LinkedIn Says The Labor Market Is Strong

The chart below supports my point that the ADP private sector payrolls report was too negative on the labor market. As you can see in the chart below, the LinkedIn hiring rate in June is up 12.1% year over year as it remains at the highest level in the past 24 months. The past two months have seen an acceleration in hiring growth after the index had been tracking the previous year’s results almost perfectly. There aren’t any other major metrics which signal the labor market is as weak as the June ADP report showed. Using recent labor reports doesn’t predict intermediate term results (12-24 months), but it does imply that the next few months will probably be fine. There would have to be a catalyst to break the trend.

This past week’s jobless claims also supports the narrative that the labor market is strong as it fell from 250,000 to 247,000. It fell for the first time in a month. The only trend in that indicator is stability. Obviously, stability comes first before an increase, but don’t be quick to assume an increase is coming soon. It can easily stay below 275,000 for another few months. I am learning from a prior failed prediction where I said the jobless claims would get above 300,000 in the summer of 2016. I’m expecting my initial guess to be 2 years off.

I love when charts prove a prior narrative false. Investing is difficult when you have all the facts, but it’s impossible when you are operating on false pretenses. The chart below shows how the metric of the number hours it takes for the average non-supervisor worker to buy the S&P 500 is a bogus stat. The blue line shows that incorrect calculation. The orange line shows the correct way to look at this metric as it uses real S&P 500 earnings. The blue line doesn’t calculate what you’re getting when you buy the S&P 500, making it useless. I have previously used the blue line to show how the market is overvalued. I stand corrected as I didn’t consider how the calculation ignored real earnings.

The takeaway from this new analysis is that using this metric makes stocks appear less expensive from a historical perspective. The original metric showed stocks to be more expensive than the technology bubble which is unlike the price to earnings metrics, making it an outlier which deserved scrutiny. Now that we see it in the light of scrutiny we can toss it aside and go with the analysis that the market is more expensive than average, but not more expensive than the most expensive market ever in the early 2000s.

The chart below takes a stab at another metric which appears to be showing the market is very overvalued. One of the most cited valuation metrics is the Warren Buffett one which looks at the S&P 500’s market cap relative to GDP. The bears like to make the point about how Warren Buffett is ignoring his favorite metric, which furthers the case than the sentiment is too bullish. Personally, I don’t care what anyone’s opinion is; I only care about the facts. Anyone can have a wrong opinion, even Warren Buffett. What can’t be wrong is the facts, if you are using the right ones. The chart below is an adjustment to Buffett’s favorite metric.

It shows the Buffet metric adjusted for the U.S. treasury’s outstanding because it assumes that the debt will be monetized, devalued, or defaulted on if stocks fall. Essentially, I see this chart as way of changing valuations to adjust for an interventionist Fed. I reject this chart as a way to try to explain why stocks aren’t overvalued. The critical mindset to have when charts are made is to figure out if the creator of the chart was trying to get a result or simply searching for the truth. The prior chart adjusting for valuations made sense because nominal prices of S&P 500 shares are a faulty metric to review.

In this case the debt outstanding shouldn’t change valuations. If anything, having more debt outstanding only makes the economy more likely to be become unstable. The idea that the Fed will rescue an overly indebted economy and there will be no negative consequences is a terrible assumption. While the adjustment makes the valuations look like the adjustment made in the prior chart, that doesn’t mean it’s accurate. There is no absolute correct way to value stocks which means there will be some divergence among stats. The key is to see what is logical.

My objective analytical viewpoint when it comes to deciphering if charts are accurate depictions of reality is looking good. If you remember, I said the U.S. Macro Surprise Index was mostly bunk because it’s affected by changes in economists’ predictions. If the economists are very positive, but the growth is only ‘o.k.’ then this index looks terrible even though the economy isn’t doing poorly. I also made the point that the index does terribly in June and great in July historically. As you can see in the chart below, the index has improved to -56.60. I expect further improvement in the index which will cause Zero Hedge to stop caring about it because it won’t fit their narrative. It’s also worth mentioning that comparing the Fed Funds to this index is a bad idea because the index isn’t a representation of the economy. Zero Hedge switched from talking about GDP because Q2 will show an improvement over Q1 as I’m expecting growth to be 2.0% to 2.5%.

Conclusion

A great chart can provide amazing incite. However, charts can go awry when the creator decides to manipulate the data to make it prove a desired point. This is one reason why I love the FRED charts and those provided by Yardini because they’re done automatically by computers, exhibiting no bias. The way to spot the biases in charts is to come from the perspective that’s neither positive nor negative. Assume everything you know is wrong and then pick apart the chart to see if it makes sense. Both bearish and bullish charts can be wrong as you have seen in this article.

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