How big is the Rogue trader distribution?  We only get to see the tails of the distribution.

Look out rogue traders exist in banks.

Shocker!  $x billion lost etc.

These headlines are not as worrying as they seem. The real worrying headlines are the ones not written. For every rogue trader loss there are significantly more bad actors and actions going on under the hood.  Institutionally the mega bank approach is antithetical to sound risk management.  Mega-bank structures mean that decision makers end up managing reports and check boxes instead of risk.

Banking isn’t complicated, it is a nice combination of high-wire tightrope walking and magic show.

The more leverage and complexity, the higher the wire. The greater the institutional complexity and size, the greater the need for magic (deception). What depositors and counter parties want is the veneer of a reputation for stability and sound practice. The machine or institution protects that veneer in the short-term at the systems expense in the long term.

In hiding the smaller (errors) rogues from others and itself institutions become blinded to the true nature of operational risk and complexity.  Current reporting on “rogue” activities in banks due to behavioral conventions is akin to flying an airplane with a fuel gauge designed to never report less than half a tank of fuel.

Designing a safe system means designing for components to fail safe.

One way to design a safe system is to acknowledge the reality that institutions die and fail all the time. It is important to acknowledge the foibles of human nature and institutional mortality. Greed and stupidity can’t be managed away, they are hard wired human traits. At best these traits impacts can be minimized or contained. Individual Institutions and banks don’t and shouldn’t matter to the overall economy. It is they economic ecosystem matters. To protect the system the rules needs to designed and managed in such a way that institutions can fail and disappear. The fact is that all institutions fail and disappear.

It is only our limited perception of time which makes large organizations feel permanent. Reading Kindelberger and other economic history is a good antidote to the permanency illusion or the overly great importance placed on today’s institutions. History humbles. History instructs. Sadly ego and vanity mean history is mostly ignored. Our time and place is unique, but probably not that exceptional when viewed in broader context.

Designing a system with smaller compartmentalized  and de-coupled institutionals is one solution. This means a trade off between resiliency versus efficiency. Society should choose, wether to have monolithic institutional titanic elephants with high ROEs (returns on equity) prone to systemic collapse, or smaller institutions with smaller ROEs prone to individual collapse.  Sustainability and resiliency often mean trading off concentrated monolithic efficiency for broader systemic resiliency.

The institutional decision tree below is likely human nature and SOP for most corporations not just banks.

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Taleb has a good video on fragility and the assymetry of risk.  The video is 68 minutes long and covers quite a few things involving the assymetry of risk, anti-fragility and robustness.

One point is well made about Jensen’s inequality and the nature of variance about the mean which significantly alters tail risk.

The way I think about these things is that a complex system has multiple components. Those components variances are not necessarily simplisticly additive. The potential for interaction to occur due to some form of coupling induces uncertainty in the systems outcomes.  The more components in the systems the greater the uncertainty of the outcomes. Additional portfolio diversification comes at the expense of knowing what is in the portfolio. If you don’t understand the sources of value or return, don’t add more of them.

This sounds obvious, but most people don’t quite get it. The addition of multiple components can vastly increase the number of “hidden” paths the overall system may take, these hidden paths include extreme tail variance.

Many systems and risks are assymetric in that thier positive variance is either de-minimus or trivial.  An airplane is a complex system made of multiple parts, those parts or components may each have a known failure rate, but the fact is that the overall failure rate of the large system is likely greater than the cumulative components failure rate, due to unforeseen systemic interactions.  The asymmetry of the system variance is obvious.  A normal functioning plane flys, a failed system crashes.

Interestingly a rule of complex systems is that they are almost never succesffully designed functional from scratch, but rather evolve from simple small systems that function.

The word evolve is logical here as one can think of a complex organism such as the human is made up of over 200 kind of specialized and differentiated/evolved cells which evolved over time into differentiated functions which allowed for a net symbiotic gain in individual reproduction.

From a risk perspective the rules fall out as the following.

• 1. Component risk is not additive at the system level.
• 2. Historical system risk and output behavior is inversely useful relative to the number of component connection/links in the system.
• 3. Asymmetrical risk in systems must be managed by adding capacity / tolerance for failure or minimizing / dampening the components interaction.
• 4. Be aware of the trade off between efficiency and robustness across components and across longer time horizons.

For robust design of a banking, biological, political, manufacturing etc. system This boils down, to keep it simple, keep it small, keep it buffered.

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