Our human brains are wired to reduce complexities into simpler parts, from which we then draw linear conclusions. While this may have served us well from an evolutionary standpoint, it often misleads us when it comes to navigating financial markets.
The financial landscape is littered with many examples of this, the most enduring of which might be the “market as economy” paradigm, which always seeks to explain market moves with economic rationale.
The allure of the paradigm is twofold, first because it forces logic onto often chaotic and inexplicable movements in asset prices, and people crave the certainty provided by logical reasoning. Second because the paradigm works some, but not all of the time.
The second reinforces the first because if prices move counter to how economic logic dictates they should, people figure that their original rationale is incorrect and then bend over backwards to come up with a new line of reasoning to explain why. In this way, the paradigm works just enough to make one think that the fault lies in their reasoning, rather than with the paradigm itself.
In this Collection we discuss the “market as economy” and similar paradigms, their limitations that lead to erroneous conclusions, as well as other ways of thinking about cause and effect in markets. We hope that this Collection helps readers to think differently about markets, or at least gain an appreciation of how different ways of thinking about markets can lead to drastically different outcomes.
Another commodity making record highs and grabbing headlines is lumber. Specifically, lumber in the United States. What could be driving the rally in this time of great uncertainty?
As is evident from the chart, lumber prices are at multi decade highs, with the PPI index for lumber prices running sharply higher ever since the pandemic began. This seems to be a consequence of a booming housing market coupled with soaring levels of home renovations and DIY improvement projects.
However, as with other commodities facing Covid related disruptions, we must ask: what about supply?
It turns out that the US lumber industry is facing the same kind of supply related disruptions due to Covid. Producers cut back on their levels of production at the beginning of the pandemic in anticipation of falling consumer demand. Lockdowns were, and still are, extremely detrimental for economic growth after all.
However, demand for house building, new or renovated, did not tank. This can also be observed in the chart above, where the index dipped slightly at the beginning of 2020, before embarking on its meteoric rise. This is in sharp contrast to oil and copper, both of which suffered major price falls before bouncing back with a vengeance.
On top of demand staying strong, supply chains were also disrupted, negatively affecting delivery times, the natural result of which is even more upward pressure on prices, and the chart we see today. Of course, all of this is strongly related to demand for housing, specifically new housing, in the US.
Here, we see the all too familiar Covid blip, with a sharp drop in new units being constructed during the initial lockdowns. Construction then came roaring back, pulling lumber prices along with it. This strength in new housing construction is corroborated by the bullishness in the general US housing market, with the Case Shiller Index moving higher during the course of the pandemic as well.
All of which begs the question, how is this possible?
Mainstream narratives attribute this to the massive amounts of both fiscal and monetary stimulus pumped into the system. But we know that QE does not work the way people think it does, which means that house prices are not higher because of the fabled “flood of liquidity”. Instead, QE has affected house prices by lowering interest rates, which has resulted in lower mortgage rates.
To be concluded…
Great economic data coming out of the US last week has the market in a tizzy. Unfortunately it’s the confused-not-great kind of tizzy, not the giddy-everything-is-rosy kind.
Retail sales in the US grew at a mindblowing 27.7% YoY, while jobless claims came in at 576,000; the first time it printed below 700,000 in about a year. Given that the last few months have seen USTs at the forefront of assets “pricing in” the great reflation, the majority of traders were looking to see yields explode even higher.
Instead, yields… fell. Needless to say, everyone rushed to defend their chosen narrative. Some rolled out the classic line, “the market has fully priced it in”. Others claimed that it was a bear market rally, and that US yields would rise again (that is, UST prices drop as selling restarts).
However, from a broader standpoint, 10 year yields have been falling for over a decade. From this multi year perspective, the whole move higher in 10 year yields from their Covid 2020 lows to the ~1.8% levels seen in April ‘21 is the correction; and the buying after last week’s data a return to trend. (Assuming the buying continues)
The common thread linking both of these lines of thinking is that they assume markets move together with the economy, that asset prices must faithfully reflect an underlying economic reality. Because they cling on to the idea in their heads that markets “should” behave in a certain way, they are unable to see market developments from other standpoints.
USTs, for one, are not just mere puppets whose strings are pulled by market perceptions of inflation and economic growth. They are a crucial part of the global financial system through their use as collateral in the repo market. Moreover, central bank action has made them ever scarcer.
Perhaps from the repo standpoint of people needing to own USTs, good data just isn’t as pertinent as the fact that 10 year USTs are trading at their cheapest levels for a year? More importantly (and ominously), in failing to see things from outside their “market should do what I think it does” perspective, they fail to ask: “Why are people looking to acquire more safe collateral even when presented with blockbuster data?”
Ultimately, the economy doesn’t care if traders and market participants are confused. At the point in time where the data was collected and relevant, US consumers/workers had a ray of optimism in a very bleak last twelve months.
But will it last? Only time will tell how much of retail sales growth was due to stimulus check spending and further reopening. The true challenge is making this positive spike sustainable. This means getting the labor force participation rate back up to pre-Covid highs at the very least (pre ‘08 levels should be the true objective, although this seems like a bridge too far). Doing so will provide the impetus for the kind of economic recovery lacking since the 2008 financial crisis – an all inclusive one.
In the meantime, let the economy be giddy for a while, as the markets run through another episode of “good data is bad and bad data is good”.
We now know that the economy cannot reliably predict how a market moves, but what if we see things from the opposite perspective – can the markets predict the economy?
Well, for the stock market, the answer is also a resounding no.
After all, it is (in)famous for being able to not reliably predict recessions. Paul Samuelson put it well when he said:
“The stock market has predicted 9 out of the last 5 recessions.”
Of course, the specific numbers will change depending on where you come across it, but the first number will always be larger than the second.
These days, the quote is often used in a way that is meant to be funny.But with how much so many commentators and traders bend over backwards to explain in their narratives any divergences in economic and stock market performance, it does make one wonder if the aphorism is more sad than funny.
Now, the bond market on the other hand, is a much better predictor of economic recessions.
Specifically, the spread between 2 and 10 year US Treasury (UST) yields have been predicting recessions accurately since the 1970s.
Every time the 2-10 spread has fallen below 0 (known as an inverted curve), that is the yield on the 2 year is higher than the 10 year, the economy has fallen into recession soon after.
This particular spread is used (as opposed to the spread between, say 3 month and 5 year USTs) as the 2 year is seen as the longest maturity UST over which the Fed’s interest rate policy holds sway. Meanwhile, the 10 year UST is the benchmark interest rate for a large portion of the global fixed income market.
Also, intuitively, the 30 year bond’s yield is too long term a rate to use.
Hence, when short term rates, as represented by the 2 year note, rise higher than those of the 10 year, it is an indication that money is harder to borrow in the short term than it is in the longer term.
This is of course not something that happens except in very strained borrowing and lending conditions; i.e. recessionary conditions.
If any market can make a claim of fulfilling the mainstream’s notion of Markets = The Economy, it is the bond market, specifically US Treasuries.
Given the global importance of the US economy and how interconnected the world’s economies and financial markets are, an inverted US yield curve is not a good harbinger of things to come globally.
It’s 8 am on the first Friday of the month.
You know the drill, you’ve experienced many Fridays like this before. You’ve done your analysis and are prepared to make a trade in half an hour’s time.
No nerves or jitters, it’s just like every other first Friday of the month.
The NFP number hits the tape. It’s a MASSIVE miss. You pile on your shorts on the SPX.
But… the market rallies. It’s now 8.35 am, the market is still rallying. You close out your trade, take the loss.
What just happened?!?!
Bad data is good!? Cue disbelief and confusion.
Most market participants, whether they’ve ever traded an NFP number or not, can probably relate with the above scenario; where the market as a whole reacts in a way completely opposite to how it should have reacted.
The emphasis here is on the word “should”, because thinking that the market should or should not react in a certain way is a product of thinking in a manner that discounts the emotions of its traders.
Clearly, if this mode of thinking is valid, then the “bad data is good?!” or “good data is bad?!” scenario cannot happen. But experience has shown that it does happen, and repeatedly too.
So, what is going on?
In general, such scenarios tend to occur when a market is trending very strongly.
This is best exemplified by strong bull markets, where traders ignore weak economic conditions to furiously bid up prices, causing them to make new record highs at a frenetic pace.
The old nugget of trading wisdom stating that markets which ignore contrary economic conditions are strong markets was written to describe precisely such a situation.
Often, these “bad data are good” market moves are rationalized by commentators who claim that markets are ignoring the economic weakness because they expect central banks to intervene with looser monetary policy.
This argument has become even more common over the last decade, especially with the onset of QE. Now, every “bad data is good” move in markets is rationalized away with “markets expect more QE”.
A good example of this is how global asset markets rallied sharply off their lows in March/April 2020, even as economies over the world faced record contractions and labor market dislocations.
Central bank action certainly affects how participants view risk taking, but the real driver of the massive, breathtaking moves especially prevalent in late stage bull markets is, believe it or not, fear.
Fear of Missing Out, more commonly known as FOMO, is what makes prices go vertical in late stage bull markets. After all, very few people can stand by and watch their neighbors quickly growing richer than them without jumping into the market with both feet.
Of course, the “good data is bad” scenario is just the opposite, where traders reject all positive data out of pure fear that prices will keep falling and conditions will not improve.
This creates massive liquidation pressure that also causes market prices to go vertical, just in a southerly direction.
Emotion, it’s a powerful thing.
Something crazy happened on the 20th of April 2020. The American crude oil benchmark, WTI, traded below $0. Yes, suppliers were paying people to take their production off their hands. In a world made topsy turvy by Covid just a month prior, having someone pay you to take their oil was so absurd that it was hilarious… but would you take the money?
First and foremost, WTI is a futures contract that is delivered to Cushing, Oklahoma. Cushing is the hub for oil storage in the US and hence also the nexus for a series of pipelines that deliver oil from all over North America. The interesting thing about Cushing, at least for the purposes of our discussion, is that it is landlocked.
In other words, it is very easy to get oil into Cushing, but almost impossible to export it. This means that available storage in Cushing is very dependent on domestic demand for crude oil. If demand for oil products, and hence crude, is weak, then more crude gets stuck in Cushing.
Not forgetting the supply side, the discovery and exploitation of the American shale patch has brought about a surge in domestic production; and these barrels of oil tended to end up in Cushing if they could not be easily brought to the export market.
Simply put, prior to Covid, the shale glut was already taking up a lot of space. Then came the double whammy of Covid and the Saudi production hike.
The Saudis decided to increase their production of crude in early March 2020, from 10mm barrels a day to 13mm barrels a day in order to combat the flood of oil supply from Russia and the American shale patch. Naturally, oil prices tanked.
But their timing could not have been worse. Covid swept across the globe shortly after, leading to lockdowns all over the globe. Demand for crude oil and its products fell off a cliff overnight just as Saudi Arabia ramped up its production, causing a catastrophic fall in global crude prices.
Which brings us back to Cushing, which as you recall, was already flush with shale production. The demand shock from Covid meant that a lot more oil was being piped into Cushing than was being brought out. The delivery point quickly filled up, even as producers struggled with decisions to mothball production (shutting down production can cost more than continuing to produce, even at below breakeven per barrel prices).
All that oil, already pumped out of the ground, had to go somewhere; and it just so happened that the somewhere they had to go was landlocked. We know the rest by now, producers started paying other people to take the oil off their hands, but because buyers could not find storage, producers offered more and more to get buyers to buy; and WTI printed a low of -$40, and settled at $-37.
Although, is it still considered “buying” if someone is paying you to take it?
At this point, it must be noted that 2020’s negative WTI episode was not a new phenomena to people involved in the shale market. North Dakota Sour traded below $0, although not by much, in 2016. The reasons then were broadly the same, too much production with no pipeline infrastructure to get the barrels to a broader domestic and/or export market.
What was shocking about WTI, however, was how famous it is. Prior to the American shale revolution, WTI was widely used as a global benchmark for pricing other similar grades of crude. While recent years have seen this role shift more towards Brent (due in part to the same oversupply of shale into landlocked Cushing factor), WTI very much remains in the mainstream consciousness; and seeing it trade so deeply negative made for great headlines if nothing else.
Crazy times, but also somehow logical.
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