Complexity, risk, uncertainty and change


image

Business management, particularly for those intent upon ‘change’ or responsible for managing exposures, needs a rigorous, objective, measurement of the endogenous properties (complexity) that enables the functionality from which (through interactions with exogenous parties) the business generates the revenues that sustain it in changing and turbulent economic times.

“Complexity increases cost and decreases flexibility — often in unforeseen ways — and also tends to decrease stability,”….

Peter Leukert, CIO of Commerzbank

It is the number, nature and integrity of dynamic, multi-scalar, interactions that are the sources of strength (enabling performance greater than the sum of the parts). The ability to distinguish and respond to ‘signals’, that maintain the variety, effectiveness and agility of the complex system, from the ‘noise’ of flawed metrics, self-serving culture, hierarchical structure (silos), skewed incentives – of an unsustainable, failed or failing, model (reliant upon  assumption, reflexive, subjective, statistical analysis and prediction) that has its foundation in flawed (linear) economic thinking.

We won’t get different or better answers while we keep on asking the same questions.

For meaningful change to occur and to be sustained requires a rigorous justification, sufficient to counter financial projections that satisfy the goals of C-level short-termism that are detrimental to the stability and long term health of the business.

Read more of this post

Naive Intervention – Part 1: From Antifragile to Models Behaving Badly


Max’s blogs are consistently, both thoughtful and thought-provoking…

Not all science suffers from naive intervention.

What physicists do differently to economists is that they learn from nature. They observe and measure and then a hypotheses is turned into a theory and then a model. It works when it predicts. In economics and business naive interventionists build a model and then turn it into a religion. There is neither proof nor validation and at best there is anecdotal evidence. But economy is a social science and not physics. Social systems are dealt with through biology. Theories of economy must follow the same natural dynamics of complexity that drive all biological systems. A biologist like E.O. Wilson can teach us more about economy than any theoretical economist can. Wilson said that Karl Marx was right about Communism. Marx just applied it to the wrong species. It does work fine for ants!

Beyond Risk Management:: What Are the Alternatives?


There really isn’t much point in me adding to this blog from Ontonix. Maybe one of these days the financial sector will overcome its “prediction addiction”. Maybe!!?

Risk STILL isn’t optional: nor is the truth!

When facing large doses of uncertainty risk model-based methods of managing uncertainty don’t work. One thing is to manage an assembly line producing, for example, computer chips, another is to run a company in a globalized, turbulent, chaotic, non-stationary and shock-punctuated economy. Some things can be accomplished via mathematical modelling some cannot. Sure, you can model anything. Nobody can stop you from dreaming up an equation based on which you invest your own savings or those of other individuals. That is not the point. The point is that some models are unable to produce results that would be good enough to justify the effort of building them. Why is that? Those who have a few decades of experience building math models know that:

Read more of this post

Risk:: some things just CANNOT be modelled


Believe it or not this is only an extract from a longer article by the Founder of Ontonix. I am, very much a layman when it comes to computer models but that is most certainly not the case with Jacek (Marczyk). However, even I know enough to question, what I have come to refer to as, the “prediction addiction”  that afflicts the insurance and wider financial sector.

There is a fundamental principle – the Principle of Incompatibility – which states that as complexity increases, precision and relevance become mutually exclusive. In other words, as things get complex (and they seem to be) your statements about it become less and less precise. This means that as something becomes highly complex you can forget building models. You need to change strategy. A new approach is needed. You must change direction. Large consulting firms claim otherwise. Read more of this post

So, what does the future hold?


…NO-ONE KNOWS! Deal with it. Move on.

It doesn’t matter whether you have a calculator or a PhD, a supercomputer and a job with a 200 year old financial institution that is a fact. So, can we PLEASE get over our prediction addiction and deal with what we are able to influence in the real world!?

Coincidentally, this morning, I read an excellent book review (Models Behaving Badly by Emanuel Derman) and I wanted to share his quote about mathematical models: “we are trying to force the ugly stepsister’s foot into Cinderella’s pretty glass slipper. It doesn’t fit without cutting off some of the essential parts.” 

But here is yet another expert making the same point…

Simulations of highly dynamic natural systems have shown that models of growing complexity are moving slowly toward reasonable replications of reality: global climate modelling is a fine example of this slow, but indisputable, trend. In contrast, forecasts of interactions of social, economic, technical, and environmental developments are not going to improve by making models more complex. This is because so many critical variables determining eventual outcomes cannot be either anticipated or, when they get considered, their probabilities cannot be confidently placed within bounds narrow enough to generate a restricted fan of possible outcomes that might be used in confident decision making. Once the inherent uncertainties make the outcome fan too wide, there is little point in building more complex models: we might have obtained pretty much the same results with a small electronic calculator and the proverbial back of an envelope.

What to Do Instead

Read more of this post