's downward revision of Q2 GDP from 2.4% to 1.6%.

Optimism has been the primary characteristic of American consumers during the past half century. To be sure, consumers repeatedly suspended that optimism around recessions, but the suspension was always considered temporary. Now economic uncertainty reigns. It is far too early to declare that consumer pessimism has become the new default outlook of consumers. Nonetheless, the economic uncertainty that now exists has caused consumers to reduce their spending and increase their precautionary saving. The lesson of the financial crisis for consumers was that their best defense against economic adversity was to reduce their own debt. (See the full report in PDF format.)

Because the sentiment index has trended upward since its inception in 1978, I've added a liner regression to help understand the pattern of reversion to the trend. I've also highlighted recessions to help evaluate the value of the Michigan Consumer Sentiment Index as a leading indicator of the economy.

Here's a quick look at Gross Domestic Product (GDP) since 1948 together with the real (inflation-adjusted) S&P Composite. Today's downward revision of 2nd Quarter GDP from 2.4% to 1.6% has been included.

I've highlighted the one double-dip recession over this timeframe. I'll update the chart again next month if September's final revision of Q2 GDP varies from today's number.

Today the Weekly Leading Index (WLI) of the Economic Cycle Research Institute (ECRI) registered negative growth for the twelfth consecutive week, coming in at -9.9, a fractional improvement from last week's -10.1. This number is based on data through August 20.

The rate of decline from the peak in October 2009 is unprecedented in the Institute's published data back to 1967. Recently, however, the Institute has disclosed that two earlier decades of data not available to the general public contained comparable declines in WLI growth (in 1951 and 1966) when no recession followed (HT Barry Ritholtz).

The ECRI WLI growth metric has had a respectable (but by no means perfect) record for forecasting recessions. The next chart shows the correlation between the WLI, GDP and recessions.

A significant decline in the WLI has been a leading indicator for six of the seven recessions since the 1960s. It lagged one recession (1981-1982) by nine weeks. The WLI did turned negative 17 times when no recession followed, but 14 of those declines were only slightly negative (-0.1 to -2.4) and most of them reversed after relatively brief periods.

Three of the false negatives were deeper declines. The Crash of 1987 took the Index negative for 68 weeks with a trough of -6.8. The Financial Crisis of 1998, which included the collapse of Long Term Capital Management, took the Index negative for 23 weeks with a trough of -4.5.

The third significant false negative came near the bottom of the bear market of 2000-2002, about nine months after the brief recession of 2001. At the time, the WLI seemed to be signaling a double-dip recession, but the economy and market accelerated in tandem in the spring of 2003, and a recession was avoided.

The question, of course, is whether the latest WLI decline is a leading indicator of a recession or a false negative. The published index has never dropped to the current level without the onset of a recession. The deepest decline without a near-term recession was in the Crash of 1987, when the index slipped to -6.8.

Can the Fed take steps to reduce the risk of a near-term recession? The next chart includes an overlay of the Federal Funds Rate.

Lowering the rate has been a primary tool for stimulating a weak economy. As the last chart shows, that tool is not available in our current situation.

Here is the latest look at the "Sweet Sixteen" Dow recoveries adjusted for inflation/deflation I've been charting over the past several months. With the Thursday close below 10,000, it seems like a good time to compare the current Dow recovery since the March 2009 with the fifteen other major recoveries since the origin of this legendary index in 1896.

At this point the Dow is 372 market days beyond the 2009 low. The index has slumped to 10th place in our Sweet Sixteen competition.

In the first chart, I've removed the 1932 data series. The rally following the Crash of 1929 was indeed an outlier — one that consisted of a series of cyclical bull and bear rallies. By removing it, the vertical axis shrinks by half, improving our ability to see the differentiation among the other recoveries. To illustrate the point, here's a link to the nominal 16-rally version.

Why is inflation adjustment useful for this overlay? Throughout history the cost of living has undergone some dramatic changes, as this chart illustrates. High inflation, such as during the 1974 recovery, gives an exaggerated sense of price growth. Deflation, which accompanied several of the earlier market cycles, makes recoveries appear weaker. By adjusting for the inflationary/deflationary cycles, we get a clearer sense of the real value of the index price across time.

Now let's extend the time frame. Here is a set of charts with increasing numbers of market days: 500, 1000, 2000, 3000, 4000, and 5000. Depending on the historical period, the number of market days in a year varies slightly. But it rounds out to about 250 market days per year. So the time frames in this series are approximately 2, 4, 8, 12, 16, and 20 years. The series includes the 500-day chart with the 1932 recovery (Great Depression) omitted, but I added it back to the longer charts. At 1000 market days, the 1932 recovery continues to lead the pack. But at 2000 day (about eight years), the recovery after the 1921 low has risen dramatically. Of course, with the benefit of hindsight, we know that this remarkable advance was the last stage of the Roaring Twenties stock bubble, as the 3000-day (12-year) overlay makes clear. At 4000 days (about 16 years), the recovery from the low in 1982 is approaching the final surge of the Tech Bubble. The 5000-day chart shows how the Tech Bubble played out for the Dow, topping out in January 2000 after a brief scare in 1998 triggered by the Long-Term Capital Management Crisis (that dip after the 4000-day mark). The chart below shows the 5000-day (approximately 20-year) overlay:

Here is a table summarizing the comparative performance of these 16 Dow recoveries at seven points in time.

The overlay charts give visual evidence of the wide range of recovery patterns. The table helps quantify the magnitude of the difference. Two of the earlier recoveries, 1903 and 1914, and two of the later recoveries, 1962 and 1970, subsequently failed. Likewise the 1938 and 1974 rallies failed before being rescued by later recoveries. This last observation touches on an important aspect of the overlay charts. As the timeframe increases, the same recovery may appear in multiple data series.

How will our current recovery fare during the coming months and years? I'm reluctant to make any inferences based on the overlay charts other than the obvious. History shows us that some recoveries are the beginnings of secular bull markets. Others turn out to be cyclical bear market rallies.

The recovery since March 2009 is the second in the first decade of the 21st century, and it started from a lower low. As we can see in the inflation-adjusted chart below, history has witnessed several other examples of multiple recoveries in relatively close succession with lower starting points. Will the current recovery be another such example? Only time will tell.

Emails arrived from all over the world in response to our latest "What do you see in this chart?" quiz. The goal of the series is to see patterns in charts, without knowing the asset, price or timeframe. Here again is the quiz chart, followed by an annotated version.

Today's answer is an asset that's been in the news of late — the Homebuilder ETF (XHB). As the chart shows, multiple support lines come into play at (1). Buy on support with a tight stop.

If support breaks and you want to score on defense, consider a position in SRS (the inverse REIT).

A week has passed, and it's time for another technical analysis quiz. Here is the latest Chris Kimble challenge.

Chris comments: Here is the latest "what do you see and what would you do" chart.

The answer to the weekly quiz will be be revealed tomorrow. If you would like to contribute thoughts or answers before we reveal the answer feel free to shoot me an email.

Have fun and good luck investing.

I just spotted this excellent post on Chris Kimble's blog, which I've reprinted below.

It initially caught my eye because Groundhog Day is my all-time favorite movie (much deeper than most people realize). But more to the point, this trio of chart annotations captures a potential market turning point of major proportions. I've reprinted Chris's analysis below.

In the movie "Ground Hog" day, actor Bill Murray found himself repeating the same day over and over again. Speaking of repeating over and over again, the 500, Nasdaq 100 and Russell 2000 find themselves back at the bottom of their trading ranges — AGAIN!

For those that are scoring on defense, bring stops down to protect gains, right now! Why? Potential short-term "inverse H&S" pattern is at hand. I do not feel this will override the larger pattern, but one must respect the bottom of the trading range and short-term oversold conditions.

FYI, I am of the opinion this pattern WILL END! For those scoring on defense, the Russell looks to be the most vulnerable in the above chart. Of course if the Russell breaks support, the other two will as well!

Note from dshort: The Nikkei 225 closed today's session down 1.66%. I've updated the chart accordingly and adjusted the callouts to show the most recent interim high and low.

Here is an that gives a close-up view of the cyclical rallies and their duration during Japan's secular bear market, now in its 20th year.

I've been posting weekly updates of a mega-bear market charts (here and here) that include Japan's Nikkei 225. In addition, every few months I update an inflation-adjusted overlay of the Nikkei 225 and S&P 500 bubbles.

The table below documents the advances and declines and the elapsed time for each cycle.

For the sake of comparison, the S&P 500 interim high thus far is 79.9% (set April 23) above the low in March 2009. The correction off the low currently stands at -13.6%