"Intellectual brilliance is no guarantee against being dead wrong."
– Carl Sagan
Claudius Ptolemy, the brilliant 2nd-century mathematician, and astronomer wrote an unnamed treatise now referred to as the Almagest some 1,900 years ago. Almagest is an Arabic/Persian translation of “The Greatest Work”.
This book was preserved all the way from the era of the Alexandria Library through the time of Persian/Islamic astronomers, all through the European Dark Ages right through to today. It was a description of geometry and astronomy and reliably modeled the solar system in that it accurately predicted certain planetary movements and eclipses using an Epicycle framework – essentially circles within circles.
The flaw?
It used a Geocentric framework rather than the Heliocentric model postulated 1,500 years later by Galileo. The quote above is part of a larger Sagan quote, which reads: “[Ptolemy’s] Earth-centered universe held sway for 1,500 years, showing that intellectual brilliance is no guarantee against being dead wrong.”
It's important to keep that concept in mind. I refer to this conceptually as the distinction between precision and accuracy. You can have a model and framework that yields tremendous precision in its estimates but delivers little in the way of consistent, useful accuracy. Much of this has to do with the layering of assumptions.
For example, to derive earnings estimates for a company, you must first make assumptions about that company’s top line. There are usually a variety of assumptions that go into that top line estimate (industry growth, market share gains, new products, etc). Then you must make assumptions about expenses/margins that are typically predicated on either past trends or forward company guidance, both of which tend not to dynamically reflect shifting macro sands.
Finally, you then need to make further assumptions around nonoperating items, tax rates and buybacks. Let’s say that you have a 75% chance of being right in each of these independent assumptions. Now let’s say that you’ve made ten of these independent assumptions to get to your earnings estimate. What is the probability that your estimate is right? Around 1 in 20 (5.6%). That’s the problem.
The presumption is that all this precision and complexity increases the probability of being correct because you have this highly detailed model. But the likelihood of being accurate is extremely low precisely because of all these layered assumptions.
Back to the Global Macro Grind…
We are often asked about our estimates and how precise or close they are to the pin. Our response is usually that we don’t care so much about being closest to the pin. We’re aiming to be directionally accurate in rate-of-change terms. In other words, we try to keep things as simple as possible because we care more about whether conditions (Growth & Inflation) are accelerating/decelerating, than about what the exact number is going to be.
In the current quarter, we use a Stochastic Nowcasting framework, which increases the probability of being correct with the passage of time and incorporation of incremental data.
For out quarters, we apply a Bayesian Inference process. This process enables us to increase the probability of being accurate by avoiding the process of assumption layering. To understand this a bit better, consider the example of the famous Monty Hall Problem. The idea is that you are the contestant on a game show and there are three closed doors facing you.
Behind one door is a great prize like a new car. Behind the other two doors is something you don’t really want like a sack of dog food. You are asked to pick the door that leads to the prize. You choose one. Then you are shown one of the other two doors behind which is the dog food, and then you are asked if you would like to change your choice or keep the door you originally selected.
Frequentist logic would hold that it shouldn’t matter whether you change doors – your odds are still one in two. One door has been eliminated and two now remain, giving you a 50/50 chance of being right. So, it really doesn’t matter whether you switch or not. Bayesian inference says that’s all wrong. Bayes would argue that in the beginning you had a one in three chance of being right and, by extension, a two in three chance of being wrong.
However, once the game show host revealed to you the incorrect door that you didn’t choose, the probabilities radically changed. With that information now in hand, you should always switch doors because it means that you go from a one in three chance of being correct to a two in three chance of being correct.
The takeaway here is a simple but important one. Having a framework that objectively improves the probability of being directionally accurate is more important than having the most intellectually compelling narrative. Some of the smartest people out there are just as likely to be dead wrong, no matter how compelling their narratives sound. Investing success is a game of having a probabilistic advantage that enables returns to compound over time.
Given all of that, I wanted to highlight two of the most interesting developments of late. The first is commodities and oil. The second is rates.
Regarding commodities, Quad 4 is historically the only Quad in which the CRB Index generates an average negative quarterly return, and quite a significant one at that. It is essentially the mirror image of Quad 2. The average quarterly return of the CRB Index in Quad 4 is -4.2%, while the average quarterly return in Quad 2 is +4.4%. Quads 1 & 3 have returned, quarterly and on average, +1.3% and +1.7%, respectively.
It is notable that the CRB Index peaked on June 9th at 339 and currently sits around 294, down -13% in just under 4wks. For reference, the 19 CRB Index components and weights are as follows: 23%: WTI; 6%: Nat Gas / Corn / Soybeans / Live Cattle / Gold / Aluminum / Copper; 5%: Heating Oil / Unleaded Gas / Sugar / Cotton / Cocoa / Coffee; 1%: Nickel / Wheat / Lean Hogs / Orange Juice / Silver.
Just for fun, of those 19 components, guess how many are higher in price today vs June 9th?
There is only one component with a price currently above its June 9th price: Lean Hogs, +3.8% with a 1% Index weighting.
In other words, 18 of the 19 commodities in the CRB Index have turned lower in the past month. That is a resounding Quad 4 mosaic jigsaw puzzle piece that just slotted in. And remember, this commodity price collapse is in the throes of 8.6% inflation.
The obverse of the commodities coin is, of course, the Dollar. Just as Quad 4 is the only one of the four quads in which commodities fall, on average, Quad 4 is also the only quad in which the Dollar rises in value, on average. Historically, the dollar has posted a Quad 4 average positive quarterly return of +1.7%. Meanwhile, YTD, the Dollar is +12% and since June 9th is higher by 4%.
Now, turning to rates – the last refuge of the Quad 3 Scoundrel – we see the potential emerging for a similar reversal. The cycle high (thus far) in the 10-YR Treasury Yield was put in on June 14th at 3.48%. During the three weeks since, it has fallen by -58 bps to 2.90% and is increasingly flirting with a Bullish TREND breakdown. That being said, it has similarly flirted with TREND breakdown previously this cycle and not yet succumbed, so we are being patient for the signal to confirm.
What makes the duration breakdown so interesting is that if it does roll over to Bearish TREND, it will open a massive incremental asset class on the long side. Direct long exposure and Duration proxies like Housing should again become longs.
Remember, simpler is often better when accuracy is the objective. When rates move dramatically, Housing becomes a one-factor model – in both directions. Perhaps of equal interest is that historically, when rates have broken down following a positive expedited rate shock, the move in the other direction has tended to endure for years.
We’ll explore these concepts in more detail when we host our Q3 Quarterly Housing Themes Call next Wednesday, July 13th. Let know if you would like access.
Immediate-term Risk Range™ Signal with @Hedgeye TREND signal in brackets:
UST 10yr Yield 2.77-3.32% (bullish)
UST 2yr Yield 2.78-3.22% (bullish)
High Yield (HYG) 72.71-74.80 (bearish)
SPX 3 (bearish)
NASDAQ 10,729-11,614 (bearish)
RUT 1 (bearish)
Tech (XLK) 124-133 (bearish)
Shanghai Comp 3 (bullish)
Nikkei 25,710-26,898 (bearish)
DAX 12,321-12,978 (bearish)
VIX 26.00-31.38 (bullish)
USD 104.03-107.11 (bullish)
EUR/USD 1.016-1.045 (bearish)
Oil (WTI) 97.35-109.48 (bearish)
Nat Gas 5.11-6.83 (bearish)
Gold 1 (neutral)
Copper 3.35-3.95 (bearish)
To your continued Success,
Josh Steiner
Managing Director
