Reflections [Expanded version]

World in depths of business cycle slowdown

On 8th June 2018 we penned a warning that the worlds’ major 41 economies, as tracked by the OECD, were headed for a synchronized business cycle slowdown.

You can read the article here : World headed for cyclical slowdown.

Indeed, as you can see below, for quite a few months shortly afterward, we bottomed out with less than 11% of the 41 countries tracked having rising OECD LEIs:

The percentage of 41 counties with a rising LEI seems to have bottomed though and as this is a  leading indicator of the global leading indicator, the assumption may be made that perhaps the worst is nearly over. A couple of more months and we will see.

WLEI updated and some news

The U.S Weekly Leading Economic Index (WLEI) as at 01 Feb 2019 has been updated to our front page together with historical vintages file. Here is a snapshot of the last few vintages:

We seem to be revising down each week but the overall shape of the WLEI still hints at an index attempting to put in a bottom and recover.

The percentage of underlying weekly components and the percentage of time the WLEI has historically been above current levels remains similar from last weeks reading:

For several quarters now we have been working on getting additional high frequency weekly leading economic data incorporated into the WLEI. It is a lot easier said than done but we are close to the final release of WLEI2 which has 20% more discrete weekly components. What we like about it is that none of the components rely on any shut-down federal agencies which means it should be fairly impervious to an extended government shutdown.

To whet you appetite and interest, it is shown below at its reading last week:

There are very few weekly leading US economic composites that remain pure to their mandate of only using weekly published data, that have not suffered from false positives in the last two business cycles, so WLEI  V2.0 is looking very promising.

Have a good weekend.

Dwaine van Vuuren.

Yield curve inversion forecast update – Dec ’18

Based on the methodology discussed here we hereby update our U.S Yield-curve inversion forecast and subsequent recession and stock market peak forecasts. All the forecast dates have moved foward by 1 month:

Yield Curve Inversion Forecast Update Nov 2018

Based on the methodology discussed here we hereby update our U.S Yield-curve inversion forecast and subsequent recession and stock market peak forecasts. All the forecast dates have moved further back by 5 months:

Stocks valuations pose “clear & present” danger.

Those clients who have been with us since 2010 will know our refrain from issuing unnecessary and/or sensationalist warnings about the economy and markets. In fact, in 2012, the general consensus was that the US economy was about to fall back into recession, a view we opposed to quite some ridicule from certain quarters.

Whilst we see no immediate danger signals from the econometric models (apart from the narrowing yield curves in the bond market) we do see danger posed by current stock market valuations. Now stock market valuations have been touted as offering “clear and present danger” for the last 3 years running from several quarters except ours, so this is the first time this business cycle we are joining that clarion call. But using different models we might add.

Our model of choice when measuring risks (or opportunities) posed by US stock market valuations is the RecessionALERT Valuation Index (RAVI) which you can read about over here. The RAVI data for 3Q2018 has just been updated and is available in the CHARTS>MACRO>RAVI tab where you can review and verify the information we provide below.

Our main tools with the RAVI to assess long-leading stock market peak warnings are:

  1. The 4-quarter average of the 1-year SP500 forecast,
  2. The average annualized forecast from the 1, 2 and 3 year forecast models
  3. The 8-quarter average of the 2-year SP500 forecast.

These are shown below, where it is evident why we are sounding the alarm on valuations:

The RAVI 1-year (3Q18 to 3Q19) and 2-year (3Q18 to 3Q20) forecast for the SP500 are depicted below:

Whilst the r-squared values are very respectable for such short-run forecasting models, it is the act of the forecasts turning negative that is of more interest, since these foretold the last two recessions and subsequent stock market crashes. Both are firmly in the red.

Given that the models run 1-quarter in arrears, and the SP500 Total Return actually topped in 3Q18, it is quite feasible that we have witnessed the stock market top already. But if not, it just means that the valuations become even more stretched in 4Q2018 – a situation that could persist for up to a several quarters (or not). One thing we cannot deny though – the business cycle is clearly in the sunset stages.

There is one big “yes, but…” with these models. We only have an accurate track record of two recessions, whilst all our other econometric models have at least 6 , sometimes 10 on their track records.

What makes this model a particularly interesting addition to our arsenal though is that it is completely different to all the others and is the only metric we have that looks at valuations themselves as a trigger for recession.

In summary, a stock market correction is more likely to be triggered by overvaluations at this point in time than by concerns about the economy. Caution is advised.

 

2nd derivative of WLEI posts warning

The RecessionALERT Weekly Leading Economic Index (WLEI) is essentially a first derivative indicator (rate of change). We can create the second derivative by measuring the percentage of time the WLEI has historically spent above the current reading. The history shows us that this is a good leading indicator for another WLEI metric, namely the percentage of WLEI components in recession territory (we call this the “WLEI Diffusion”):

The 2nd derivative is diverging from the  WLEI Diffusion, and as we mentioned, in the past when this has occurred, the Diffusion eventually is forced to play catch-up.

This implies more structural damage could be ahead for the WLEI, that is not just limited to a deterioration in its levels.

The components of the WLEI currently in recession are all related to the corporate bond market (AAA/BAA etc.) The Credit spreads market composite and the labour market composite are looking impervious at this stage. This leaves any further damage to the Diffusion likely to originate from the stock market or the Treasury/Corporate bond spreads composite.

Another useful leading indicator for the WLEI is ECRI’s own WLI, which confirms that more damage ahead for the WLEI is likely:

The ECRI WLI can lead the WLEI on many occasions, as it is composed of some longer leading and/or more sensitive indicators than the WLEI.

When we constructed the WLEI our focus was less on longer leading characteristics and more on less “false positives”. As you can see from the chart the WLI has had 4 false positives so far this business cycle versus 1 for the WLEI. It’s a good pairing for high frequency leading data – you take the ECRI WLI as the 1st warning and the WLEI as second. If both are flagging recession, which looks increasingly likely in the next few weeks, you obviously need to take note and start consulting the more robust monthly models or the SuperIndex which is composed of many monthly models.

SP500 was ahead of itself but tailwinds could be back

During the 6 months running from March to September 2018, the SP500 was running counter to the seasonal average returns profile of the 4-year U.S Presidential Cycle:

It appears the seasonality averages eventually got their way and the SP500 fell hard in October 2018, in what was supposed to be a strong month. In all likelyhood the tailwinds of one of the strongest periods in the Presidential Cycle will come to bear and we should expect good returns for the next 8-10 months.

Below is a slightly outdated (as of 2016), but no less relevant, statistical analysis of the Presidential Cycle. We have just entered the 2nd month of the “PowerZone” which is the 11th month of the Mid-term year.

The height of the bars represent the average gain for the month, and the percentages within the bars represent how many of the months posted gains, followed by the gain/loss ratio. So for November 2018, the 2nd month of the “PowerZone”, we expect an average return of 2.5% with a 78% probability of a positive gain this month. The gains from the winning months in the 2nd month of the “PowerZone” outpace the losses 4.6 times to 1.

January 2019 promises to be the most powerful month of the entire 4 year cycle, with greater than 4% gains and a heady 93% winning percentage. The model suggests a dose of leverage between now and August 2019, although I prefer to scale back any leverage beyond April 2019.

The historical returns from the above suggested strategy of buying on 2X leverage from the 10th Month of the Mid-term year, selling in the 8th month of the pre-election year, and buying again with no leverage in the final month of the pre-election year and then selling again at points “SELL-A” (best winning ratio), “SELL-B” (best return) and “SELL-C” (most in the market) are simply astounding. In fact, I am not even going to bother putting them up for display lest your glasses become too rose-tinted.

Yield curve inversion & recession forecast

There is naturally a lot of focus on the U.S yield-curve at the moment, as it moves relentlessly toward inversion (when short-term rates are higher than long-term rates.) Can the history of the yield-curve inversion provide for useful forecasting as to the start dates of the next U.S recession?

The 10’s vs. 1’s yield-curve and U.S recessions in the post-war era are displayed below, where it is clear that the nine recessions since 1956 were predicted by yield-curve inversion, with one false positive in 1966.:
2018-09-22_1259

The chart below shows how many months the yield-curve inverted before each of the recessions. We ignored the false positive in 1966 to give the yield-curve the benefit of the doubt. The smallest lead-times to recession average 8 months, the median lead-time is 12 months and the longest lead-times average 20 months:
2018-09-22_1303

So all that is required now is to project the current yield-curve trajectory into the future to see when it will invert, arriving at a date of February 2019:
2018-09-22_1447

From this projected inversion date we can make some estimates on when we are most likely to see the arrival of a U.S recession based on the average short lead-time, the median lead-time and the average longest lead-time to a recession:

2018-09-22_1455

Now it is accepted that the U.S stock market is a forward-looking indicator and will peak before the onset of a recession. Sure enough, in our 2012 research note: “Recession: Just How Much Warning Is Useful Anyway?” we showed that any generalized stock market defensive actions 5 months before the onset of recession are likely to prove unproductive, based on the last 5 recessions. This would imply we need to start preparing for a U.S stock market peak around the following dates:
2018-09-25_0932

There is a lot of commentary around the yield-curve no longer being an effective recession warning indicator due to the artificial low-interest rate environment created by the FED. There is also the timeless stock market quip that when you start hearing that “this time is different” that things will turn out anything but different. There are a lot of theories as to why an inverted yield-curve for even short periods will guarantee a recession, but the one that made the most sense to me follows:

“Banks make longer-duration loans to clients who pay the longer term rates. These loans are the assets of the bank. Depositors lend money to the bank at the short-term interest rate. These are the bank’s liabilities. When the bank pays a higher rate on its liabilities than what it earns on its assets, it loses the incentive to forward more loans to businesses and stops lending. This causes a “credit crunch” or the falling availability of credit. Businesses struggle to roll over their current account credit and they are forced to downsize and lay off workers, and we enter a recession. The moment the Fed engineers short-term interest rates to go below long-term interest rates, the banks can generate a profit again, credit expansion will resume and the stock market and economy can recover.”

If one assumes the above narrative to be true, then it doesn’t matter how low the interest rate environment currently engineered by the FED is – when short-term rates are higher than long-term rates a credit crunch, stock market peak, and recession is inevitable.

We can make some interesting observations by measuring the area under the yield-curve when it is above and below zero respectively as depicted below:
2018-09-25_1022

We note that it does not take a lot (as measured by cumulative inversion area below zero) to trigger a credit crunch and recession. We can also deem the area above zero as representing “excess liquidity” and quite clearly the area of the current credit-easing cycle dwarfs all those preceding it. Many believe that the larger the credit easing excess, the worse the subsequent recession, but this is untested by any research we have conducted or come across yet.

World headed for cyclical slowdown

Despite the U.S leading economic indicators appearing healthy, the global economy appears to be headed for a slow down, with only 34% of the 40 countries we track having leading economic indicators (LEI’s) signalling growth ahead, and the actual GDP-weighted Global LEI growth now below zero:

2018-06-08_1200

The specific country details are displayed below:

2018-06-08_1204

The European countries, representing some 25% of world economic output have taken a decidedly worrisome turn :

2018-06-08_1207

Many of these LEI’s include sentiment data, and its probably a fair assumption to assume that the “trade wars” talk doing the rounds of late have a big part to play in these negative future growth projections.

Whilst the RecessionALERT U.S Leading index is currently looking robust, we cannot ignore the fact that there is a not-insignificant 40% correlation between the movements of the U.S LEI and the Global one. In fact a visual inspection shows that downturns in the Global LEI invariably always lead to downturns in the US LEI:

2018-06-08_1239

This correlation by no means implies a US recession, but it undoubtedly is likely to put downward pressure on the U.S LEI in the coming months.

It is early days for the co-incident data and no significant signs of a slowdown can yet be witnessed among them. To this end, here is an interesting chart of country GDP growth from 1Q2017 to 1Q2018:

2018-06-08_1316

If you are a RecessionALERT subscriber, you can view the comprehensive global report for May 2018 from the REPORTS menu. You can subscribe to RecessionALERT for a nominal fee over here.

Like this kind of information? We post occasionally to our public Twitter feed here : https://twitter.com/RecessionAlert2

 

 

Dealing with a runaway market

Those of you who have been following us since 2010 will identify us a perma-bulls. Even in the depths of the ECRI 2012 /Hussman recession calls we were firmly bullish on the US economy and stock market – quite contrary to the popular consensus at the time. Those subscribers who have been diligently following the RAVI SP500 forecasting model and its consistently accurate bullish forecasts will have noticed this year that all the targets we have set for 3Q2018 have been met on our Dashboard:

2018-01-18_1400

This means, for the first time since we have been running this model, that RAVI SP500 valuations have finally run ahead of themselves. This is not to say this exuberance will not continue for some time, but it is a warning for those who like to deploy valuation risk metrics in their asset allocation models.

Now for a long time, various valuation models have been at elevated levels. Here are a few below:

2018-01-18_1413

Despite these elevated levels, RAVI was forecasting bullish returns for 2016 and 2017. All these models above have very good correlations to 10-14 year ahead SP500 returns and in many instances of late were actually forecasting muted to negative 10-year ahead returns. But just because a valuation model is forecasting a negative 10-year return doesn’t mean that 1-3 year returns will be poor! This mistake is consistently made by forecasters! A case in point is shown below, using Warren Buffets famous valuation metric. Since 2014 this model has been persistently forecasting low to negative 10-year ahead returns – but that didn’t  stop the SP500 roaring ahead!

2018-01-18_1419

Does this mean Warren Buffets indicator is useless? Of course not – it means it’s been interpreted incorrectly! In all likelihood, in 10 years’ time we come back to this chart and remark on how accurate it was since the black line (actual 10-yr returns) will closely track the green line (the forecasted 10-year returns.) As far as a long-run forecasting models go, the Buffet indicator, whilst not the best, is fairly respectable with an r-squared of 0.76 – so it would be surprising if that black line doesn’t hug the green line closely!

2018-01-18_1434

There is no model that can directly predict short-term SP500 returns with meaningful accuracy. But you can get pretty damn close (as these things go) by deriving short term returns from accurate long-run models like the Buffet model. It works like this:

1.Find a really robust and accurate long-run (assume 10 year) forecasting valuation model (there are many)
2.Get the 10-year forecast from this model from nine years ago
3. Work out how much the SP500 has grown since this date 9 years ago
4. Subtract (3) from (2) to work out how much upside is left in the year ahead.

In fact we can apply this short-run look-ahead method to any x-year horizon, and this is what we do with the RAVI to compute 1/3/5 year look-ahead forecasts:

2016-04-04_1712

The important thing to bear in mind is that the current reading of a long-term  valuation model, be it Buffet, Tobin-Q, Shiller P/E, Hussmans Market-cap to Gross Value Add etc. means absolutely nothing to short-to-medium term forecasts. What is important, is what this model was saying 7-10 years ago and how much the SP500 has eaten into those forecasted gains since then.

Now the RAVI long-run model has the following 10-year forecasting profile, which at 0.89 r-squared is pretty respectable:

2018-01-18_1450

If we use the methodology described above to forecast 1-year ahead returns we get the following profile. I can tell you, an r-squared of 0.4 on such a short-run forecast is pretty decent as these things go. But quite obviously from the profile, you can see wide variances on occasion:

2018-01-18_1454

On a three year look-ahead things become rather respectable in terms of correlations for short run forecasts:

2018-01-18_1456

Five-year look-ahead accuracy is pretty remarkable given how close its correlation is to the accuracy of the 10-year forecast:

5yr

We can deduce that both the 5-year and the 3-year look-ahead models are forecasting around 4% annual growth for the SP500 from here on, which is pretty low. In fact it becomes pretty interesting to track the average annualized look-ahead forecast of all the models over time:

avgannual

You can see that as the SP500 has been tracking upwards relentlessly, so the average annual forecasts have been declining of late. But more interesting is that when the average annual forecasts turn negative, it looks like, on the surface, we have a nice recession/bear market warning. Stock market valuation model as recessionary indicator – the idea is appealing!

So there you have it – we are in an era of weak forecasted SP500 returns with all the elevated risks associated with that. You need to decide if we are in a “new paradigm” of prolonged elevated valuations (its quite possible) and take your chances, or de-risk accordingly. Caveat Emptor

Like what you see? Please support us with a modest annual subscription over here https://recessionalert.com/sign-up/

Negative returns for SP500 in next decade

The RecessionALERT Valuation Index (RAVI) has been updated for 1Q17 and for the first time since 1999, is forecasting negative 10-year total returns for the SP500:

2017-08-01_1347

The chart on the right shows that the RAVI continues to forecast SP500 decade-ahead total returns with relative accuracy, especially when one considers that the green forecast line has data points that are seen 10 years before the black line depicting actual 10-year returns.

Now there have been a lot of valuation models predicting 10-year ahead negative returns but this does not mean one should be getting out the stock markets. One needs to review the short run (albeit less accurate) forecasts. As we can see below, these still hint at reasonable short run returns of the order of 11% per annum:2017-08-01_1422

In March 2017, we used the 4Q16 RAVI forecast to predict returns for the SP500 to the end of 2017. Our low estimate was 2472, our median estimate was 2,565 and our high estimate was 2,718. As you can see from the RAVI daily tracker on top-right below, we have achieved the lower target and are 3.8% away from the median target and 10% away from the high target with some 5 months still to go:
2017-08-01_1424

Here is another interesting way to asses potential short-run returns for the SP500 – look at the US economy as per our Long Leading Index. When this signals recession then we have cause for concern for the stock market
output_Ef8qe2

25 most important US economic indicators animated in 1 minute

Here’s something fun we played with after just compiling our June Long leading US Index report for our subscribers

output_Ef8qe2

Horrific revisions to HWOL data

The Conference Board Help-Wanted-Online (HWOL) program is closely followed by us to get a feel for the labor market. It is one of over two dozen labor indicators we examine. The monthly HWOL data have been produced by the Conference Board since May 2005, replacing the Help Wanted Advertising Index of print ads, which was published from 1951 to 2008. HWOL data contain the universe count of all ads posted online during a month, with a mid-month survey reference period (e.g., data for October would be the sum of all posted ads from September 14th through October 13th). The HWOL program collects data from over 16,000 online job sources and removes duplicated ads.

The February release incorporated revisions with the following description “With the February 2017 press release, the HWOL program has incorporated its annual revision, which helps ensure the accuracy and consistency of the HWOL time series. This year’s annual revision includes updates to the job board coverage, a revision of the historical data from May 2005 forward, an update of the Metropolitan Statistical area definitions to 2015 Office of Management and Budget (OMB) county-based MSA definitions, and the annual update of the seasonal adjustment factors.”

“Great stuff” we thought. “Some solid revisions to keep us honest”. First up was “Total ads” which are all unduplicated ads appearing during the reference period.  This includes ads from the previous months that have been reposted as well as new ads. We had to double-take when we looked at the data. It looked vastly different to the last time we peeked at it. Upon inspections the revisions were downright nasty:
2017-03-08_1911

We also look at the “New ads” which are all unduplicated ads which did not appear during the previous reference period. An online help wanted ad is counted as “New” only in the month it first appears. This is more volatile but provides useful comparison data to “Total Ads”.  Again this is when that coffee you’re holding spills into your lap as you look in disbelief…ugly ugly ugly.
2017-03-08_1911_001

Both of these metrics are screaming recession from the hilltops – and this just after revisions. Given that the Conference Board is an organisation that’s being doing the data compilation and revisions thing for a while now, this has to be pause for thought. The labor market is not as well as we may think.

Let’s look at various labor indicators taken from our Long leading Index of US Economy:

Weekly Unemployment Claims, an old stalwart,  look benign..
2017-03-08_1922

The Fed’s composite of 19 Labor Market Indicators looks rather pale….but no rooftop alarm bells just yet.
2017-03-08_1923

We had quite a scare from the % of US States with rising unemployment rates, but that resolved itself over the last 3 months:
2017-03-08_1928

So these HWOL revisions look rather alarming, but are not being collaborated by many other traditional metrics. Lets look at it again, but in the context of the last recession (grey shading). There’s no two ways about it – butt ugly.
2017-03-08_1935

The folks at The Conference Board are onto this though. From their website : “NOTE: Recently, the HWOL Data Series has experienced a declining trend in the number of online job ads that may not reflect broader trends in the U.S. labor market. Based on changes in how job postings appear online, The Conference Board is reviewing its HWOL methodology to ensure accuracy and alignment with market trends.”

The Board of Governers sniffed that something was up in June 2016 already, observing a substantial divergence since the end of 2012 between HWOL and the Job Openings and Labor Turnover Survey (JOLTS), administered by the Bureau of Labor Statistics. From their note : “All told, the average price for Craigslist job ads rose substantially, and roughly doubled since the end of 2012 (Figure 2), coinciding with the period when online vacancy posting as measured by HWOL noticeably underperformed the JOLTS vacancy growth.”

2017-03-08_1950

Now that the Conference Board is sanity-checking its HWOL methodology, it’s going to be really interesting to see how this pans out. But can this really be simply blamed on Craiglist prices? I’m not so sure. Surely its not that ridiculously simple?

Our house view is that we may have recently narrowly avoided recession, but are not close to it now. The lessons here are that reliance on single economic time-series, no matter how comprehensive they may appear (HWOL is fairly comprehensive in its number of datapoints), can be dangerous. It also highlights how revisions can wildly swing data with certain economic time series (as opposed to financial data such as interest rates, interest rate spreads, bond yields, credit spreads,  corporate bond yields and the like.)

Mixed Signals from Labor Market

We keep getting good news about employment and the labor market. But we rarely see the less optimistic numbers.

THE GOOD

Yellen’s Labor Dashboard (see here) is looking strong with all but 3 of the 9 components above pre-recession levels:
2016-11-16_1744

The Employment Trend Index briefly wavered but now seems to be picking up steam again
2016-11-16_1758
Weekly unemployment claims are recovering from a recent near-miss recession call:
2016-11-16_1803

MIXED SIGNALS

The popular unemployment numbers, by many different measures, seem to be bottoming-out but no cause for alarm yet
2016-11-16_1741

The Federal Reserve Board of Governors Labor Market Conditions Index is looking iffy. The broadness of this index makes its current levels worrying
2016-11-16_1806

Overtime is looking weak, but attempting to raise head above water:
2016-11-16_1804

An index derived from the percentage of U.S states with rising unemployment looks worrying. Whilst the national unemployment figures seem fine, the population demographics of some large states seems to be masking underlying weakness at a state-level. Again, the broadness of this index makes for worrying numbers:
2016-11-16_1810

THE BAD

Help-wanted online looks to be recovering from a really protracted  bad spell:
2016-11-16_1756

Here is another way of looking at the state-level unemployment numbers. The black line is derived from simply averaging up the unemployment rate from each individual state whilst the green line is the actual % of states with unemployment rates that are rising.
2016-11-16_1815

THE UGLY

Another useful way to look at the state-level unemployment is to count how many states have unemployment rates higher than the lowest (best) value seen in the expansion to date:
2016-11-16_1819

That means 75% of US States have unemployment levels higher than the best (lowest) numbers yet witnessed.

In summary, it would appear that several large-population states may be enjoying employment gains, but large swathes of the U.S are not.

NOTE : The state-level unemployment metrics shown above are excellent early-warning signals and are included in our highly comprehensive U.S Long-Leading Economic Index

U.S Economy remains vulnerable

It is interesting to see the recent re-appearance of articles relating to flashing warning signals of recession (see here and here and here)

It is true that some genuinely troubling signals are starting to make themselves known. Let’s look at some of them.

Heavy Duty Truck sales, a reliable long-leading indicator for US recession, has recently tanked:
raupdatesept_1

Growth in Total Freight Shipments and Revenues has been negative since early 2015::
raupdatesept_2

The Inventory-to-Sales ratio was one of the first trouble spots and has persisted for quite some time now:
raupdatesept_3

A composite of 35 diversified spreads from the Credit Markets is also providing a  warning:
raupdatesept_5

Lending standards at financial institutions are tightening up:
raupdatesept_4

The annual growth in corporate profits has been negative for six quarters now, although seems to be recovering:
raupdatesept_9

Quarterly % change in Federal Tax Receipts are looking vulnerable:
raupdatesept_10

A composite of various housing market indicators is left wanting, but showing signs of recovery:
raupdatesept_11

The collapse in the oil price that decimated the shale gas industry has led to a well publicized  recession in industrial production and manufacturing…
raupdatesept_13

But by far the most worrying trend, is the labor market, where a broad-based, consistently increasing weakness among the 52 US States is being masked by national numbers being touted about that include high population density states:
raupdatesept_6

The prior chart that shows the average unemployment rate among the 52 states, together with the % of 52 US States with rising unemployment (now at 50%) being in far worse shape than the national unemployment rate below implies:
raupdatesept_7

These are just a few indicators in a battery of twenty-one that we examine, and whilst there are no alarm bells yet, the aggregate composite of all 21 indicators shows the US economy the most vulnerable to exogenous shock since this expansion started:
raupdatesept_8

Unemployment more widespread than thought

The Total Non-farm Payrolls data made another solid print for the month of July 2016, leading to the assumption that all is good with employment in the U.S:
2016-08-22_1641

Similarly, if we examine the countrywide Civilian Unemployment Rate, we also get reassuring signs:
2016-08-22_1646

However, if we dig deeper and examine the per-state unemployment rates for 52 U.S states from the Bureau of Labor Statistics, a very different picture emerges:
2016-08-22_1648

The average state unemployment rate seems to be putting in a bottom, a less flattering picture than that painted by the nationwide unemployment rate. But the real surprise comes from the percentage of 52 US states that have rising unemployment, which shot to over 60% for the month of July 2016. The last time this rose to above 60%, was six months before the economy peaked in 2008.

The chart below shows all prior occasions the percentage of U.S States with rising unemployment went above 60%. We see that the percentage of US states with rising unemployment is an excellent proxy for the probability of US recession:
2016-08-22_1659

It is clear some close attention is going to have to be paid to this metric over ensuing months. Whilst the national rolled-up unemployment figures are not showing signs of stress, it is quite clear that stresses are building up when examining the individual state data.

The percentage of U.S states with rising unemployment is but but one of 21 indicators we use for our Long Leading US Economic Index.

NBER’s Big-4 Indicators had a narrow miss

Reading through all the positive press about jobs numbers and so forth, its hard to comprehend that the 4 main indicators used by the National Buro of Economic Research (NBER) to determine US recessions, had a narrow miss recently.

If you recall from our popular 2012 article, the NBER does not define a recession in terms of two consecutive quarters of decline in real GDP. Rather, a recession is a significant decline in economic activity spread across the economy, lasting more than a few months, normally visible in real GDP, real income, employment, industrial production, and wholesale-retail sales.

With regards to the monthly data, they examine 4 monthly co-incident indicators:

  1. Industrial Production
  2. Real personal income less transfers deflated by personal consumption expenditure
  3. Non-farm payrolls
  4. Real retail sales deflated by consumer price index

If one takes the month-on-month percentage change of these four data series, and combine them into a standardized average composite, you get the below, where we had negative prints for February and May:
2016-08-12_1851

Taking a moving average of the above to smooth out volatility, we get the following index that reliably signals recession when it turns negative. Lets call this event Syndrome-One
2016-08-12_1853

We can also count the amount of times the non-smoothed month-on-month indicator in the first chart has dipped below zero in a rolling 4-month period. When this count reaches 2 we are in a “danger zone” and when it hits 3, we are most likely already in a recession. We hit the danger zone in May and June. Lets call this count reaching three Syndrome-Two.
2016-08-12_1859

Another interesting thing to note is how many consecutive negative prints the indicator in the first chart has made. When this hits three we are also most likely in a Recession. Lets call this event Syndrome-Three:
2016-08-12_1905

The below Syndrome count shows how many of the three syndromes are present at any time. If two or more syndromes are present, we are most likely already in recession.

2016-08-12_1914

We run a more sophisticated algorithm for the Big-4 for our subscribers, as described in this robust tested methodology, and here are the probabilities of recession from the model:
2016-08-12_2001

To conclude, looking at the individual co-incident monthly data used by the NBER shows a far more pessimistic view currently than when looking at a syndrome of conditions. But the co-incident data in this particular indicator and the recession probabilities we are registering are not as bullish as the employment data would have you think. In fact, taking our proprietary implementation of the Big-4 index, and comparing it to the last 8 expansions, shows just how meek this recovery has been:

2016-08-12_2007

There is one final interesting observation though – for the first time this expansion, the co-incident data is coinciding with the weak leading economic data made from 21 leading data series and first witnessed  for February 2016. And that’s something worth pondering about.

2016-03-03_1334

 

Number of countries with back-to-back negative quarterly GDP prints is rising

2016-07-01_1721

The percentage of 41 OECD countries around the globe that have just posted a negative 1Q2016 on the back of a negative  4Q2015 (old fashion technical recession) has started to rise. Its nothing to be concerned about just yet but the rise itself, although shallow, is something worth watching as 2Q2016 numbers start coming out.

U.S Economy most vulnerable to any shock since 2008

The #Brexit vote caught the consensus view off-guard and stock markets, currencies and commodity prices have made large responses. This may be bringing up thoughts if Brexit could be the external shock that marks the decent of the U.S economy.

Whilst we will not entertain making predictions on this complex matter, we can however state that the U.S economy is the most vulnerable it has ever been since the 2008 financial crises. This is at least according to our composite of 21 leading indicators as at May 2016 shown below:

2016-06-24_1315

From the green diffusion line in the chart above we note that more than 50% (eleven) of these indicators are now in recession territory, with the overall (black) composite hovering near contraction (the red line). Eleven of the 21 indicators are long-leading and ten are short-to-medium leading.  Six  (60%) of the  short-to-medium leading indicators are in recession and five (45%) of the long-leading indicators are in recession territory.

Whilst the above analysis may appear bleak, a probability model taking all indicators into account only forecasts a 4.8% probability of recession within the next 6-12 months:
2016-06-24_1334

Visitations of the green diffusion index to the 50% mark and of the black composite to the red zero mark have been frequent in the past without leading to recession, but the fact of the matter is that these are periods of extreme vulnerability of the economy to internal or exogenous shocks or  geopolitical events. With no margin of safety, or buffer, it doesn’t take a very large shock to tip many of the indicators past the point of no return, resulting in contagion to other indicators and finally the whole economy.

The long-leading components of our composite of leading indicators that are currently in trouble are:
2016-06-24_1414
2016-06-24_1415

The short-leading components that are displaying signs of distress are:
2016-06-24_1419

Recession Probability Roundup : Elevated levels

NOTE : This is a subscriber-only article that was made open for public viewership on 20 May 2016.

A few subscribers have been concerned by the recent jump in recession odds of the Headwinds Index model to 60%
2016-04-26_1755

A probability of recession of 60% most certainly also implies probability of no recession of 40% and of course this is related directly to any false positives that may (and have) occurred in the past (see March 2003 in above chart.) You will note from the Headwinds chart on top of page 8 of the most recent SuperIndex report that we make a recession call only when the headwinds index exceeds 5, since this is the level that has produced the least false positives in the past. Only when this occurs, does the Headwinds index add one point to the Recession Forecast Ensemble (RFE)

Also, the Headwinds index, due to its stylized (as opposed to numeric) nature is very lumpy and thus recession probabilities can jump by large amounts moving from one headwinds level to the next. So whilst this model is showing elevated recession probabilities in 9-14 month time it does not constitute actionable information at this juncture.

The HeadWinds index is but one of the 6 models in the RFE and that is precisely why we designed the RFE – to allow for input of multiple robust diversified models into determining recession. Even if the Headwinds index was to move to 6 and the model were to call recession, the RFE would only rise by 1, which still does not constitute actionable information other than maybe some modest  hedging or de-risking activity.

Another way to look at the RFE is to average the current recession probability showing on each of its six model components, which is currently showing a 14.6% probability of recession. This model appears to have served well in the past, with zero false positives above readings of 0.20.
2016-04-26_1743

It is therefore true that recession probabilities are elevated, the highest they have been since this expansion started in 2009. In fact, we have been witnessing this quite emphatically with non-RFE components, with both the Weekly Leading Economic Index (WLEI) and more importantly, the new and comprehensive US Long Leading Index.

But as the chart above shows, elevated probabilities only becomes concerning once the average RFE component recession probability is above 0.2.

It is our suspicion that the recession probabilities will abate in coming months, purely based on the recovery we are seeing in the WLEI and the March bounce we saw in the new Long leading Index report published last month to the USLLGI reports tab. This leading index has over 50% of its 21 indicators in recession territory (green line below).
2016-04-26_1749