The following chart shows the 1-year moving average of the natural log of real total corporate dividends (adjusted for inflation). When using natural logs, exponential growth can be seen as a straight line.
Click to enlarge.
I have good news, bad news, worse news, and more good news.
1. The good news is that we made it back into the red long-term trend channel.
2. The bad news is that the blue trend failed a year ago. It is what got us back into the red long-term trend channel.
3. The worse news is that the red long-term trend channel has now failed again as well.
4. And finally, the good news. Maybe nobody will notice or care.
Let's zoom in for a closer look.
Click to enlarge.
Source Data:
St. Louis Fed: Custom Chart
Real Estate Newsletter Articles this Week: Existing-Home Sales Increased to
4.15 million SAAR in November
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At the Calculated Risk Real Estate Newsletter this week:
[image: Existing Home Sales]*Click on graph for larger image.*
• NAR: Existing-Home Sales Increase...
11 hours ago
4 comments:
This parabola thing is pretty fascinating.
Is it safe to say that you think parabolas in financial systems are unnatural (unsustainable) so that's why you point them out?
It seems there are three components of your parabolas that are interesting (beyond just the existence of the parabola):
1) fit
2) duration of fit
3) slope at failure
It seems to me that
1) "fit" is the amount of unnaturalness (almost, like a manipulation rating).
2) "duration of fit" is the skill level of the manipulators or maybe the gullibility of the participants.
3) "slope at failure"... this one... not sure what it is, but it's a number/measurement and it would be interesting if it was correlated-with/a-function-of 1 & 2.
Seem likes are you could be (somehow) measuring (quantify) human behavior here. NOT with the individual parabolas but with the statistics about all your parabolas.
You need a database of parabola types with the three items above.
It would be interesting to see if all of your parabola stats then showed any pattern over time.
Parabolas are common in nature. When a ball is thrown, that's a parabola.
I therefore don't think parabolas are unnatural. I just didn't expect to see so many in economics since each one must end in failure.
So let's talk about what it means to be parabolic.
In nature, it just means that a constant force (like gravity) is being applied. That constant force translates to a constant acceleration. That acceleration leads to a velocity which grows (or shrinks) linearly over time. The position grows (or shrinks) parabolically.
Here is a parabolic progression.
1, 4, 9, 16, 25, 36, 49...
y = x^2
Note what's being done at each step. First 3 is added, then 5. Then 7, 9, 11, and so on.
So let's relate this natural phenomenon to the economy. I see two types of parabolas.
1. A constant positive force is being applied. Picture a hot stock or commodity that investors pile into. Eventually you run out of investors and it's game over.
2. A constant negative force is being applied. Picture an economy that is being pulled down by gravity. Now picture our government throwing massive one-time stimulus at it all at once. To me, that's like a bat hitting a ball. The initial direction is up but gravity linearly reduces the upward velocity. At some point the ball stops going up and begins to fall again.
Let's talk about your "fit" concept.
In a normal economy, let's say there's a lot of turbulence caused by fluctuations in short-term interest rates. These fluctuations add uncertainty and help break up parabolas before they can fail spectacularly. Picture a ball flying in gusty winds. Harder to bet on where it lands.
Now picture our economy. There have been no gusty winds. The ball is moving in a vacuum. It doesn't go up chaotically. It goes up smoothly. It adds false confidence that it will always go up. It gets people to take more risk.
To be continued...
Your "duration of fit" concept is definitely something that has interested me. When I make parabolic charts, the more elapsed time in the parabola the more interesting/dangerous the chart becomes. Put another way, the more time investors have to unknowingly embrace the parabola, the more spectacular the failure can be.
This is one reason commodity parabolas can be especially dangerous for investors. They tend to have long timeframes.
1. Somebody starts to hoard.
2. The price starts to rise.
3. More people hoard.
4. The price really starts to rise.
At some point, as with hot stocks, somebody thinks about selling. Not everyone thinks parabolas are sustainable. Unlike stocks (generally), there is something else going on as well though.
As the price rises, commodity producers up production. Stock investors dabbling in commodities get blindsided. They aren't used to seeing this behavior.
"Slope at failure" is also interesting. The steepest act as if one friend tells 10 friends, each friend tells 10 friends, and so on. I wonder how much the Internet has contributed to that!
I am seeing human behavior in these charts but I'm also seeing advanced trading algorithms trying to take advantage of this behavior. You can bet I'm not the only one searching for parabolas.
George Soros understands parabolas. He's done very well riding them and getting off.
Parabolas come in all shapes and sizes. They can start and stop on a moment's notice. They can be slow or quick. They can be smooth or choppy. Some start and fail in unexpected ways. Not every parabola fails spectacularly. Some just transition fairly harmlessly to a more sustainable trend. All that can be said with absolute certainty is that they do all fail. None are sustainable.
Other than ZIRP smoothing some of them out (an opinion) and the Internet enhancing their behavior (so many charts, so many sharing) I don't think I could easily group the parabolas I've seen. Each one seems unique, like a snowflake.
It does seem that ZIRP should be having some effect on them.
Oh well, interesting things to see and watch anyway.
Have a good weekend.
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