The Blame Games of 2008 - A Late Review

In 2008 a game went over the financial world: "blame anonymous men at market participants, methodology and technology providers, ... for the crisis".

I will concentrate on quant finance and issues that are in the frame of the business we are in: models and methods for derivative and risk analytics.

What was blamed 2008 and what do we know now?

What was not known 2008: diversification does not work 
What should have been anticipated 2008: normally distributed short rate models are dead - long live normally distributed short rate models

What has been named, but is, IMO, still misinterpreted, or even ignored but also what has been blamed incorrectly and what do we know better?

Complex Instruments - "CDO^2",  ABS, MBS, ... probably among the most complex (most naive?) modeling can be found behind these instruments. Does it make a difference that some of these models and methodologies are now available for free?

Credit modeling (in general) - usually default is not a probabilistic event, it is often a business decision. Not to speak about sovereign ...
Credit modeling is going into a next round, with the introduction of exposure modeling for CVA/DVA .. adjustments. But, IMO, if forced to apply it in pricing uncompromisingly it might lead to unintended complexity ..

Risk neutrality - this fundamental concept is not so easy to understand (Paul Wilmott who also organized a Name and Shame in Our New Blame  Game poll in his online server estimated 2008 that only 2% of people working in derivative and risk management do).
It is a concept that makes the market a fair play. But it needs to be played. And the simple Black Scholes game was successfully played by 1987 - the the out-of-the-money options are introduced and the smile was discovered. With the consequence of complex modeling and the needs to ride the price waves with calibration and recalibration, with the problem of inverse problems ...

VaR - NN Taleb even blamed it in front of TheUS Congress. Yes, it was misunderstood and maybe even used to hide risk. But we know more now: VaR in the jungle.

Mathematics - dumbing it down is bad, because you cannot price sophisticated deal types without and how can you know all the risk. Making models too complicated may be even worse. What is the use of many factors, if you lose the extra information in the numerical jungle. If we think of our cross-sectoral mathematical repertoire, OK, quant finance is one of the easiest, in principle ... but you can make it as complicated as you like.
This is our commitment: we never give our customers false comfort about the accuracy and robustness of our model-method combinations.

And this is one of the (hidden) strengths of the UnRisk core team: we have a deep look into the math behind and see toxicity, traps, spurious accuracy and robustness, ...

And we still lose a few sales cases, because we reject to bend the reality. But at the other hand it makes Arming David so exciting: you can explain what you do and how and what you do not and why - to chief executive buyers.