Author Archives: Ted Kavadas

Building Financial Danger – February 8, 2017 Update

My overall analysis indicates a continuing elevated and growing level of financial danger which contains many worldwide and U.S.-specific “stresses” of a very complex nature. I have written numerous posts in this site concerning both ongoing and recent “negative developments.”  These developments, as well as other exceedingly problematic conditions, have presented a highly perilous economic environment that endangers the overall financial system.

Also of ongoing immense importance is the existence of various immensely large asset bubbles, a subject of which I have extensively written.  While all of these asset bubbles are wildly pernicious and will have profound adverse future implications, hazards presented by the bond market bubble are especially notable.

Predicting the specific timing and extent of a stock market crash is always difficult, and the immense complexity of today’s economic situation makes such a prediction even more challenging. With that being said, my analyses continue to indicate that a near-term exceedingly large (from an ultra-long term perspective) stock market crash – that would also involve (as seen in 2008) various other markets as well – will occur.

(note: the “next crash” and its aftermath has great significance and implications, as discussed in the post of January 6, 2012 titled “The Next Crash And Its Significance“ and various subsequent posts in the “Economic Depression” category)

As reference, below is a daily chart since 2008 of the S&P500 (through February 7, 2017 with a last price of 2293.08), depicted on a LOG scale, indicating both the 50dma and 200dma as well as price labels:

(click on chart to enlarge image)(chart courtesy of StockCharts.com; chart creation and annotation by the author)

S&P500 since 2008

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The Special Note summarizes my overall thoughts about our economic situation

SPX at 2293.29 as this post is written

February 7, 2017 Gallup Poll Results On Economic Confidence – Notable Excerpts

On February 7, 2017 Gallup released the poll results titled “U.S. Economic Confidence Index Hit New High in January.”

Notable excerpts include:

Americans’ confidence in the U.S. economy remained strong in January. Gallup’s U.S. Economic Confidence Index averaged +11, the highest monthly average in Gallup’s nine-year trend. However, the index has been slightly lower so far in February.

also:

Gallup’s U.S. Economic Confidence Index is the average of two components: how Americans rate current economic conditions and whether they feel the economy is improving or getting worse. The index has a theoretical maximum of +100 if all Americans were to say the economy is doing well and improving, and a theoretical minimum of -100 if all Americans were to say the economy is doing poorly and getting worse.

In January, 31% of Americans rated the economy as “excellent” or “good,” while 21% said it was “poor,” resulting in a current conditions score of +10 — marking the highest monthly reading for this component since 2008.

The economic outlook component also reached a new high score of +11 in January. This score was the result of 52% of Americans saying economic conditions in the country were “getting better,” while 41% said they were “getting worse.”

Here is an accompanying chart of the two components of the Gallup Economic Confidence Index, discussed above:

Gallup U.S. Economic Confidence Index Components - Monthly Averages

Here is an accompanying chart of the Gallup Economic Confidence Index:

Gallup U.S. Economic Confidence Index - Monthly Averages

 

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The Special Note summarizes my overall thoughts about our economic situation

SPX at 2292.38 as this post is written

Recession Probability Models – February 2017

There are a variety of economic models that are supposed to predict the probabilities of recession.

While I don’t agree with the methodologies employed or probabilities of impending economic weakness as depicted by the following two models, I think the results of these models should be monitored.

Please note that each of these models is updated regularly, and the results of these – as well as other recession models – can fluctuate significantly.

The first is the “Yield Curve as a Leading Indicator” from the New York Federal Reserve.  I wrote a post concerning this measure on March 1, 2010, titled “The Yield Curve as a Leading Indicator.”

Currently (last updated February 2, 2017 using data through January) this “Yield Curve” model shows a 4.0601% probability of a recession in the United States twelve months ahead.  For comparison purposes, it showed a 3.7396% probability through December, and a chart going back to 1960 is seen at the “Probability Of U.S. Recession Predicted by Treasury Spread.” (pdf)

The second model is from Marcelle Chauvet and Jeremy Piger.  This model is described on the St. Louis Federal Reserve site (FRED) as follows:

Smoothed recession probabilities for the United States are obtained from a dynamic-factor markov-switching model applied to four monthly coincident variables: non-farm payroll employment, the index of industrial production, real personal income excluding transfer payments, and real manufacturing and trade sales. This model was originally developed in Chauvet, M., “An Economic Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching,” International Economic Review, 1998, 39, 969-996. (http://faculty.ucr.edu/~chauvet/ier.pdf)

Additional details and explanations can be seen on the “U.S. Recession Probabilities” page.

This model, last updated on February 1, 2017, currently shows a 2.84% probability using data through November.

Here is the FRED chart (last updated February 1, 2017):

U.S. Recession Probability model

Data Source:  Piger, Jeremy Max and Chauvet, Marcelle, Smoothed U.S. Recession Probabilities [RECPROUSM156N], retrieved from FRED, Federal Reserve Bank of St. Louis, accessed February 6, 2017:

http://research.stlouisfed.org/fred2/series/RECPROUSM156N

The two models featured above can be compared against measures seen in recent blog posts.  For instance, as seen in the January 12 post titled “The January 2017 Wall Street Journal Economic Forecast Survey“ economists surveyed averaged a 16.49% probability of a U.S. recession within the next 12 months.

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The Special Note summarizes my overall thoughts about our economic situation

SPX at 2292.56 as this post is written

Monthly Changes In Total Nonfarm Payrolls – February 6, 2017 Update

For reference purposes, below are five charts that display growth in payroll employment, as depicted by the Total Nonfarm Payrolls measures (FRED data series PAYEMS).

PAYEMS, which is seasonally adjusted, is defined in Financial Reserve Economic Data [FRED] as:

All Employees: Total Nonfarm, commonly known as Total Nonfarm Payroll, is a measure of the number of U.S. workers in the economy that excludes proprietors, private household employees, unpaid volunteers, farm employees, and the unincorporated self-employed. This measure accounts for approximately 80 percent of the workers who contribute to Gross Domestic Product (GDP).

This measure provides useful insights into the current economic situation because it can represent the number of jobs added or lost in an economy. Increases in employment might indicate that businesses are hiring which might also suggest that businesses are growing. Additionally, those who are newly employed have increased their personal incomes, which means (all else constant) their disposable incomes have also increased, thus fostering further economic expansion.

Generally, the U.S. labor force and levels of employment and unemployment are subject to fluctuations due to seasonal changes in weather, major holidays, and the opening and closing of schools. The Bureau of Labor Statistics (BLS) adjusts the data to offset the seasonal effects to show non-seasonal changes: for example, women’s participation in the labor force; or a general decline in the number of employees, a possible indication of a downturn in the economy. To closely examine seasonal and non-seasonal changes, the BLS releases two monthly statistical measures: the seasonally adjusted All Employees: Total Nonfarm (PAYEMS) and All Employees: Total Nonfarm (PAYNSA), which is not seasonally adjusted.

The series comes from the ‘Current Employment Statistics (Establishment Survey).’

The source code is: CES0000000001

The first chart shows the monthly change in total nonfarm payrolls from the year 2000 through the current report of January 2017:

(click on charts to enlarge images)

PAYEMS monthly change

Data Source: FRED, Federal Reserve Economic Data, Federal Reserve Bank of St. Louis: All Employees: Total nonfarm [PAYEMS] ; U.S. Department of Labor: Bureau of Labor Statistics; accessed February 6, 2017;

https://research.stlouisfed.org/fred2/series/PAYEMS

The second chart shows a long-term chart of the same month-over-month change in total nonfarm payrolls (reports of January 1940 through the present report of January 2017):

PAYEMS monthly change

The third chart shows the aggregate number of total nonfarm payrolls, from January 1939 – January 2017 (January 2017 value of 145.554 million):

Total Nonfarm Payrolls

The fourth chart shows this same aggregate number of total nonfarm payrolls measure as seen above but presented on a LOG scale:

Total Nonfarm Payroll LOG scale

Lastly, the fifth chart shows the total nonfarm payrolls number on a “percent change from year ago” basis from January 1940 – January 2017:

PAYEMS percent change from year ago

_________

I post various indicators and indices because I believe they should be carefully monitored.  However, as those familiar with this blog are aware, I do not necessarily agree with what they depict or imply.

_____

The Special Note summarizes my overall thoughts about our economic situation

SPX at 2295.91 as this post is written

Average Hourly Earnings Trends

I have written many blog posts concerning the worrisome trends in income and earnings.

Along these lines, one of the measures showing disconcerting trends is that of hourly earnings.

While the concept of hourly earnings can be defined and measured in a variety of ways, below are a few charts that I believe broadly illustrate problematic trends.

The first chart depicts Average Hourly Earnings Of All Employees: Total Private (FRED series CES0500000003)(current value = $26.00):

(click on chart to enlarge image)(chart last updated 2-3-17)

CES0500000003

Data Source: FRED, Federal Reserve Economic Data, Federal Reserve Bank of St. Louis: Average Hourly Earnings of All Employees:  Total Private [CES0500000003] ; U.S. Department of Labor: Bureau of Labor Statistics; accessed February 3, 2017:

http://research.stlouisfed.org/fred2/series/CES0500000003

This next chart depicts this same measure on a “Percentage Change From A Year Ago” basis.   While not totally surprising, I find the decline from 2009 and subsequent trend to be disconcerting:

(click on chart to enlarge image)(chart last updated 2-3-17)

CES0500000003

There are slightly different measures available from a longer-term perspective. Pictured below is another measure, the Average Hourly Earnings of Production and Nonsupervisory Employees – Total Private (FRED series AHETPI)(current value = $21.84):

(click on chart to enlarge image)(chart last updated 2-3-17)

AHETPI

Data Source: FRED, Federal Reserve Economic Data, Federal Reserve Bank of St. Louis: Average Hourly Earnings of Production and Nonsupervisory Employees:  Total Private [AHETPI] ; U.S. Department of Labor: Bureau of Labor Statistics;  accessed February 3, 2017:

http://research.stlouisfed.org/fred2/series/AHETPI

Pictured below is this AHETPI measure on a “Percentage Change From A Year Ago” basis.   While not totally surprising, I find the decline from 2009 and subsequent trend to be disconcerting:

(click on chart to enlarge image)(chart last updated 2-3-17)

AHETPI percent change from year ago

I will continue to actively monitor these trends, especially given the post-2009 dynamics.

_________

I post various economic indicators and indices because I believe they should be carefully monitored.  However, as those familiar with this blog are aware, I do not necessarily agree with what they depict or imply.

_____

The Special Note summarizes my overall thoughts about our economic situation

SPX at 2295.99 this post is written

U-3 And U-6 Unemployment Rate Long-Term Reference Charts As Of February 3, 2017

Shortly after each monthly employment report I have been posting a continual series titled “3 Critical Unemployment Charts.”

Of course, there are many other employment charts that can be displayed as well.

For reference purposes, below are the U-3 and U-6 Unemployment Rate charts from a long-term historical perspective.  Both charts are from the St. Louis Fed site.  The U-3 measure is what is commonly referred to as the official unemployment rate; whereas the U-6 rate is officially (per Bureau of Labor Statistics) defined as:

Total unemployed, plus all persons marginally attached to the labor force, plus total employed part time for economic reasons, as a percent of the civilian labor force plus all persons marginally attached to the labor force

Of note, many economic observers use the U-6 rate as a (closer) proxy of the actual unemployment rate rather than that depicted by the U-3 measure.

Here is the U-3 chart, currently showing a 4.8% unemployment rate:

(click on charts to enlarge images)(charts updated as of 2-3-17)

U.S. unemployment rate

Data Source: FRED, Federal Reserve Economic Data, Federal Reserve Bank of St. Louis: Civilian Unemployment Rate [UNRATE] ; U.S. Department of Labor: Bureau of Labor Statistics; accessed February 3, 2017;

http://research.stlouisfed.org/fred2/series/UNRATE

Here is the U-6 chart, currently showing a 9.4% unemployment rate:

U-6 RATE

Data Source: FRED, Federal Reserve Economic Data, Federal Reserve Bank of St. Louis: Total unemployed, plus all marginally attached workers plus total employed part time for economic reasons  [U6RATE] ; U.S. Department of Labor: Bureau of Labor Statistics; accessed February 3, 2017;

http://research.stlouisfed.org/fred2/series/U6RATE

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The Special Note summarizes my overall thoughts about our economic situation

SPX at 2293.89 as this post is written

3 Critical Unemployment Charts – February 2017

As I have commented previously, as in the October 6, 2009 post (“A Note About Unemployment Statistics”), in my opinion the official methodologies used to measure the various job loss and unemployment statistics do not provide an accurate depiction; they serve to understate the severity of unemployment.

However, even if one chooses to look at the official statistics, the following charts provide an interesting (and disconcerting) long-term perspective of certain aspects of the officially-stated unemployment (and, in the third chart, employment) situation.

The three charts below are from the St. Louis Fed site.  Here is the Median Duration of Unemployment (current value = 10.2 weeks):

(click on charts to enlarge images)(charts updated as of 2-3-17)

median duration of unemployment

Data Source: FRED, Federal Reserve Economic Data, Federal Reserve Bank of St. Louis: Median Duration of Unemployment [UEMPMED] ; U.S. Department of Labor: Bureau of Labor Statistics; accessed February 3, 2017;

http://research.stlouisfed.org/fred2/series/UEMPMED

Here is the chart for Unemployed 27 Weeks and Over (current value = 1.850 million):

unemployed 27 weeks and over

Data Source: FRED, Federal Reserve Economic Data, Federal Reserve Bank of St. Louis: Civilians Unemployed for 27 Weeks and Over [UEMP27OV] ; U.S. Department of Labor: Bureau of Labor Statistics; accessed February 3, 2017;

http://research.stlouisfed.org/fred2/series/UEMP27OV

Here is the chart for Total Nonfarm Payroll (current value = 145.554 million):

Total Nonfarm Payrolls

Data Source: FRED, Federal Reserve Economic Data, Federal Reserve Bank of St. Louis: All Employees: Total nonfarm [PAYEMS] ; U.S. Department of Labor: Bureau of Labor Statistics; accessed February 3, 2017;

https://research.stlouisfed.org/fred2/series/PAYEMS

Our unemployment problem is severe.  The underlying dynamics of the current – and especially future – unemployment situation remain exceedingly worrisome.    These dynamics are numerous and complex, and greatly lack recognition and understanding.

My commentary regarding unemployment is generally found in the “Unemployment” category.  This commentary includes the April 24, 2012 five-part post titled “The Unemployment Situation Facing The United States”, which discusses various problematical issues concerning the present and future employment situation.

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The Special Note summarizes my overall thoughts about our economic situation

SPX at 2290.06 as this post is written

Stock Market Capitalization To GDP – Through Q4 2016

“Stock market capitalization to GDP” is a notable and important metric regarding stock market valuation.  In February of 2009 I wrote of it in “Does Warren Buffett’s Market Metric Still Apply?

Doug Short has recently published a post depicting this “stock market capitalization to GDP” metric.

As seen in his February 2, 2017 post titled “Market Cap to GDP:  An Updated Look at the Buffett Valuation Indicator” he shows two different versions, varying by the definition of stock market capitalization. (note:  additional explanation is provided in his post.)

For reference purposes, here is the first chart, with the stock market capitalization as defined by the Federal Reserve:

(click on charts to enlarge images)

Stock Market Capitalization To GDP

Here is the second chart, with the stock market capitalization as defined by the Wilshire 5000:

Stock Market Capitalization To GDP

As one can see in both measures depicted above, “stock market capitalization to GDP” is at notably high levels from a long-term historical perspective.

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The Special Note summarizes my overall thoughts about our economic situation

SPX at 2280.85 as this post is written

Median Household Income Chart

I have written many blog posts concerning the worrisome trends in income and earnings.

Doug Short, in his February 2, 2017 post titled “Real Median Household Income:  No Growth in 2016” produced the chart below.  It is based upon data from Sentier Research, and it shows both nominal and real median household incomes since 2000, as depicted.  As one can see, post-recession real median household income (seen in the blue line since 2009) remains worrisome.

(click on chart to enlarge image)

Real Median Household Income

As Doug mentions in his aforementioned post:

As the excellent data from Sentier Research makes clear, the mainstream U.S. household was struggling before the Great Recession. At this point, real household incomes are about where they were during the middle of the Great Recession.

Among other items seen in his blog post is a chart depicting each of the two (nominal and real household incomes) data series’ percent change over time since 2000.

_________

I post various indicators and indices because I believe they should be carefully monitored.  However, as those familiar with this site are aware, I do not necessarily agree with what they depict or imply.

_____

The Special Note summarizes my overall thoughts about our economic situation

SPX at 2279.16 as this post is written

VIX Weekly And Monthly Charts Since The Year 2000 – February 2, 2017 Update

For reference purposes, below are two charts of the VIX from year 2000 through Wednesday’s (February 1, 2017) close, which had a closing value of 11.81.

Here is the VIX Weekly chart, depicted on a LOG scale, with the 13- and 34-week moving averages, seen in the cyan and red lines, respectively:

(click on chart to enlarge image)(chart courtesy of StockCharts.com; chart creation and annotation by the author)

VIX Weekly LOG since 2000

Here is the VIX Monthly chart, depicted on a LOG scale, with the 13- and 34-month moving average, seen in the cyan and red lines, respectively:

(click on chart to enlarge image)(chart courtesy of StockCharts.com; chart creation and annotation by the author)

VIX Monthly since 2000

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The Special Note summarizes my overall thoughts about our economic situation

SPX at 2279.55 as this post is written