Predicting phase transitions

I am not sure the modelling methodology described in this article is quite as good as the title suggests…

“Chaos Researchers Can Now Predict Perilous Points of No Return”

… but it would be very interesting if it lives up to the claims made in the article. It is a quick read and the subject matter seems worth keeping an eye on.

Here are two short extracts to give you a flavour of the claims made

A custom-built machine learning algorithm can predict when a complex system is about to switch to a wildly different mode of behavior.

In a series of recent papers, researchers have shown that machine learning algorithms can predict tipping-point transitions in archetypal examples of such “nonstationary” systems, as well as features of their behavior after they’ve tipped. The surprisingly powerful new techniques could one day find applications in climate science, ecology, epidemiology and many other fields.

Tony – From the Outside

Red flags in financial services

Nice podcast from Odd Lots discussing the Wirecard fraud. Lots of insights but my favourite is to be wary when you see a financial services company exhibit high growth while maintaining profitability.

There may be exceptions to the rule but that is not how the financial services market normally works.

podcasts.apple.com/au/podcast/odd-lots/id1056200096

Tony — From the Outside

What Michael Lewis loves about experts

This link takes you to the last of a 7 episode podcast Michael Lewis has done on the role of experts

podcasts.apple.com/au/podcast/against-the-rules-with-michael-lewis/id1455379351

The whole series is highly recommended but I especially like this quote in which he attempts to sum up the series

“Life eventually humbles us all. What I love about experts, the best of them anyway, is that they get to their humility early, they have to, it’s part of who they are, it’s necessary for what they are doing. They set out to get to the bottom of something that has no bottom, and so they are reminded, constantly, of what they don’t know. They move through the world focussed not on what they know but on what they might find out.”

In that spirit, let me know what I am missing

Tony – From the Outside

“Safe” assets can be risky – check your assumptions

Anyone moderately familiar with crypto assets is no doubt aware that the Terra stablecoin has been experiencing problems with its algorithmic smart contract controlled peg mechanism. There are lots of lessons here I am but I think Matt Levine flags one of the more interesting ones in his “Money Stuff” column (13 May 2022).

Safe assets are much riskier than risky ones.

Matt goes on to expand on why this is so …

This is I think the deep lesson of the 2008 financial crisis, and crypto loves re-learning the lessons of traditional finance. Systemic risks live in safe assets. Equity-like assets — tech stocks, Luna, Bitcoin — are risky, and everyone knows they’re risky, and everyone accepts the risk. If your stocks or Bitcoin go down by 20% you are sad, but you are not that surprised. And so most people arrange their lives in such a way that, if their stocks or Bitcoin go down by 20%, they are not ruined.

On the other hand safe assets — AAA mortgage securities, bank deposits, stablecoins — are not supposed to be risky, and people rely on them being worth what they say they’re worth, and when people lose even a little bit of confidence in them they crack completely. Bitcoin is valuable at $50,000 and somewhat less valuable at $40,000. A stablecoin is valuable at $1.00 and worthless at $0.98. If it hits $0.98 it might as well go to zero. And now it might!

The takeaway for me is to once again highlight the way in which supposedly safe, “no questions need be asked”, assets can sometimes be worse than assets we know are risky due to the potential for them to quickly flip into something for which there is no liquidity, just a path to increasingly large price falls. This is a theme that I regularly hammer (so apologies if you are tired of it) but still for me one of the more important principles in finance (right up there with “no free lunch”).

Tony – From the Outside

Never let the facts stand in the way of a good story

Shout out to Tim Harford for this introduction to the study of how, in his words, ignorance can be deliberately produced. The technical term “agnatology” is I suspect unlikely to catch on but the underlying message is one worth understanding. At a minimum it is a handy addition to your Scrabble dictionary.

The article was originally published in March 2017 but I only came across it recently via this podcast interview Harford did with Cardiff Garcia on “The New Bazaar”. The context in 2017 was the successful campaign for the US presidency that Donald Trump ran during 2016 with a bit of Brexit thrown in but this is a challenge that is not going away anytime soon.

Harford notes that it is tempting to think that the answer to the challenge posed by what has come to be known as a post truth society lies in a better process to establish the facts

The instinctive reaction from those of us who still care about the truth — journalists, academics and many ordinary citizens — has been to double down on the facts.

He affirms the need to have some agreement on how we distinguish facts from opinions and assertions but he cautions that this is unlikely to solve the problem. He cites the tobacco industry response to the early evidence that smoking causes cancer to illustrate why facts alone are not enough.

A good place to start is by delving into why facts alone are not enough – a few extracts from the article hopefully capture the main lessons

Doubt is usually not hard to produce, and facts alone aren’t enough to dispel it. We should have learnt this lesson already; now we’re going to have to learn it all over again…

Tempting as it is to fight lies with facts, there are three problems with that strategy…

The first is that a simple untruth can beat off a complicated set of facts simply by being easier to understand and remember. When doubt prevails, people will often end up believing whatever sticks in the mind…

There’s a second reason why facts don’t seem to have the traction that one might hope. Facts can be boring. The world is full of things to pay attention to, from reality TV to your argumentative children, from a friend’s Instagram to a tax bill. Why bother with anything so tedious as facts?…

In the war of ideas, boredom and distraction are powerful weapons.
The endgame of these distractions is that matters of vital importance become too boring to bother reporting…

There’s a final problem with trying to persuade people by giving them facts: the truth can feel threatening, and threatening people tends to backfire. “People respond in the opposite direction,” says Jason Reifler, a political scientist at Exeter University. This “backfire effect” is now the focus of several researchers, including Reifler and his colleague Brendan Nyhan of Dartmouth…

The problem here is that while we like to think of ourselves as rational beings, our rationality didn’t just evolve to solve practical problems, such as building an elephant trap, but to navigate social situations. We need to keep others on our side. Practical reasoning is often less about figuring out what’s true, and more about staying in the right tribe…

We see what we want to see — and we reject the facts that threaten our sense of who we are…

When we reach the conclusion that we want to reach, we’re engaging in “motivated reasoning”…

Even in a debate polluted by motivated reasoning, one might expect that facts will help. Not necessarily: when we hear facts that challenge us, we selectively amplify what suits us, ignore what does not, and reinterpret whatever we can. More facts mean more grist to the motivated reasoning mill. The French dramatist Molière once wrote: “A learned fool is more foolish than an ignorant one.” Modern social science agrees…

When people are seeking the truth, facts help. But when people are selectively reasoning about their political identity, the facts can backfire.

So what are we to do?

Harford cites a study that explores the value of scientific curiosity

What Kahan and his colleagues found, to their surprise, was that while politically motivated reasoning trumps scientific knowledge, “politically motivated reasoning . . . appears to be negated by science curiosity”. Scientifically literate people, remember, were more likely to be polarised in their answers to politically charged scientific questions. But scientifically curious people were not. Curiosity brought people together in a way that mere facts did not. The researchers muse that curious people have an extra reason to seek out the facts: “To experience the pleasure of contemplating surprising insights into how the world works.”

It is of course entirely possible that Tim Harford’s assessment is just calling to my own bias. I will admit that one the things that I always looked for when hiring, or working, with people was curiosity. These people are surprisingly rare but (IMHO) worth their weight in gold. An intellectually curious mind makes up for a lot of other areas where the person might not be perfect in terms of skills or experience. The general point (I think) also ties to the often cited problem that people with lots of knowledge can sometimes be prone to not being so street smart. Nassim Taleb makes this argument in nearly everything he writes.

So Tim Harford might not be offering the entire answer but I think his article is worth reading on two counts

  • Firstly as a cautionary tale against expecting that all debates and disputes can be resolved by simply establishing the “facts”
  • Secondly as a reminder of the power of a curious mind and the value of the never-ending search for “what am I missing?”

Let me know what I am missing

Tony – From the Outside

Misunderstanding Narratives: The Hero’s Journey – The Big Picture

Joseph Campbell’s “The Hero with a Thousand Faces” is a great book. It offers insights into some deep ideas about how the world does (or should) work that have influenced a wide variety of people including George Lucas and Ray Dalio and was included in Time magazine’s list of the top 100 books.

Barry Ritholz did a short, but insightful, post here where he reminds us that the timeless appeal of the narrative that Campbell explores can also mislead us.

Our narrative bias for compelling stories can prevent us from seeing the forest for trees. Dramatic tales with clearly delineated Good & Evil are more memorable and emotionally resonant than dry data and tedious facts. Try as you might, finding a singular cause of some terrible economic outcome is an exercise in futility. Instead, you will find a long history of political, economic, psychological, and (occasionally) irrational drivers that eventually led to some disaster.

We look for the spark that ignites the room full of hydrogen, instead of 1,000 other factors that created the conditions precedent. You can find example after example of disasters widely thought of as “single event causes;” upon closer examination, they are revealed as the result of far more complex circumstances and countless interactions

https://ritholtz.com/2021/09/misunderstanding-narratives-the-heros-journey/

This for me is an insight that rings very true but is often forgotten to feed our appetite for reducing complex stories to simple morality plays. I like the stories as much as the next person but the downside is that the simple appealing story distracts us from understanding the route causes of why things like the GFC happened and leave us exposed to the risk that they just keep repeating in different forms.

Tony – From the Outside

Andrew Haldane

Claire Jones writing for the Financial Times Alphaville column confesses a fondness for the speeches of Andrew Haldane (departing chief economist at the Bank of England) . She offered a selection of favourites (you can access her column by signing up to Alphaville if you are not an FT subscriber).

I also rate pretty much everything he writes as worth reading often more than once to reflect on the issues he raises. To her top three Haldane speeches, I will add one he did in 2016 titled “The Great Divide” which explored the gap between the way banks perceive themselves and how they are perceived by the community.

Tony – From the Outside

What Can We Learn from a Big Boat Stuck in a Canal?

Interesting post by Matt Stoller on the broader policy issues associated with the current problem in the Sues Canal.

Here is a short extract capturing the main idea …

“Industrial crashes, in other words, are happening in unpredictable ways throughout the economy, shutting down important production systems in semi-random fashion. Such collapses were relatively rare prior to the 1990s. But industrial crashes were built into the nature of our post-1990s production system, which prioritizes efficiency over resiliency. Just as ships like the Ever Given are bigger and more efficient, they are also far riskier. And this tolerance for risk is a pattern reproducing itself far beyond the shipping industry; we’ve off shored production and then consolidated that production in lots of industries, like semiconductors, pharmaceutical precursors, vitamin C, and even book printing.

What is new isn’t the vulnerability of the Suez Canal as a chokepoint, it’s that we’ve intentionally created lots of other artificial chokepoints. And since our production systems have little fat, these systems are tightly coupled, meaning a shortage in one area cascades throughout the global economy, costing us time, money, and lives.”

Irrespective of whether you agree with the solutions he proposes, I think the point he makes (i.e. the tension between efficiency and resilience and the systemic problem with systems that are “tightly coupled”) is a very real issue. We saw this play out in the financial system in 2008 and we saw it play out in global supply chains in 2020. There are differing views on whether the measures have gone far enough but the financial system has been substantially re-engineered to make it more resilient. It remains to be seen how global supply chains will evolve in response to the problems experienced.

Link to the post here

https://mattstoller.substack.com/p/what-we-can-learn-from-a-big-boat

Tony – From the Outside

In Search of a Post-Pandemic Modeling Paradigm – Risk Weighted

Nice post from Tony Hughes discussing the difference between modelling intended to forecast a most likely outcome and modelling tail risk …

“A forecasting mindset yields very tight models, whereas a tail risk mindset demands a far more liberal approach to model specification.”

— Read on riskweighted.com/2021/03/03/in-search-of-a-post-pandemic-modeling-paradigm/