Confessions of a Fragilista: Talebian Redundancies and Insurance

I’ve been on a Taleb streak this year (here, here and here). Nassim Nicholas Taleb, that is, the options trader-turned-mathematician-turned public intellectual (and I even managed to get myself on his infamous blocklist after arguing back at him). Many years ago, I read Fooled by Randomness but for some reason it didn’t resonate with me and I wasn’t seeing the brilliance.

Last spring, upon reading former poker champion Annie Duke’s Thinking in Bets and physicist Leonard Mlodinow’s The Drunkard’s Walk, I plunged into Taleb land again, voraciously consuming Fooled, The Black Swan and Skin in the Game, followed by Antifragile just a few months ago.

Taleb is a strange creature; vastly productive and incredibly successful, everything he touches does not quite become gold, but surely stirs up controversy. What he’s managed to do in his popular writing (collected in the Incerto series) is to tie almost every aspect of human life into his One Big Idea (think Isaiah Berlin’s hedgehog): the role of randomness, risk and uncertainty in everyday life.

One theme that comes up again and again is the idea of redundancies: having several different and overlapping systems – back-ups to back-ups – that minimize the chance of fatally bad outcomes. The failures of one of those systems will not result in the extremely bad event you’re trying to avoid.

Focusing primarily on survivability – “absorbing barriers” – through the handed-down wisdom of the Ancients and the Classic, the take-away lesson for Taleb in almost all areas of life is overlapping redundancies. Reality is complicated, and the distribution from which events are drawn is not a well-behaved Gaussian normal distribution, but one of thick tails. How thick nobody knows, but wisdom in the presence of absorbing barriers suggest that taking extreme caution is a prudent long-term strategy.

Of course, in the short run, redundancy amounts to “wasted” resources. In chapter 4 of Fooled, Taleb relates a story from his option trading days where a client angrily calling him up about tail-risk insurance he had sold them. The catastrophic event from which the insurance protected had not taken place, and so the client felt cheated. This behavior, Taleb maintains quite correctly, is idiotic. After all, if an insurance company’s clients consist of only soon-to-be claimants, the company won’t exist for long (or it prices insurance at prohibitively high rates, undermining the business model).

Same thing applies for one of his verbose rants about airline “efficiency,” a rather absurd episode of illustrating “asymmetry” – the idea that downside risks are larger than upside gains. Consider a plane departing JFK for London, a trip scheduled to take 7h trip. Some things can happen to make the trip quicker (speedy departure, weather conditions, landing slot available etc), but only marginally; it would, for instance, not be possible to arrive in London after only an hour. In contrast, the asymmetry arises as there are many things that can delay the trip from mere minutes to infinity – again, weather events, mechanical failures, tech or communication problems.

So, when airlines striving to make their services more efficient by minimizing turnaround time – Southwest’s legendary claim to fame – they hit Taleb’s antifragile asymmetry; getting rid of redundant time on the ground, makes the process of on-loading and off-loading passengers fragile. Any little mistake can cause serious delays, delays that accumulate and domino their way through crowded airport networks.

Embracing redundancies would mean having more time in-between flights, with extra planes and extra mechanics and spare parts available at many airports. Clearly, airlines’ already brittle business model would crumble in a heartbeat.

The flipside efficiency is Taleb’s redundancy. Without optimization, we constantly use more than we need, effectively operating as a tax on all activity. Taleb would of course quibble with that, pointing out that the probability distribution of what “we need” must include Black Swan events that standard optimization arguments overlook.

That’s fine if one places as high a value on risks that Taleb does, and indeed they’re voluntarily paid for. If customers wanted to pay triple the money for airfares in order to avoid this or that delay, there is a market for that – it just seems few people value that price over the damage from (low-probability) delays.

Another example is earthquake-proving buildings that Nate Silver discussed in his The Signal and the Noise regarding the Gutenberg-Ritcher law (the reliably inverse relationship between frequency and magnitude of earthquakes). Constructing buildings that can withstand a high-magnitude earthquake, say a one-in-three-hundred-year event is something rich Californians or Japanese can afford – much-less so a poor country like the Philippines. Yes, Taleb correctly argues, the poor country pays its earthquake expenses in heightened risk of devastating damage.

Large redundancies, back-ups to back-ups, are great if you a) can afford them, and b) are risk-averse enough. Judging by his writing, Taleb is – ironically – far out along the right-tail of risk aversion; for most other people, we have more urgent needs to look after. That means occasionally “blowing up” and suffer hours and hours of airline delays or collapsing buildings after an earthquake.

Taleb rarely considers the trade-offs, and the different subjective value scales (or discount rates!) that differ between people. While Taleb may cherish his redundancies, most of us would rather eliminate them for asymmetrically small gains.

Insurance is a relative assessment of price and risks. Keeping a reserve of redundancies are subjective choices, not an objective necessities.

Nightcap

  1. How things fell apart in 20th century Germany Adam Tooze, Financial Times
  2. The world was just an aggregation of nation-states” Branko Milanovic, globalinequality
  3. Godspeed Justin Raimondo, You Brilliant Son of a Bitch Nicky Reid, Counterpunch
  4. The problem is that our own agency is so precious to us” Caleb Scharf, Life Unbounded

Economists, Economic History, and Theory

We can all come up with cringeworthy clichés for why history matters to society at large – as well as policy-makers and perhaps more infuriatingly, to hubris-prone economists:

And we could add the opposite position, where historical analysis is altogether irrelevant for our current ills, where This Time Is completely Different and where we naively disregard all that came before us.

My pushback to these positions is taken right out of Cameron & Neal’s A Concise Economic History of The World and is one of my most cherished intellectual guidelines. The warning appears early (p. 4) and mercilessly:

those who are ignorant of the past are not qualified to generalize about it.

We can also point to some more substantive reasons for why history matters to the present:

  • Discontinuities: by studying longer time period, in many different settings, we get more used to – and more comfortable with – the fact that institutions, routines, traditions and technologies that we take for granted may change. And do change. Sometimes slowly, sometimes frequently.
  • Selection: in combination with emphasizing history to understand the path dependence of development, delving down into economic history ought to strengthen our appreciation for chance and randomness. The history we observed was but one outcome of many that could have happened. The point is neatly captured in an obscure article of one of last year’s Nobel Prize laureates, Paul Romer: “the world as we know it is the result of a long string of chance outcomes.” Appropriately limiting this appreciation for randomness is Matt Ridley’s rejection of the Great Man Theory: a lot of historical innovations seems to have been inevitable (When Edison invented light bulbs, he had some two dozen rivals doing so independently).
  • Check On Hubris: history gives us ample examples of similar events to what we’re experiencing or contemplating in the present. As my Glasgow and Oxford professor Catherine Schenk once remarked in a conference I organized: “if this policy didn’t work in the past, what makes you think it’ll work this time?”

History isn’t only a check on policy-makers, but on ivory-tower economists as well. Browsing through Mattias Blum & Chris Colvin’s An Economist’s Guide to Economic Historypublished last year and has been making some waves since – I’m starting to see why this book is quickly becoming compulsory reading for economists. Describing the book, Colvin writes:

Economics is only as good as its ability to explain the economy. And the economy can only be understood by using economic theory to think about causal connections and underlying social processes. But theory that is untested is bunk. Economic history provides one way to test theory; it forms essential material to making good economic theory.

Fellow Notewriter Vincent Geloso, who has contributed a chapter to the book, described the task of the economic historian in similar terms:

Once the question is asked, the economic historian tries to answer which theory is relevant to the question asked; essentially, the economic historian is secular with respect to theory. The purpose of economic history is thus to find which theories matter the most to a question.

[and which theory] square[s] better with the observed facts.

Using history to debunk commonly held beliefs is a wonderful check on all kinds of hubris and one of my favorite pastimes. Its purpose is not merely to treat history as a laboratory for hypothesis testing, but to illustrate that multitudes of institutional settings may render moot certain relationships that we otherwise take for granted.

Delving down into the world of money and central banks, let me add two more observations supporting my Econ History case.

One chapter in Blum & Colvin’s book, ‘Money And Central Banking’ is written by Prof. John Turner at Queen’s in Belfast (whose writings – full disclosure – has had great influence on my own thinking). Focusing on past monetary disasters and the relationship between the sovereign and the banking system is crucial for economists, Turner writes:

We therefore have a responsibility to ensure that the next generation of economists has a “lest we forget” mentality towards the carnage that can be afflicted upon an economy as a result of monetary disorder.” (p. 69)

This squares off nicely with another brief article that I stumbled across today, by banking historian and LSE Emeritus Professor Charles Goodhart. Lamentably – or perhaps it ought to have been celebratory – Goodhart notes that no monetary regime lasts forever as central banks have for centuries, almost haphazardly, developed their various functions. The history of central banking, Goodhart notes,

can be divided into periods of consensus about the roles and functions of Central Banks, interspersed with periods of uncertainty, often following a crisis, during which Central Banks (CBs) are searching for a new consensus.”

He sketches the pendulum between consensus and uncertainty…goodhart monetary regime changes

…and suddenly the Great Monetary Experiment of today’s central banks seem much less novel!

Whatever happens to follow our current monetary regimes (and Inflation Targeting is due for an update), the student of economic history is superbly situated to make sense of it.

Normas, decisiones y complejidad

Hace pocos días, se publicó en el sitio americanscientist.org un ambicioso artículo sobre el concepto de lo aleatorio. El autor, Scott Aaronson, trataba de elucidar bajo qué criterio podíamos distinguir una serie aleatoria de números de otra serie de números ordenados conforme cierto patrón, difícil de determinar, pero estructurante al fin de un orden en la serie. En otras palabras, si una computadora arrojaba “aleatoriamente” un número “9” y luego otro número “9” y luego otro y otro, ¿estábamos ante el resultado del azar, que se juega en cada nueva jugada, o ante un patrón que podía expresarse en una fórmula? ¿Si de repente apareciera en la serie un número 4, eso confirmaría el azar, o nos indicaría que nos encontramos ante un patrón más complejo?

Aaronson propone en el referido artículo, como criterio identificatorio de un número aleatorio, la característica de no ser susceptible de reducción a un algoritmo más simple. La explicación aparece como plausible y tiene un gran poder de seducción. Sin embargo, desde nuestro punto de vista, tal conceptualización no permite distinguir azar de complejidad. Friedrich A. Hayek se inspiró en Kurt Gödel para proponer, como caracterización de un fenómeno complejo, aquél sobre el que, en atención a la heterogeneidad de sus elementos, ninguna teoría puede ofrecer su descripción completa, es decir, que no puede expresarse en un algoritmo más simple.

La noción de fenómeno complejo tiene sus raíces en el empirismo de David Hume: las relaciones entre los términos (una serie de números, por ejemplo) no se encuentran en los términos mismos, si no que son atribuidas por el sujeto (en nuestro ejemplo, le adjudicamos un patrón a aquella serie de números.) Desde el momento en el que el conocimiento general no proviene de los hechos si no que es atribuido a los mismos, tal conocimiento general no nos permitirá agotar el conocimiento de lo particular. En otras palabras, siempre habrá un elemento empírico en toda teoría.

Para continuar con nuestro ejemplo: podemos enunciar un patrón que explique la sucesión de una serie de números, pero estamos expuestos a que aparezca un nuevo número en la serie que nos obligue a revisar nuestra teoría. Cuando aparece un nuevo acontecimiento que se escapa a nuestras expectativas, lo que hacemos es reajustar la noción de orden que le atribuimos a la realidad. Lo que hace que una serie de acontecimientos configure un orden o estructura, y no sea caótica o aleatoria no es, por consiguiente, que las expectativas en torno a los acontecimientos siempre se cumplan, si no que exista un rango de acontecimientos que nunca se verifique, en otras palabras: que determinadas expectativas sean sistemáticamente frustradas.

Igualmente, la confusión entre azar y complejidad puede ser fecunda y arrojar más luz sobre la naturaleza de la segunda. Por ejemplo, Nicolás Maquiavelo culminaba “El Príncipe” con la afirmación de que la iniciativa era la virtud fundamental del político, ya que la fortuna tendía a favorecer más al arriesgado que al cauto. En términos poblacionales, vemos más hombres de éxito con iniciativa que sin ella ya que, para resultar exitosos, se tuvieron que conyugar dos situaciones: la decisión de asumir riesgos y que la oportunidad favorable efectivamente se haya presentado. En el conjunto de políticos sin éxito encontraremos a los cautos y también a los arriesgados (que no tuvieron suerte). Va de suyo que podemos sustituir “fortuna” por “complejidad” sin perder mucho del sentido de la idea.

Asimismo, The Economist publicó la semana pasada un interesante artículo sobre la relación entre la estructura del azar y laestructura de las decisiones. Todo parece indicar que efectivamente existen buenas y malas rachas, pero ello no se debe al azar si no a la estructura de decisiones que se toman frente a una situación difícil o imposible de comprender. Un jugador tiene a la suerte de su lado cuando, luego de ganar la primera apuesta, en las sucesivas va reduciendo su exposición al riesgo. Correlativamente en este caso, a menores riegos, menores ganancias pero también menores pérdidas, con lo que el resultado neto de todo el conjunto de jugadas es positivo. Paralelamente, si un jugador pierde en su primera apuesta, incrementar el riesgo de las sucesivas con la idea de compensar la primera pérdida sólo lo llevará a la ruina. En síntesis, una muy buena estrategia para lidiar con el riesgo es actuar como un sistema de retroalimentación negativa: a cada desvío del promedio estándar, responder con mayor moderación. Después de todo, la comparación con un sistema de retroalimentación negativa era la caracterización que F. A. Hayek hacía de la función del derecho y de todo sistema normativo en general, aportando mayor estabilidad y mejores resultados netos.

Publicado originariamente en http://www.ihumeblog.blogspot.com.ar , el blog institucional de la Fundación Instituto David Hume (www.ihume.org), de Buenos Aires, Argentina.