SMPLFCTN

As an actuary, you probably grew up with that famous quote of Einstein:

Everything Should Be Made as Simple as Possible,

But Not Simpler.

However, as 'Quote Investigator' shows, there is no direct evidence that Einstein crafted this aphorism...

Hmmmm.... Never mind.... as this quote is clearly redundant and therefore can be simplified....

So, it's enough to stick to the subjective concept of 'keep it simple'.....

'Simple', simply means 'easy to understand'.  

If we would try to present or explain something 'too simple', we are in fact making it harder to understand and therefore 'more complicated'.

Example

If we try to explain that we can estimate the area of a circle (approx. 3.14159...; radius=1) in practice by a n-sided polygon, a three year old child ;-) will buy your simplification in case of  a 12-sided polygon.

Oversimplified, or Worse: Desimplified
In case of a square (4-sided polygon), he'll probably raise his eyebrow, as you oversimplified the topic. And in case of a triangle you'll probably have lost him completely. You desimplified and thereby complicated your case to the opposite of what you untended : a clear understanding.

Simplification Criterion
Keep in mind that, like in the case above, you must develop a criterion when you simplify things. In the above example, a criterion could (e,g) be that the area of the polygon shouldn't differ more than 10% of the original circle and must have a relative simple (round) answer. This criterion would lead to a 12-sided polygon as an adequate simplification example.

And of course, we have to test this ex-ante 12-sided criterion in practice by means of a questionnaire.

Simplification is Complicated
However, 'simplification' as process, is not simple at all. In practice simplification can be used to reduce things that are:

1. complicated (not simple, but knowable) or 
2. complex (not simple and never fully knowable) 

In an article called 'Simplicity: A New Model',  Jurgen Appelo tries to simplify the complex world of simplicity linked concepts. He states that simplification means 'make understandable', which means moving it vertically, from the top of the model to the bottom in the following Appelo-illustration.

Anyhow, there's much to learn about simplicity related topics.....   

Let's finish with an excellent example of a need for simplification : 

Simplifying 'Complexity of financial regulation'
In an excellent presentation, Executive Director Financial Stability of the Bank of England,  Andrew Haldane, pleas and argues to simplify financial regulation.

It turns out that the growing number of regulation rules and principles (e.g. Basel III) has an adverse effect on taming the crisis.

Also the traditional Merton-Markowitz approach that assumes a known probability distribution for future market risk and enables portfolio risk to be calculated and thereby priced and hedged, offers no help to solve the current crisis.
Haldane concludes that "More simple regulation  based on 'Optimal choice under uncertainty' is necessarily. Haldane concludes:

"Modern finance is complex, perhaps too complex.  Regulation of modern finance is complex, almost certainly too complex.  That configuration spells trouble.

As you do not fight fire with fire, you do not fight complexity with complexity.  Because complexity generates uncertainty, not risk, it requires a regulatory response grounded in simplicity, not complexity. 

Delivering that would require an about-turn from the regulatory community from the path followed for the better part of the past 50 years.  If a once-in-a-lifetime crisis is not able to deliver that change, it is not clear what will.  

To ask today’s regulators to save us from tomorrow’s crisis using yesterday’s toolbox is to ask a border collie to catch a frisbee by first applying Newton’s Law of Gravity."

Haldane's (2012) presentation called 'Ensuring Long-Term Financial Stability', or more popular 'The dog and the frisbee', is a breakthrough in managing, modeling and controlling Risk and financial future results. It's a MUST read for actuaries and board members in the financial industry.

Finally
From now in, actuaries can simply start 'helping' as a border collie!

Sources/Links
- The dog and the frisbee
- Risk models must be torn up
- Mathematica: Play with Polygons
- Einstein's Simple Quote Investigated
- Complex versus Complicated
- Complicated vs complex vs chaotic
- Simplicity a new model

Risky and Happy 2012

A happy new year to all Actuary-Info readers!



While actuaries and other risk mangers are still trying to cope with 'real' (btw: what's really real?) risks, a lot of other people are still worried about the risk of risks:

The end of the world

as (assumed) predicted by the Mayans!

Maya Calendar Explained

Consult Cathryn Reese-Taylor (program director, department Archeology University of Calgary) (or read this link) for who's interested in the interesting explanation behind the end of the Maya calender.

In short, it turns out that 21 December 2012 is simply the end of the 13th baktun, a period of roughly 5200 years that the Maya used as a period-unit for counting time. Just like we in our culture use millennial periods for constructing time.

Besides this fact, the Maya predicted other events far into the future, well beyond 2012. Problem solved!

2012: year of Risks
Having said all of this, it doesn't imply that 2012 will not turn out to become a year of risks: (aamof) It Will!

New Risk Management

Main issue will be that we'll have to change our view on Risk Management in 2012 from a classical view to a new self-conscious view ...

The old classical view goes something like this:

In the old view, Regulation and Governance are more or less considered as 'constant' and as a 'condition you have to meet'.

However,  nothing is farther from the truth.
In the last decade we've seen that changes in Regulation substantially have influenced the way we calculated, perceived and managed risk. The obvious examples are everywhere around us: Solvency II, Basel I/II/III, AIFMD, MIFID, OTC, etc., etc.........

So, in fact the new simplified Risk Management looks (less spectacular) more like this:

In this 'New'  Risk Model, EVERYTHING -including Risk management itself, is considered as RISK!

Main issue is not to take anything (or risk) for granted and to (re)consider each risk element (minimal) once a year in order to keep RISK FIT.

Just a few illustrations on some of the new risk topics to set the mind in the right direction:

I. Regulation Risk
It's not just a case of checking if you're Regulation Risk Compliant. It's also anticipating on coming new legislation, directives and rules. Not only 'formal' new directives (like Solvency) but also informal rules like CSR's  "acting green" are important. Not acting pro-active could cause a severe reputation risk.

II. Governance Risk
It's not only about improving (corporate) governance quality and reducing the risk of governance failures, it's more. Managing the risk of governance risk, is double and independent checking on:
- Truly independence of (supervisory) board members
- Timely (3 years) rotation
- Appointing timely 'new' knowledge in boards, audit/investment committees
- Transparent reporting to shareholders and regulators about (different) views
   and explaining WHY decisions have been taken the way they are, including
   pro and contra arguments.

III. 'Risk Appetite' Risk
- Check (by reporting!) regularly if your risk budget and risk results
   (SD, Sharpe Ratio, Sortino Ratio, Information ratio, etc) are still in
   line with your risk appetite. If not: Act upon it!
- Compare your risk appetite and the results with those of compettitors.


IV. Models and Data Risk
Change and adapt your data and used models regularly with reality.
You do? ......
E.g.: Risk is not just Standard Deviation (SD). If so, why are Efficient frontiers in ALM still calculated and published on basis of simple (but not applicable anymore!) SD.


Anyhow.... Risky and Happy 2012 Risks!

Related Links:
- Definitions: SD, Sharpe Ratio, Sortino Ratio, Information ratio, etc
- PWC European financial regulation updates
- EIFR
- Bloomberg Financial regulation
- ICFR: What does good regulation look like?

Langton's Actuarial Ant

As an actuary, you believe in the consistency of your risk models.

You might think that with 10.000 observations you've got enough stuff to present a consistent statistical model with realistic expectations, variances, etc.

You are aware that the output of your model depends on the quality of the data and the assumptions. In your advice you try to communicate all that to the board in order to support sound and responsible decisions.

In other words, you've got a consistent model and, as an actuary with a professional and consistent life-philosophy, you have everything under control. No great changes will take place?

Well, 

you're probably wrong !

Just like our models, we actuaries, are not consistent

Even if we (or the risk reality we try to model) act in a stable consistent way, we (or risk reality) keep interfering with our environment and our environment responses to us.

At first this response seems meaningless and of no value. You think you're consequent and your work and achievements in life seem relatively stable, perhaps a little bit chaotic and of no great significance. But in repeating your proven receipts, way of doing or procedures endlessly, eventually

Something will change
This change often will not appear as an evolution in your life, but as a kind of revolution, out of the blue and most often unexpected.
Suddenly, just like in the credit crisis, there's an emerging situation. The way you always did it, doesn't turn out right anymore. Your model crashed, you crashed and there was nothing you could do about it. You couldn't have foreseen it, you could not have prevented it the classical way.

That's why we always have to add some non-classical extra 'common sense' safety margin thinking in our models.

Progress?
The other side of this is also true. Fore example, when you study, you'll probably, once in a while, think: what progress am I making?

But don't worry, if you keep on your track, there'll be a day your future suddenly comes to you (out of the blue: as a kind of emergent property) instead of "the you trying to make your future" in this Game of Life.

A good demonstration of this principle is

Langton's ant Langton's ant is an virtual ant that starts out on a grid containing black and white cells, and then follows the following set of rules. If the ant is on a black square, it turns right 90° and moves forward one unit. If the ant is on a white square, it turns left 90° and moves forward one unit. When the ant leaves a square, it inverts the color. The result is a quite complicated and apparently chaotic, but relatively stable, motion. But after about 10.000 moves the ant starts to build a broad diagonal "highway".

So keep in mind "Langton's Actuarial Ant" next time you design a new risk model.

Anyhow, stay on your track as an actuary and remember, whether it's you in life or your models, someday there'll be

a collapse of chaos