Streetwise Professor

May 20, 2020

Whoops! WTI Didn’t Do It Again, or, Lightning Strikes Once

The June 2020 WTI contract expired with a whimper rather than a bang yesterday, thereby not repeating the cluster of the May contract expiry. In contrast to the back-to-back 40 standard deviation moves in April, June prices exhibited little volatility Monday or Tuesday. Moreover, calendar spreads were in a modest contango–in contrast to the galactangos experienced in April, and prices never got within miles of negative territory.

Stronger fundamentals certainly played a role in this uneventful expiry. Glimmers of rebounding demand, and sharp supply reductions, both in the US and internationally, caused a substantial rally in flat prices and tightening of spreads in the first weeks of May. This alleviated fears about exhaustion of storage capacity. Indeed, the last EIA storage number for Cushing showed a draw, and today’s API number suggests an even bigger draw this week. (Though I must say I am skeptical about the forecast power of API numbers.). Also, the number of crude carriers chartered for storage has dropped. (H/T my daughter’s market commentary from yesterday). So the dire fundamental conditions that set the stage for that storm of negativity were not nearly so dire this week.

But remember that fundamentals only set the stage. As I pointed out in my posts in the immediate aftermath of the April chaos, technical factors related to the liquidation of the May contract, arguably manipulative in nature, the ultimate cause of the huge price drop on the penultimate trading day, and the almost equally large rebound on the expiry day.

The CFTC read the riot act in a letter to exchanges, clearinghouses, and FCMs last week. No doubt the CME, despite it’s Frank Drebin-like “move on, nothing to see here” response to the May expiry monitored the June expiration closely, and put a lot of pressure on those with open short positions to bid the market aggressively (e.g., bid at reasonable differentials to Brent futures and cash market prices). A combination of that pressure, plus the self-protective measures of market participants who didn’t want to get caught in another catastrophe, clearly led to earlier liquidations: open interest going into the last couple of days was well below the level at a comparable date in the May.

So fundamentals, plus everyone being on their best behavior, prevented a recurrence of the May fiasco.

It should be noted that as bad as April 20 was (and April 21, too), the carnage was not contained to those days, and the May contract alone. The negative price shock, and its potentially disastrous consequences for “fully collateralized” long-only funds, like the USO, led to a substantial early rolls of long positions in the June during the last days of April. Given the already thin liquidity in the market, these rolls caused big movements in calendar spreads–movements that have been completely reversed. On 27 April, the MN0 spread was -$14.45: it went off the board at a 54 cent backwardation. Yes, fundamentals were a major driver of that tightening, but the early roll in the US (and some other funds) triggered by the May expiration clearly exacerbated the contango. Collateral damage, as it were.

What is the takeaway from all this? Well, I think the major takeaway is not to overgeneralize from what happened on 20-21 April. The underlying fundamentals were truly exceptional (unprecedented, really)–and hopefully the likelihood of a repeat of those is vanishingly small. Moreover, the CME should be on alert for any future liquidation-related game playing, and market players will no doubt be more cautious in their approach to expiration. It would definitely be overlearning from the episode to draw expansive conclusions about the overall viability of the WTI contract, or its basic delivery mechanism.

That mechanism is supported by abundant physical supplies and connections to diverse production and consumption regions. Indeed, this was a situation where the problem was extremely abundant supply–which is an extreme rarity in physical commodity futures markets. Other contracts (Brent in particular) have chronic problems with inadequate and declining supply. As for WTI being “landlocked,” er, there are pipelines connecting Cushing to the Gulf, and WTI from Cushing has been exported around the world in recent years. With the marginal barrel going for export, seaborne crude prices drive WTI. With a better-monitored and managed liquidation process, especially in extraordinary circumstances, the WTI delivery mechanism is pretty good. And I say that as someone who has studied delivery mechanisms for around 30 years, and has designed or consulted on the design of these contracts.

May 14, 2020

Strange New Respect

Filed under: Climate Change,CoronaCrisis,Economics,Energy,Politics,Regulation,Tesla — cpirrong @ 5:50 pm

The past few weeks have brought pleasant surprises from people whom I usually disagree with and/or dislike.

For one, Michael Moore, the executive producer of Planet of the Humans. Moore does not appear on camera: that falls to Jeff Gibbs and (producer) Ozzie Zehner. The main virtue of the film is its evisceration of “green energy,” including wind and solar. It notes repeatedly that the unreliability of these sources of power makes them dependent on fossil fuel generation, and in some cases results in the consumption of more fossil fuels than would be the case if the renewables did not exist at all. Further, it points out-vividly-the dirty processes involved with creating wind and solar, most notably mining. The issues of disposing of derelict wind and solar facilities are touched on too, though that could have been beefed up some.

If you know about wind and solar, these things are hardly news to you. But for environmentalists to acknowledge that reality, and criticize green icons for perpetrating frauds in promoting these wildly inefficient forms of energy, is news.

The most important part of the film is its brutal look at biomass. It makes two points. First, that although green power advocates usually talk about wind and solar, much of the actual “renewable” energy is produced by biomass, e.g., burning woodchips. In other words, it exposes the bait-and-switch huckersterism behind a lot of green energy promotion. You thought you were getting windmills? Sucker: you’re getting plants that burn down forests. You fucked up! You trusted us!

Second, that biomass is hardly renewable (hence the quote marks above), and results in huge environmental damage. Yes, trees can regrow, but not as fast as biomass plants burn them. Moreover, the destruction of forests is truly devastating to wildlife and to irreplaceable habitats, and to the ostensible purpose of renewables–reduction of CO2.

The film also points out the massive corporate involvement in green energy, and this represents its weakest point. Corporations, like bank robbers, go where the money is. But that begs the question: Why is there money in horribly inefficient renewables? Answer: Because of government subsidies.

Alas, the movie only touches briefly on this reality. Perhaps that is a bridge too far for socialists like Moore. But he (and Gibbs and Zehner) really want to stop what they rightly view as the environmental and economic folly of renewables, they have to turn off the money tap. That requires attacking the government-corporate-environmentalist iron triangle on all three sides, not just two.

I am not a believer in the underlying premise of the movie, viz., that there are too many people consuming too much stuff, and if we don’t reduce people and how much they consume, the planet will collapse. That’s a dubious neo-Malthusian mindset. But put that aside. It’s a great thing that even hard core environmentalists call bull on the monstrosity that is green/renewable energy, and point out the hypocrisy and fundamental dishonesty of those who hype it.

My second candidate is long-time target Elon Musk. He has come out as a vocal opponent to lockdowns, and a vocal advocate for liberty.

Now I know that Elon is talking his book. Especially with competitors starting up their plants in the Midwest, the lockdown in California that has idled Musk’s Fremont manufacturing facility is costing Tesla money. But whatever. The point is that he is forcefully pointing out the huge economic costs of lockdowns, and their immense detrimental impact on personal liberty earns him some newfound respect, strange or otherwise.

Lastly, Angela Merkel. She has taken a much more balanced approach to Covid-19 than most other national leaders. Perhaps most importantly, she has clearly been trying to navigate the tradeoff between health, economic well-being, and liberty. Rather than moving the goalposts when previous criteria for evaluating lockdowns had been met, when it became clear that the epidemic was not as severe in Germany as had been feared, and that the economic consequences were huge, and that children were neither potential sufferers or spreaders, she pivoted to reopening quickly and pretty rationally.

The same cannot be said in other major countries, including the UK and France as notable examples. She comes off well in comparison to Trump, although the comparison is not completely fair. Trump only has the bully pulpit to work with, for one thing: actual power is wielded by governors. But Trump’s use of the bully pulpit has been poor. Moreover, he has deferred far too much to execrable “experts,” most notably the slippery Dr. Fauci, who has been on the opposite sides of every policy decision (Masks? Yes! Masks? No! Crisis? Yes! Crisis? No!), is utterly incapable of and in fact disdainful of balancing health vs. economics and liberty, and who brings to the table a record of failure that Neil Ferguson could envy, for its duration if nothing else. The Peter Principle personified: he is clearly at the level of his incompetence, and due to the perversity of government, has remained at that level for decades.

Merkel’s performance is particulary outstanding when compared to those who wield the real power in the current crisis, American governors, especially those like Whittmer, Pritzker, Evers, Walz, Brown, Wolf, Cuomo, Murphy, Northam, and Newsom. These people are goalpost movers par excellence, and quite clearly find the unfettered exercise of power to be orgasmic.

It is embarrassing in the extreme to see the Germans–the Germans–be far more solicitous of freedom and choice than elected American officials, who seem to treat freedom–including the freedom to earn a livelihood–as an outrageous intrusion on their power and amour-propre.

Will this represent the new normal? Will SWP props for Moore, Merkel, and Musk become routine in the post- (hopefully) Covid era? I doubt it, but for today, I’m happy to give credit where credit is due.

May 11, 2020

Imperial Should Have Called Winston Wolf

Filed under: CoronaCrisis,Economics,Politics,Regulation — cpirrong @ 3:09 pm

In the film Pulp Fiction, moronic hoodlums Jules (Samuel L. Jackson) and Vincent (John Travolta) pick up a guy who had stolen a briefcase from the back of their boss Marcellus Wallace’s car. While driving him away, Vincent accidentally shoots him, leaving the back of the car splattered with blood and brains. In a panic, they drive to friend Jimmy Dimmick’s (Quentin Tarantino’s) house. Dimmick tells them his wife will be home in an hour and they can’t stay. In a panic they call Wallace, who calls in Winston Wolf. Wolf says: “It’s an hour away. I’ll be there in 10 minutes.” In 9 minutes and 37 seconds, Wolf’s car squeals to a halt in front of Jimmy’s house. Wolf rings the doorbell, and when Jimmy answers, Wolf says: “I’m Winston Wolf. I solve problems.” Within 40 minutes, Wolf solves Jules’ and Vincent’s problem. The car is cleaned up with the body is in the trunk, ready to be driven to the wrecking yard to be crushed.

The Imperial team that relied on Microsoft/Github to fix its code should have called Winston Wolf instead, because MS/Github left behind some rather messy evidence. “Sue Denim,” who wrote the code analysis I linked to yesterday, has a follow up describing what Not Winston Wolf left behind:

The hidden history. Someone realised they could unexpectedly recover parts of the deleted history from GitHub, meaning we now have an audit log of changes dating back to April 1st. This is still not exactly the original code Ferguson ran, but it’s significantly closer.

Sadly it shows that Imperial have been making some false statements.

I don’t quite know what to make of this. Originally I thought these claims were a result of the academics not understanding the tools they’re working with, but the Microsoft employees helping them are actually employees of a recently acquired company: GitHub. GitHub is the service they’re using to distribute the source code and files. To defend this I’d have to argue that GitHub employees don’t understand how to use GitHub, which is implausible.

I don’t think anyone involved here has any ill intent, but it seems via a chain of innocent yet compounding errors – likely trying to avoid exactly the kind of peer review they’re now getting – they have ended up making false claims in public about their work.

My favorite one is “a fix for a critical error in the random number generator.” In 2020? WTF? I remember reading in 1987 in the book Numerical Recipes by  William H. Press, Saul A. Teukolsky, William T. Vetterling and Brian P. Flannery a statement to the effect that libraries could be filled with papers based on faulty random number generation. (I’d give you the exact quote, but the first edition that I used is in my office which I cannot access right now. Why is that, I wonder?). And they were using a defective RNG 33 years later? Really?

“Algorithmic errors” is another eye popper. The algorithms weren’t doing what they were supposed to?

Read the rest. And maybe you’ll conclude that this was a mess that even Winston Wolf could have cleaned up in 40 days, let alone 40 minutes.

May 10, 2020

Code Violation: Other Than That, How Was the Play, Mrs. Lincoln?

Filed under: CoronaCrisis,Economics,Politics,Regulation — cpirrong @ 3:03 pm

By far the most important model in the world has been the Imperial College epidemiological model. Largely on the basis of the predictions of this model, nations have been locked down. The UK had been planning to follow a strategy very similar to Sweden’s until the Imperial model stampeded the media, and then the government, into a panic. Imperial predictions regarding the US also contributed to the panicdemic in the US.

These predictions have proved to be farcically wrong, with deaths tolls exaggerated by one and perhaps two orders of magnitude.

Models only become science when tested against data/experiment. By that standard, the Imperial College model failed spectacularly.

Whoops! What’s a few trillions of dollars, right?

I was suspicious of this model from the first. Not only because of its doomsday predictions and the failures of previous models produced by Imperial and the leader of its team, Neil Ferguson. But because of my general skepticism about big models (as @soncharm used to say, “all large calculations are wrong”), and most importantly, because Imperial failed to disclose its code. That is a HUGE red flag. Why were they hiding?

And how right that was. A version of the code has been released, and it is a hot mess. It has more bugs than east Africa does right now.

This is one code review. Biggest take away: due to bugs in the code, the model results are not reproducible. The code itself introduces random variation in the model. That means that runs with the same inputs generate different outputs.

Are you fucking kidding me?

Reproducibility is the essence of science. A model whose predictions can not be reproduced, let alone empirical results based on that model, is so much crap. It is the antithesis of science.

After tweeting about the code review article linked above, I received feedback from other individuals with domain expertise who had reviewed the code. They concur, and if anything, the article understates the problems.

Here’s one article by an interlocutor:

The Covid-19 function variations aren’t stochastic. They’re a bug caused by poor management of threads in the code. This causes a random variation, so multiple runs give different results. The response from the team at Imperial is that they run it multiple times and take an average. But this is wrong. Because the results should be identical each time. Including the buggy results as well as the correct ones means that the results are an average of the correct and the buggy ones. And so wouldn’t match the expected results if you did the same calculation by hand.

As an aside, we can’t even do the calculations by hand, because there is no specification for the function, so whether the code is even doing what it is supposed to do is impossible to tell. We should be able to take the specification and write our own tests and check the results. Without that, the code is worthless.

I repeat: “the code is worthless.”

Another correspondent confirmed the evaluations of the bugginess of the code, and added an important detail about the underlying model itself:

I spent 3 days reviewing his code last week. It’s an ugly mess of thousands of lines of C (not C++). There are hundreds of input parameters (not counting the fact it models population density to 1km x 1km cells) and 4 different infection mechanisms. It made me feel quite ill.

Hundreds of input parameters–another huge red flag. I replied:

How do you estimate 100s of parameters? Sounds like a climate model . . . .

The response:

Yes. It shares the exact same philosophy as a GCM – model everything, but badly.

I recalled a saying of von Neumann: “With four parameters I can fit an elephant, with five I can make him wiggle his trunk.” Any highly parameterized model is IMMEDIATELY suspect. With so many parameters–hundreds!–overfitting is a massive problem. Moreover, you are highly unlikely to have the data to estimate these parameters, so some are inevitably set a priori. This high dimensionality means that you have no clue whatsoever what is driving your results.

This relates to another comment:

No discussion of comparative statics.

So again, you have no idea what is driving the results, and how changes in the inputs or parameters will change predictions. So how do you use such a model to devise policies, which is inherently an exercise in comparative statics? So as not to leave you in suspense: YOU CAN’T.

This is particularly damning:

And also the time resolution. The infection model time steps are 6 hours. I think these models are designed more for CYA. It’s bottom-up micro-modelling which is easier to explain and justify to politicos than a more physically realistic macro level model with fewer parameters.

To summarize: these models are absolute crap. Bad code. Bad methodology. Farcical results.

Other than that, how was the play, Mrs. Lincoln?

But it gets better!

The code that was reviewed in the first-linked article . . . had been cleaned up! It’s not the actual code used to make the original predictions. Instead, people from Microsoft spent a month trying to fix it–and it was still as buggy as Kenya. (I note in passing that Bill Gates is a major encourager of panic and lockdown, so the participation of a Microsoft team here is quite telling.)

The code was originally in C, and then upgraded to C++. Well, it could be worse. It could have been Cobol or Fortran–though one of those reviewing the code suggested: “Much of the code consists of formulas for which no purpose is given. John Carmack (a legendary video-game programmer) surmised that some of the code might have been automatically translated from FORTRAN some years ago.”

All in all, this appears to be the epitome of bad modeling and coding practice. Code that grew like weeds over years. Code lacking adequate documentation and version control. Code based on overcomplicated and essentially untestable models.

But it gets even better! The leader of the Imperial team, the aforementioned Ferguson, was caught with his pants down–literally–canoodling with his (married) girlfriend in violation of the lockdown rules for which HE was largely responsible. This story gave versimilitude to my tweet of several days before that story broke:

It would be funny, if the cost–in lives and livelihoods irreparably damaged, and in lives lost–weren’t so huge.

And on such completely defective foundations policy castles have been built. Policies that have turned the world upside down.

Of course I blame Ferguson and Imperial. But the UK government also deserves severe criticism. How could they spend vast sums on a model, and base policies on a model, that was fundamentally and irretrievably flawed? How could they permit Imperial to make its Wizard of Oz pronouncements without requiring a release of the code that would allow knowledgeable people to look behind the curtain? They should have had experienced coders and software engineers and modelers go over this with a fine-tooth comb. But they didn’t. They accepted the authority of the Pants-less Wizard.

And how could American policymakers base any decision–even in the slightest–on the basis of a pig in a poke? (And saying that it is as ugly as a pig is a grave insult to pigs.)

If this doesn’t make you angry, you are incapable of anger. Or you are an idiot. There is no third choice.

May 2, 2020

You Will Respect My Authoritah: Destroying the Healthcare System to Save It

Filed under: CoronaCrisis,Economics,Politics — cpirrong @ 9:55 am

I think it’s fair to say that I was one of the early lockdown (AKA Karentine) skeptics. In one post (19 March) I asked rhetorically whether we were destroying society to save it. Evidence accumulates daily that the lockdowns were indeed wildly costly compared to the benefits, and in the case of the healthcare industry in the US in particular, it is only slightly rhetorically excessive to say that yes, we destroyed it to save it.

Recall that the primary justification for lockdowns was to prevent the healthcare system from being overwhelmed. With a few very localized (and highly publicized) exceptions, it never was, nor was it in any danger of being so. (And for those who claim this was the result of the lockdowns, there is mounting empirical evidence both within the US and internationally that variations in lockdown policy in terms of stringency and timing have trivial impacts on the trajectories of the epidemic.)

But to “save” the healthcare system, the non-coronavirus-targeted system was almost completely shut down. One major effect of this has been financial: hospital systems and individual physicians and nurses have been financially devastated. I can’t put my hands on the citation right now, but I read that something like 40 percent of the large decline in US GDP in March was due to reduced output in the healthcare sector.*

And there will be severe health consequences as well. “Elective” procedures are not unnecessary ones: avoiding or even delaying treatment of many conditions increases the risk of death, and the number of deaths. Such avoidance or delays can also lead to serious declines in quality of life.

These effects are part of the “unseen” that I mentioned in my earlier post. People will die because of the lockdowns, but there are no Lockdown Death Trackers. And those responsible for the lockdowns, or for cheerleading for them (which includes most major media outlets), have absolutely no incentive to create them. Because you can’t handle the truth, apparently.

It is sickly ironic (deliberate word choice) that many of the most strident defenders of lockdowns were, in normal times, almost equally strident in their insistence that the lack of adequate government provided or funded health care caused people to receive too little care, thereby leading to increased mortality and greater incidence of debilitating ailments. And no, don’t bother trying to reconcile these positions: it’s impossible.

I also note that the persistence of the lockdowns, especially in places like California, Michigan, Illinois, Wisconsin, and Minnesota gives the lie to the “flattening the curve to save the healthcare system” justification for them. In California in particular, but also in the other states (outside of perhaps Detroit, which has its own pathologies decades in the making), there has been a yawning gap between ICU capacity and utilization. Yet despite these what should be welcome data, and increasingly restive citizenries in these states, their governors refuse even to countenance relaxation. So it wasn’t really about the healthcare system, was it? Or if it was, it’s now about something else.

And what is that something else? Power.

Gavin Newsom’s tirade against those who dared to go to beaches is a particularly odious example. He basically treats the 40 million people of his state as would a control-freak father incensed at the audacity of his children in defying his authority. This is not a statewide lockdown. This is a statewide grounding–and if you break the rules again, sonnie, the grounding will be extended! Indefinitely! Not because it has any public benefit. But because you dared to challenge Governor Cartman’s–excuse me, Governor Newsom’s–authoritah.

And, of course, Google and Facebook in particular are willing–nay, eager–accessories to these mass deprivations of rights. They have become censors in chief, extirpating (sorry, “deplatforming” and “removing” are too weak) content that crosses the authoritahs’ official line.

The logic behind the lockdowns was always dubious, and they were NEVER based on reliable data. (And don’t get me started on the models.). But whatever logic there was, it is non-existent now. They have become self-perpetuating. Or rather, they are being perpetuated in order to perpetuate the powers seized by governors and local officials.

And if it destroys the healthcare system (not to mention the livelihoods of tens of millions of Americans)? Well, as a man who is apparently the role model for many governors once supposedly said, you can’t make an omelet without breaking some eggs.

*Here are the data. (See p. 9.) GDP fell $234b in the first quarter. Since GDP was rising rapidly–about 3.5 percent annualized–in Q4, and the lockdowns didn’t kick in until March, virtually all of this likely occurred in the last half of March. A pretty staggering decline in a few weeks.

Expenditures on health care fell $110b, almost exactly the 40 percent I mentioned in the original post. This contrasts to a $27b increase over Q4.

Powered by WordPress