How to live in a world that we don’t understand, and enjoy it (Taleb)

N Taleb How to live in a world that we don’t understand, and enjoy it  Goldstone Lecture 2011 (U Penn, Wharton)

Notes from the talk

Taleb returns to his alma mater. This talk supercedes his previous work (e.g. Black Swan). His main points are:

• We don’t have a word for the opposite of fragile.
Fragile systems have small probability of huge negative payoff
Robust systems have consistent payoffs
? has a small probability of a large pay-off
• Fragile systems eventually fail. ? systems eventually come good.
• Financial statistics have a kurtosis that cannot in practice be measured, and tend to hugely under-estimate risk.
Often more than 80% of kurtosis over a few years is contributed by a single (memorable) day.
• We should try to create ? systems.
He calls them convex systems, where the expected return exceeds the return given the expected environment.
Fragile systems are concave, where the expected return is less than the return from the expected situation.
He also talks about ‘creating optionality’.
• He notes an ‘action bias’, where whenever there is a game like the stock market then we want to get involved and win. It may be better not to play.
• He gives some examples.

Taleb is dismissive of economists who talk about Knightian uncertainty, which goes back to Keynes’ Treatise on Probability. Their corresponding story is that:

• Fragile systems are vulnerable to ‘true uncertainty’
• Fragile systems eventually fail
• Practical numeric measures of risk ignore ‘true uncertainty’.
• We should try to create systems that are robust to or exploit true uncertainty.
• Rather than trying to be the best at playing the game, we should try to change the rules of the game or play a ‘higher’ game.
• Keynes gives examples.

The difference is that Taleb implicitly suppose that financial systems etc are stochastic, but have too much kurtosis for us to be able to estimate their parameters. Rare events are regarded as rare events generated stochastically. Keynes (and Whitehead) suppose that it may be possible to approximate such systems by a stochastic model for a while, but the rare events denote a change to a new model, so that – for example – there is not a universal economic theory. Instead, we occasionally have new economics, calling for new stochastic models. Practically, there seems little to choose between them, so far.

From a scientific viewpoint, one can only asses definite stochastic models. Thus, as Keynes and Whitehead note, one can only say that a given model fitted the data up to a certain date, and then it didn’t. The notion that there is a true universal stochastic model is not provable scientifically, but neither is it falsifiable. Hence according to Popper one should not entertain it as a view. This is possibly too harsh on Taleb, but the point is this:

Taleb’s explanation has pedagogic appeal, but this shouldn’t detract from an appreciation of alternative explanations based on non-stochastic uncertainty.

In particular:

• Taleb (in this talk) seems to regard rare crisis as ‘acts of fate’ whereas Keynes regards them as arising from misperceptions on the part of regulators and major ‘players’. This suggests that we might be able to ameliorate them.
• Taleb implicitly uses the language of probability theory, as if this were rational. Yet his argument (like Keynes’) undermines the notion of probability as derived from rational decision theory.
Not playing is better whenever there is Knightian uncertainty.
Maybe we need to be able to talk about systems that thrive on uncertainty, in addition to convex systems.
• Taleb also views the up-side as good fortune, whereas we might view it as an innovation, by whatever combination of luck, inspiration, understanding and hard work.