Risk, models, intelligence – 1c or should that be 2c, or 3a, or something different

Will do a more detailed post tonight – was thinking about this whilst out on a run this morning. Robert Merton made some interesting points in a recent lecture at MIT

“Things are not conceptually out of control. This is not some mystery black swan that we don’t understand how it could happen and we have to rewrite all the paradigms because all the modelling is wrong…. There are plenty of bad and incompetent people…but if there are well meaning, ethical people, there is still a structural problem…If we do 100 innovations…lucky if 2 of them are successful so not feasible to produce a complete infrastructure for every innovation in advance or whilst simultaneously creating them…Its a trade-off, judgement…Models are always incomplete descriptions of complex reality.The need for financial engineering is going up, not down. 600 trillion of derivatives are not going away – its like saying we’re going to get rid of cars.”1

The majority of financial corporations (and people employed in academic/corporate economic roles) are dependent on the existence of risk. If we know what is going to happen in advance with an organization’s performance then there is very little opportunity to ‘get ahead of the competition’ and a better return on an investment, because if we know, the chances are that everyone else either knows – or now through the web, will catch up very quickly. If there is no risk at a micro, human level, that will not be particularly satisfying (less brain activity?) and at a more macro level, financial companies cannot offer anything competitive or different to their potential investors.

I can’t remember who said it (possibly Warren Buffett?) but you can hear people say – only invest in something that you can sleep at night about…or words to that effect. Without technology we know that if there is more than one option for something, as our options increase, so does our uncertainty of the outcome of an event:

“If risk taking where exclusively of the nature of a known chance or mathematical probability, there could be no reward of risk-taking, the fact of risk could exert no considerable influence on the distribution of income in any way…the existence of a problem of knowledge depends on the future being different from the past, while the possibility of the solution of the problem depends on the future being like the past.”2

As financial theories have advanced (?) over the last century or so with the increase of investment and insurance options, they have all offered different analyses of risk and how to manage it – i.e. if you are uncertain about the particular performance of a stock from one company – you think it might do particularly well or badly at a specific time of the year, what can you do to make sure you don’t lose (loss aversion in a future post) too much or get a better overall return? For example

• hedging – by spreading your options wider with different company stocks that you are more certain will perform better during the period that you were unsure about with the initial company,
• or a contract – that you are unsure about the outcome but you will take a chance with a guess at a return that you feel comfortable with
• insurance – if you think that you are not going to get a return, take an insurance option that will provide a return in the event of a company not being able to make payment

Technologies including use of spreadsheets, simulations have been used as human decision makers are unable to process these levels of complexity in order to understand about the depth and different types of uncertainties that can exist when making decisions about what and how to invest. Will try and look later today at whether it could be a models problem (in that we have used models to explain everything that is happening without looking at variables and randomness that a model might not take account of), a models comprehension problem (we do not understand what has happened in the calculation so make different assumptions based on the results we are viewing), a complacency about the ability of technologies to produce accurate modelling.

1. Merton R, (2009) Observations on the Science of Finance in the Practice of Finance, MIT World, available at: http://mitworld.mit.edu/video/659
2. Knight  F, (1921) Risk, Uncertainty and Profit, Library of Economics and Liberty, available at: http://econlib.org/library/Knight/knRUPCover.html