Mar 17, 2013

AIFMD Fun of Funds

To prevent future crises, a new European law, the Alternative Investment Fund Managers Directive (AIFMD)  came into force on 22 July 2011.

The new directive has to be implemented before 22 July 2013 and will also apply to non-EU fund managers if they ares managing or marketing an AIF to investors in the EU.

It is believed that the directive will reduce the number of non-EU managers operating within the EU.

AIF's assets and risk management
Although the AIFM-Directive has many new demands (appoint independent valuer, custodian, disclosure) we'll focus here on the requirement to ensure an independent evaluation of the AIF's assets and risk management.

AIFMD Risk Management Obligations
  • Every AIFM needs to have an adequate documented risk management policy, covering all possible risks faced by the AIFs
  • Every AIFM has to set quantitative and qualitative risk limits for each AIF for all possible kind of risks 
  • An AIFM's Risk Measurement Procedure should include requirements for: backtesting, stress-testing, scenario analyses and the rules should describe remedial action plans when limits are breached. 

So far so good, peace of a cake, you would think. Unfortunately: NO!

1. In-depth market risk assessment: too complex and not adequate
An adequate in-depth market risk assessment of AIFMs AIFs actually requires a full 'fund of funds' transparency of the portfolio of the (AIF) funds.

The problem is that full 'fund of funds' transparency does not exist yet, nor can it finally be fully obtained. It's simply too complex:
  • undefined systemic risks are often beneath the analyse surface
  • (re)hedged risks could be part of a fatal unknown or unapparent self-reference hedge cycle
  • in-depth 'fund of funds' management is time consuming and presumes that risk profiles of sub-funds are available, when in practice they are often not

To illustrate the desperate, funny and useless efforts that are made to tame the 'fund of funds' issues within the AIFMD, just take a look at the next quote from the AIF Handbook draft 2013 :

Section 5-iii-1, Alias 'Fun' of Funds
"Any proposed investment by a Qualifying Investor AIF into another investment fund must be clearly disclosed.
Disclosure must focus on the implications of this policy regarding 
increased costs to unitholders (i.e. the fact that fees will arise at two or, in the cases where the underlying fund it itself a fund of funds, three levels – the Qualifying Investor AIF, the underlying fund of funds and the underlying funds in which the underlying fund of funds invests) and the resultant lack of transparency in investments."

I hope you're still with me after all this fund of funds of funds of funds fun..... ;-)

Thus, in-depth market risk assessments in a non transparent market are inadequate and may potentially result in ill-founded or even erroneous conclusions (e.g.' false safety').

Market Risk Assessment
The adequacy of an AIFMD's Market Risk Assessment could be roughly defined as:

MRA-Adequacy = ADTQ x RPQ x RMQ


With: ADTQ= Asset Data Transparency Quality, RPQ= Risk Policy Quality and RMQ = Risk Model Quality.

Just let your colleague rate your ADTQ, RPQ and RMQ on a ten point scale. If the outcome MRA-Adequacy is lower than 800, consider your test as inadequate.

As transparency also includes full sub-cycle  'fund of funds' transparency, often ADTQ will not score high enough for an adequate test outcome.

Example
Suppose an AIF consists of 30% 'fund of funds' with minor risk information regarding the sub-funds.All other scores of the AIF score well (10). In this case the test adequacy score is 700 (= 7 x 10 x 10) . Conclusion: the quality of your risk assessment is insufficient for drawing robust conclusions.

2. Alternative: Strategic Market Risk Assessment
Instead of - come what may - trying to get to the endless bottom of a 'fund to fund' construction, a more strategic risk assessment approach -  as an alternative -could work out much more effective. A strategic market risk assessment that assesses the nature, risk and policy of a AIF and its investments and that implicitly takes into account non-linear risks, the presence of systemic risk, a large number of weighted and not-weighted economic scenarios, stress tests and fat tail risks.

The Secret of the Chef
Many (hedge) funds have only a limited transparent investment policy or an investment policy that  - for whatever reason -is regarded as 'The Secret of the Chef'.

In these kind of funds 'full disclosure' will end in a lot of degrees of freedom in 'risk policy' and corresponding mandates.

It's important to realize that the more degrees of  freedom in 'risk policy' a manager of a fund has, the more risk will emerge in the above formulated alternative assessment.

New alternative market risk models?
Key question is: are there new models that can assess investment strategies and portfolios in a systemic risk environment and on basis of non-linear modeling.

The answer to this question is : Yes, very soon!

Symetrics, a brand new company in the Netherlands is developing an investment decision support and assessment system called SyMath, that is based on nonlinear modeling, grasps systemic risk and includes future crises. SyMath will be on the market mid 2013.



Until then will have to assess AIFMs with pen and pencil... ;-)


Links, Used Sources


Feb 26, 2013

NOT Discriminating is NOT possible

Tomorrow I'll be discussing the borders of solidarity as a panel member at an actuarial congress (VSAE)  for econometricians in The Hague (The Netherlands).

In a Dutch interview preceding the congress, two students asked me:

"The  Court of Justice of the European Union (CJEU) has decided that the use of gender as a risk factor by insurers should not lead to individual differences in premiums and benefits.
What is your opinion?"

My short answer was :

NOT Discriminating is 
NOT Possible

Examples
Let me illustrate this 'quantum quote' with two examples.

Example I: Gender Neutral Car Insurance 
  • It's scientifically proven that women are better drivers, have just as much car accidents as men, but cause less damage. That's a fact and that's why car insurance for women is cheaper than for men. 
  • As from December 21, 2012, European insurers are not allowed to 'discriminate' anymore by gender, implying equal car insurance premiums for men and women. 
  • If insurers calculate this premium as the weighted average of their portfolio, women are obliged to pay (much) more premium than before and also more than actually and actuarially necessary regarding their gender group. 
  • Therefore women are de facto discriminated, although the genuine intention was NOT to discriminate!
  • Not only women, but also insurers are discriminated as they now will be faced with anti-selection: Relatively more men will choose an insurance cover, as car insurance premiums for men have become less than the premium corresponding with the expected damage for their gender group. Insurers will therefore face a loss on car insurance. 
  • Based on solvency legislation, the insurer will (next) be 'forced' to increase the average weighted premium. This - in turn - is at odds with the measures envisaged by the European Court. 
  • A similar kind of reasoning applies also for unisex rates for pension and life insurance.
  • The upcoming (2014) US health care law will also prohibit “gender rating”. However, gaps persist in most states. There seem to be no signs of insurers that have taken steps to reduce them.

The conclusion must be that discrimination regulation is carried too far.

 'Over-Solidarity' as in this case has nothing to do with real solidarity and is in nobody's interest; it has become 'Anti-solidarity'.

The proposed measures - no matter how well intended - have a opposite effect and should be reconsidered on basis of the question: are the discriminating effects before the new legislation more or less than after?

We've got to stop discrimination due to over-discrimination and anti-discrimination!

Insurance Rating Fallacy: Gender anti-discrimination laws are superseded 
Prohibiting "gender", "marital status" and "age" as rating elements doesn't solve anything.

Modern rating systems based on data mining (Google history), social media (premium quoting on basis of: your smart-phone that captures and shares your drivingstyle with the insurer) and neural networks are "black boxes" that quote insurance premiums in such a way that every client can get individually quoted on bases of his 'profile'.


That 'profile' doesn't have to contain any of the forbidden discriminating elements (nor direct related) to get satisfactory results for clients as well as insurers. Although there are also simple (e.g. Bayesian-Classification) techniques to derive a clients gender from other non-discriminant related variables (e.g. height, weight and foot-size determine gender quite accurately) in an insurers direct or indirect related data base, insurers and their actuaries would end up in an unwanted ethical dilemma by using these direct-related techniques.

Another illustrative and strong example of determining your gender on bases of - at first sight - non-gender-related information is Hacker Factor's "Gender Guesser"  that attempts to determine an author's gender based on the words used. Try  "Gender Guesser" for yourself HERE. Take a part of an email you've written (more than 300 words), copy-paste it to Gender Guesser and notice how gender Guesser will probably determine your gender without any problem in a split of a second!


These simple techniques show that the developed anti discrimination legislation is superseded and has become irrelevant for insurers and their clients to come anyhow to an adequate and ethical responsible rating policy on basis of neural networks or social media related information, such as information from smartphones that transmit your driving style information to the insurer (why not, if you have nothing to hide?).

Example 2:.Women on Boards: Commission proposes 40% objective
The European Commission has proposed legislation with the aim of attaining a 40% women presence objective in non-executive board-member positions of publicly listed large companies.
Currently, large boards are dominated by men (85% non-executive, 91% executive).

No matter how welcome and needful women are on board level, forcing such a development makes no sense and will have an adverse effect.

From experience I can tell that women who really qualify for board level positions, are very unhappy if they are appointed under the vigor of gender legislation and not on basis of their acknowledged competences.

This is perhaps a sign that women who really qualify feel discriminated by this new proposal. Proposals should better emphasize on stimulating women presence on board level and take away old boys network principles.

Conclusion
Anti discriminating legislation often results in the exact opposite of what is intended. Legislation is often superseded, should be carefully evaluated on its effects and certainly reconsidered if the discriminating effects after applying the new legislation increase.


Used Sources and Links

Humor: Actuarial Creativity

As actuaries we've studied a lot in life. And to keep up with actuarial science we'll probably keep studying until our personal mortality rate hits us finally in the back.

Although study brought us to the top of financial and statistic modeling, there's a small but fatal risk that we become so engrossed in our work that we loose our creativity or ability to solve things in a simple way.

Test

To test whether you're still a creative 'simplist', let's do a short 3 question test. Here it is:

Question 1
 "Show how it is possible to determine the height of a tall building with the aid of a barometer."



If you think you've solved this high school level problem, go to the next question

Question 2
 "Solve question 1 with another method."

If you think you've solved this problem as wel, go to the final question

Question 3
 "Solve question 1 with 4 other methods."

Evaluation
Although actuaries never give up, there's a slight chance you had to surrender and are longing for the answer.
In that case (only), read further for the answer.

Answer: The Barometer Fable
Bob Pease (Nat.Semi.) records the story of the Physics student who got the following question in an exam: "You are given an accurate barometer, how would you use it to determine the height of a skyscraper ?"

  1. He answered: "Go to the top floor, tie a long piece of string to the barometer, let it down 'till it touches the ground and measure the length of the string".

    The examiner wasn't satisfied, so they decided to interview the guy: "Can you give us another method, one which demonstrates your knowledge of Physics ?"
     
  2.  "Sure, go to the top floor, drop the barometer off, and measure how long before it hits the ground……"

    "Not, quite what we wanted, care to try again ?"
     
  3. "Make a pendulum of the barometer, measure its period at the bottom, then measure its period at the top……"

    "..another try ?…."
     
  4. "Measure the length of the barometer, then mount it vertically on the ground on a sunny day and measure its shadow, measure the shadow of the skyscraper….."

    "….and again ?…."
     
  5. "walk up the stairs and use the barometer as a ruler to measure the height of the walls in the stairwells."

    "…One more try ?"
     
  6. "Find where the janitor lives, knock on his door and say
    'Please, Mr Janitor, if I give you this nice Barometer, will you tell me the height of this building ?"


Find more than 140 solutions and read the original famous Barometer Fable, as published in 1968 in an article  by Alexander Calandra.

Warning!
Keep in mind that not every method leads to satisfactory results.
An uncertainty analysis of determining a building height using a barometer, developed by Israel Urieli, shows that this method is not accurate at all!

So the surprising news is that the first two alternative methods mentioned above are more accurate than the method you learn at high school.

Finally
It's always best when you can solve an (actuarial) problem in more than one way and the outcomes point in the same direction. The more a specific solution comes to front by applying different methods and/or data, the more confident you can be that the outcome is robust.

Used Sources