Actuary Info Blog

Interactive Map Charts

2012-01-18T14:50:00.004+01:00

Remarkably interesting interactive charts at Chartsbin.

Just some examples:

- Press on 'Key' to toggle descrition square
- Press on Big Screen to view more details

1. Current World Life Expectancy at Birth

via chartsbin.com

2.Body Mass Index (BMI) by Country

via chartsbin.com

Want more chart examples with dropdown-menus for non-IE-users...?

Click Here

It's also possible to
- Embed Chartsbin charts in your Powerpoint presentation!
- Search voor Chartsbin charts

Enjoy!

Pensionpoly

2012-01-17T23:50:00.001+01:00

Brainteaser...... What skills do you need to manage a pension fund?

Whatever brilliant your answer, I'm sure that the 'art of playing Monopoly' wasn't a part of it.

Yet, playing Monopoly and managing a pension fund [ let's call it Pensionpoly] have a lot in common nowadays.

The main difference is that with Monopoly you can actually calculate the probability you land on one of the forty squares, while in Pensionpoly you THINK you can calculate the probability of the return of a certain asset class.

The similarities between Monopoly and Pensionpoly are that while executing a certain buying strategy (whether houses, hotels, stocks, bonds or other asset classes), the - short term - outcome also depends on the (financial) effects of the squares we land on and on a number of uncertain events as a result of drawing Chance and Community Chest cards.

Monopoly probabilities
As described by Jörg Bewersdorff, the probability of landing on a particular square, basically can be calculated either on basis of Markov Chains or by means of applying the famous Monte Carlo method.

As an example here's the outcome of lending on a particular square on basis of a Monte Carlo simulation (more than 60.000 observations).

What's striking is that there's a 9.3% chance of ending up in jail.....

Of course, playing Monopoly takes a lot more than just calculating the probability on which square you'll be landing. Some excellent calculations have been made by Truman Collins (2005) , that include:

Long term probabilities for ending up on each of the squares
Expected income per opponent roll on all properties and other squares
Expected number of opponent rolls to lose or recoup mortgages

Pensionpoly
Back to Pensionpoly....
You can now practice you skills in playing Pensionpoly by downloading the Pensionpoly board game here.

Unzip (no viruses) the download (2Mb) file, click on 'Monopoly.exe' and start playing Pensionpoly in a minute.

Playing Pensionpoly is like playing Monopoly, with the following main differences:

Cities are replaced by Asset Classes
Streets are investment categories in a certain Asset Class
'Buying Houses' is replaced by hiring (buying, appointing) Fund Managers (F-Managers);
Five Fund managers make no Hotel, but a Fund Team (F-Team)
Chance cards are replaced by Asset (chance) cards
Community Chest cards are replaced by Liability (chance) cards

Pensionpoly is a nice example of what is called Gamification. More info about this subject on Pension Gamification.....

Have fun playing Pensionpoly and don't forget to play normal Monopoly with this application as well !

Sources and related links
- Bewersdorff: Monopoly in the view of mathematics (2002)
- German: Monopoly im Blickwinkel der Mathematik
- Collins: Probabilities in the Game of Monopoly (2005)

- Create your own Monopoly at Parkeeerbonnen (Dutch)
- Direct download Monopoly from Parkeerbonnen
- Markov Chains and Monopoly (Scribd)

- 18-karat solid gold Monopoly set (Museum of American Finance)

Download
- - Download Pensionpoly (zip file)

Risky and Happy 2012

2012-01-02T15:46:00.000+01:00

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), it's really - as we've seen - about standard deviation. 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?

Sylvester: ABP, Cut Pensions?

2011-12-31T22:16:00.001+01:00

At the end of 2011, let's take a short view on the madness around cutting pensions.

As a leading example, I'll discuss ABP, a Dutch 240 billion pension fund and one of the largest pension funds in the world.

Being fanatic blog readers and actuaries, you're probably 'in' for a teasing joke on Sylvester or 'New Years Eve'.

As you all know communication is key in the pension business. However, as pension investment results get more volatile and complex (in time) to explain, communication about pension issues becomes more and more Chinese for ordinary pension members.

The latest threat, cutting pension benefits, urges board members to develop themselves to a kind of 'five-legged sheep' .... The new 'normal' pension board member is undoubtedly the ideal combination of an actuary, accountant, investment specialist, communication expert, ICT specialist and - on top of - a keen psychologist.

Communication is a Profession
I'll give a short slightly exaggerated demonstration to all pension board members and actuaries of how difficult reading and understanding a well meant pension board message is, to an average pension member.

In order to 'save what can be saved' ABP's Vice-Chair Joop van Lunteren pleads for political help in ABP's 2011 Q3 Press Release.
Besides the question if a press release is indeed the right place for such a call, most pension members will have a hard time to understand what Mr. Van Lunteren wants so rightfully to express. For these pension members Mr. van Lunteren's message is more like Chinese...

ABP's Q3 Results: Cutting Pensions?
Now to more serious business... Altough ABP's Q3 results are indeed not splendid,

the call for a more long term sustainable valuation system that makes pension funds less dependent upon volatile interest rates makes sense!

Also, there no need for panic (direct cutting measures), as from the 2010 annual report we can find that the annual benefits payments summed up to around € 7.5 billion on a total of assets of around € 240 Billion. If ABP would be allowed to wait for the effects of taken measures en developing markets for another five years, a 10% cutting of benefits would only have an impact of around € 4 to 6 billion on the total assets of around € 240 mln.
More info about Cutting Pension rights on Actuary Info....

Happy Silvester and good luck ABP!

Sources/Links:
- ABP Q3 Press Release
- ABP Annual Report 2010
- Ming Imperial Fonts

Humor: Pickles Risk Management Lesson

2011-12-16T14:37:00.001+01:00

All credits to the author of Pickles:Brian Crane

Original Sources /Links:

- Gocomics : Pickles
- The art of making Pickles
- Pickles Wikipedia
- Brian Crane

Forecast Period Principle

2011-12-12T07:42:00.006+01:00

As actuaries we mostly try to shape the data for our models (ALM, Stress Tests, Assessments, Etc.) on basis of economic scenarios.

Recently we have experienced (Sub prime crisis, Bank crisis, Country crisis, Currency crisis, Debt crisis, etc) that our economy isn't that stable as we might perhaps have estimated or hoped (what's the difference nowadays?) .............

In other words:

Our Economy is chaotic by nature

Therefore, to learn how to shape our data, models and equations in a more chaotic or fuzzy way, let's take a look at the more chaotic processes of nature self.

Sea Level Rising
As an example let's pick out a major discussion: Sea level rising!
The discussion around this topic resembles the fuzzy way we discuss our economic and financial system. Some say sea level is rising and our (grand)children will surely drown. Others tell us not to worry. Who's right?

As the above graph - based on data of the University of Colorado - clearly shows, sea level is rising (Trend: ~3.1mm/year).

But just like in risk management models, the devil is in the details and (on the other hand) God's wisdom rules in time......

Actuarial devil watchers will have noticed a strange 'hockey schtick' in the above graph: Sea level is actually declining since 2007.

This leads to the key question:

What is a reliable Sea Level long term forecast?

How to answer this question...

Forecast Period Principle
To draw sensible forecast conclusions, the period of the measured and analyzed historical facts and their (explaining) context, has to be of the same order of magnitude as the period we use to (context-dependable) project our data in the future.

So if we want to say something about for instance the next 14000 years, we should (also) look back 14000 years:

From the above chart it's clear that forecasts about sea level forecast on basis of 4, 10 or even 50 years are madman's exercises and useless.

On the long term (10-100 years) sea level will most likely keep rising at an average 3-4mm/year rate. So you don't need to calculate if your home will turn into an houseboat, unless....

Pension Funds and 'Forecast Period Principle'
Now let's apply the 'Forecast Period Principle' on pension funds...

Pension funds have a life span of more than hundred years, pension fund members have a life span of about 70-80 years.
Therefore projections and valuation of pension funds should also take place on basis of periods and (long) term discount rates of the same order of magnitude (10-50-100 years) as their life span.
This implies that calculating coverage ratio's on a daily basis is perhaps a nice way to make a living as actuary, but practical completely inadequate. As it serves no goal, leads to unnecessary worries and misleads pension board members.
Lesson: calculate coverage ratios on 1,5 and 10 year basis and take action if all these coverage ratios start pointing in the same direction....

Unless.... : Langton Warning Principle

Yet, if you calculated your forecast on basis of the 'Forecast Period Principle', do not go to sleep peacefully!

Even if your models and visual inspection indicate a steady development, there's always the risk of a sudden 'Langton's Event' (loss).

In other words:

So take the 'Langton Warning Principle' serious and try to stay alert as risk manager in every possible circumstance.

Do you want to learn more about Langton's principle? Read: Langton's Actuarial Ant

Conclusions
'Crisis' will become business as usual for actuaries. Coming years, our short term 'Langton Warning Principle models' will be just as important as our steady forecasts on basis of the 'Forecast Period Principle'. Don't mix them up!!

Keep in mind the warning of NOAA Administrator Jane Lubchenco:

“We have good reason to believe that what happened this year is not an anomaly, but instead is a harbinger of what is to come.”
NOAA Administrator Jane Lubchenco (2011)

Key Question

Finally, the crisis key question will be:
Are we Sinking or Thinking?

Answer: It's all a matter of communication!

Related links/Sources
- Langton's Actuarial Ant
- Colorado University: Sea level
- Some Actuarial Formula of Life Insurance for Fuzzy Markets
- Google books: Actuaries' survival guide: how to succeed
- Fractals & Actuaries (1997)
- What about my town, when sea level rises X meter?
- actual and historical sea levels: sea levels online
- Sea levels Online
- NOAA Report
- Sea level Spredsheet of this Blog
- Original Picture: Climate Change Science Compendium 2009

River Deep Mountain High Actuary

2011-12-05T01:05:00.004+01:00

As actuaries we execute Risk management by the book. We dive deep into the tails of our risk sea and try to catch every small risk until we reach the value of the Planck constant.

This approach was a proven method to success during the last decades. Our current financial crisis shows us that no asset class is free of risk. This crisis forces us not only to dive deep but also to look at the high mountains of economic risks and emotional winds.....

In other words, to survive the next decades, we have to practice risk management

River Deep, Mountain High

In an excellent presentation Chris Martenson shows us that the constant doubling of debt is about tot collapse and that our economy has to make a turn.

If you got some time left in your busy actuarial life, enjoy the full presentation of Chris and define for yourself which asset classes will be strong enough to survive this mother of all crises. Determine how you're going to embed these conclusions in your actuarial models...

Chris Martenson’s presentation at the Gold & Silver Meeting in Madrid

Here's the PPT presentation of Chris.

Martenson Gold Silver Meeting Madrid 20111

Rethink your Asset Mix
If one thing becomes clear in this presentation, it's that your 'In crisis Asset Mix' will differ substantially from your 'Before Crisis Asset Mix'. By means of economic scenarios and combining financial facts with common sense, you and your board are challenged to find the right asset combination that de-risks your portfolio......

After studying Chris' presentation I'm sure you'll be a qualified 'River Deep, Mountain High Actuary' !

Sources/related Links:
- Homepage Chris Martenson
- Picture Rochat

'Trying' is hard: Youtube

Humor: Past Performance is...

2011-11-25T14:27:00.001+01:00

To protect (!) the customer more and more, investment funds feel the need - or are obligated - to communicate about the expectation of their funds' future return.

One of the most used non- or disinformation statements funds use, is the line:

Past performance is no guarantee of future results

A general lesson is that all prefab communication lines and static communication tools are doomed tot fail, as communication is context and time dependent.

Models

Just as Communication, your Actuarial, Investment or Financial Models are also context (economic, fiscal, ethics) and time dependent.

Change them upfront, as 'performance of yesterday's models is no guarantee for the future.....' ;-)

Sources:
- Free Flash Animations - Smilies by Adrian Wilman

Related:
- Disinformation: Everything You Know Is Wrong

A Better Life

2011-11-21T06:27:00.002+01:00

The new (June 2011) 'OECD Health Data 2011' report shows the latest insights in health spending costs. Here are some results for the main OECD countries:

Health Costs

Total health spending accounted on average for 9.5% of the GDP for all OECD countries (main countries: 9.8%).

Public health is a substantial part of health funding in all OECD countries.

Control Health Costs
Key question is: will relative 'big rising spenders' like The Netherlands and the U.S., be able to control their health costs in the near future?

Besides the fact that health costs undoubtedly rise sharply with age, the bulk of 'annual health spending growth' depends mainly on overall population growth, increases in the health prices and the introduction of new high-cost medical products and treatments used by all age groups.

In controlling health costs, the most difficult an challenging question is in fact:

What are we trying to maximize
with the help of health investment costs?

Our first answer could be : Maximize Health.

In practice we (countries in the world) haven't explicitly defined what we try to maximize... Unfortunately discussing health costs without a clear goal, is an endless road, leading nowhere.... A Health Mission Impossible.....

On top of, 'Health' is - at its best - a non defined subjective perception.....
Let's dive deeper on this theme of perception. Can we grasp it?

Health Perception
As in every corner of (your) life

Perception = Reality

Therefore let's take a look at how health is perceived by people in different countries. For a global 'health perception picture' we have to fall back on self-reported health status figures of around 2006-2007:

As is clear Canada and the U.S. are clear 'feeling healthy' champions, with Japan as poorest performer.

Quality and Quantity of Life
To examine whether the self-reported health status indicator (representing the quality of life) also indicates a 'longer life expectancy' (representing the quantity of life), here is the 'life expectancy indicator'.

Surprisingly the results are - at first sight - counter intuitive:

Japan, with the poorest health perception, scores best in longevity
The U.S., with the almost best health perception, scores worst in longevity

'Good health' and 'life expectancy'
It is known that elderly people report a less than average good healthy condition.

Unfortunately, as the next diagram indicates, there's no convincing direct relationship between 'perceived good health' and 'life expectancy' or 'median age' (as explaining variables) :

Reference: Japan Explained?

To find out 'what drives a health perception', we may examine one of the rare underpinned studies : "The Surveys on the Japanese National Character".

First of all there's a relationship between Economy and Health:

Though declining, more than 50% of all respondents in this survey say that "people's health will get worse".

What's even of more concern, is that younger people are experiencing an increasing feeling of nervousness during the last decades.

This survey supports the idea that perceptions of 'health' and 'happiness' are more or less embedded in a nations' culture and not related to the investments in health.

Find out more on what's going on in Japan beneath the surface on:
Assessment of the Japanese Economy

It's all about Happiness

What remains is that it's all about happiness in life....
And of course happiness and good health are 'somewhat' and 'somehow' related:

Conclusion
Maximizing or optimizing Health in on basis of 'health investments' (health costs) is tricky business. Although Happiness and Health Perception are related, they both don't relate to health investments.

The maximum price for 'good health' is subjective. Governments will have to border the maximum public financed costs of health on basis of objective goals of health condition (eg. max % obesity, BMI, etc) in relation to what's "bearable" in terms of costs in relation to the strength of their national economy.

Let's conclude with some positive news...

Your Better Life Index
I would like to invite you to take part in the Your Better Life Index.

'Your Better Life Index' was designed as s an interactive tool that allows you to see how countries perform according to the importance you give to each of 11 topics – like education, housing, environment, and so on – that contribute to well-being in OECD countries. Your Better Life Index allows you to put different weights on each of the topics, and thus to decide for yourself what contributes most to well-being.

It is a pioneering, interactive tool combining OECD substance with modern
technology in order to educate, promote dialogue and encourage consensus on the balance between societal and economic well-being. Your Better Life Index will be maintained on an ongoing basis.

Here's MY Better life index as an eample.

Live a healthy and - above all - happy life..... A Better life!

Sources
- OECD Health Data 2011 How Does the Netherlands Compare?
- OECD Health Data 2011
- Health Self-Reported Health Status
- Assessment of the Japanese Economy: A Continuing Downward Trend
- Why Does U.S. Health Care Cost So Much? ( An Aging Population Isn’t the Reason)
- The Surveys on the Japanese National Character

Related
- Does Medicare Work Better Than Private Insurance?
- Balancing Affordability and Value: The Universal Challenge in Health Care Delivery

- Spreadsheet with all health data of this blog

Humor: Peanuts: Risk Free

2011-11-12T16:37:00.002+01:00

Risk free rates are an illusion. Risk free is an illusion. Everything in life is 'Free Risk'.... . Don't think about Risk as 'Peanuts'... It's not, as Charlie Brown, Snoopy and Woodstock show...

How to catch Risk?

2011-11-10T05:06:00.003+01:00

Desperate attempts to catch Risk in new regulatory standards like Basel (II/III) for banks and Solvency (II) for insurers seem a dead end street....

What is happening?

That's the question we're about to answer in this blog!

Here are some observations:

Risk Weighting
All new risk valuating standards are based on Risk Weighting. Some assets (or liabilities) are assumed to be more risky than others. In practice, every asset class that has been identified as more or less 'safe', has turned out to be risky after all. E.G., government bonds where - until the 2011 crisis in Greece - assumed to be risk free. Unfortunately, nothing could be further from the truth...

Nothing in life is risk free
Tier Ratio's
Instead of simple 'Equity to Asset Ratios', Tier 1 & 2 ratios where developed. These Tier ratios only take a fraction of the total assets into account. This leads to 'Equity to Risk-Weighted Assets Ratios' that insinuate adequate, substantial and reassuring 10-15% Capital ratios, while - in fact - they're not! These kind of ratios are misleading and create a false sense of safety....

Tier Ratios lead people up the garden path
Tail Hide and Seek
As more and more risks are valued, regulated and urge for extra capital requirements, financial institutions will try to create extra return on risks that are formally not or only 'light weighted' measured. This way substantial risks are 'pushed' into the tail, fat risk tails are created and the sight on the real risks in the company becomes misty.

Overregulation decreases the effect of good risk management

Illustration: Comparison 'Deutsche Bank' - 'Bank of America'
To illustrate what is happening, let's compare a giant like "Deutsche Bank" (DB) with the number one on the banking list, the "Bank of America" (BOA).

Financial Ratios	Deutsche Bank		Bank of America
(x 1 bn $) Year:	2010	2009	2010	2009
Assets (A)	1906	1501	2265	2230
Liabilities (L)	1855	1463	2037	1999
Shareholder Equity (SE)	49	37	228	231
SE / A - Ratio	2.6%	2.4%	10.1%	10.4%
---------------------------------
Risk-Weighted Assets (RWA)	346	273	1456	1543
Assets (A)	1906	1501	2265	2230
RWA / A - Ratio	18%	18%	64%	69%
---------------------------------
Regulatory Capital (RC)	49	38	230	226
Risk-Weighted Assets (RWA)	346	273	1456	1543
Total Capital Ratio	14.1%	13.9%	15.8%	14.7%
---------------------------------
Tier 1 capital	43	34	164	160
Risk-Weighted Assets (RWA)	346	273	1456	1543
Tier 1 Capital Ratio	12.3%	12.6%	11.2%	10.4%

Although both banks have more or less the same 'Tier 1' and 'Total Capital Ratio', their individual risk profile is completely different.

In the case of DB only 18% of the assets are assumed (marked) risky, while in the case of BOA around 64% is assumed risky and taken into account for a risk weighted solvency approach.

Notice that the simple gross 'Equity to Asset' Ratio (E/A-Ratio, or in short 'EAR') of DB is only 2.6%, while the similar ratio of BOA is around 10.1%. If DB would be hit by an 5% impact loss, it would be in deep trouble.

Reflections

Our risk models have become too sophisticated and don't cover the area of 'Unkown Risk' enough. Unintentionally rand controversially, risk regulations and models make us implicitly sweep our real risks under the carpet. In principle Risks can be categorized as:

Known Risk Measured
Known Risk Unmeasured
Unknown Risk
Hidden Risk (knowingly or unknowingly)

It's time to admit that no asset or liability is completely free of risk and there's an overall substantial probability that risk - by definition - will hit eventually from an unexpected corner. To put things in perspective: In the 19th century, banks funded their assets with around 40-50% equity.

Conclusion
Including 'Unkown Risk', a simple gross E/A-Ratio (EAR) of a magnitude of 15-25% (across the total assets) would probably be the best kind of guarantee to accomplish a more sustainable financial system in the world. The new EAR could be best defined as the sum of an actuarial underpinned percentage on basis of the underlaying calculable covered risks and a TBD overall 10% 'add up' for unknown risks:

E/A-Ratio = EAR = EAR_{[ calculable risk ]} + EAR_{[ unknown risk ]}

Until we've included Unkown Risk fully in our risk models, we'll stay in deep trouble.

Aftermath: 'Avatar Ratios'
To rate a company (bank), often it's not enough to look at just the traditional financial ratios. An interesting way to additionally rate a company in a more sophisticated way, is with the help of so - by me - called 'Avatar Ratios'.

Additional to financial ratios, 'Avatar Ratios' tell you more about what the intentions, (real) important issues and the 'drive' of a company and its employees are.

An 'Avatar Ratio Analysis' gives you more or less 'the embodiment' of all what drives a company. It can be constructed by making a word analysis of a crucial document or annual report of a company. In short: You simply download the annual report (or any other company characteristic document) and analyze it with a 'Word Frequency Counter' like WriteWords.

IAA Demo
As a demo, let's analyze the IAA's Strategic Plan

Frequency	Word
21	actuarial
10	strategic
10	develop
8	associations
6	standards
6	priorities
6	plans
6	objective
6	action
5	promote
5	profession
5	member
5	international
5	iaa
5	association
4	practice
4	maintain
4	key
4	global
4	encourage
4	education
3	worldwide
3	statement
3	relationships
3	plan
3	including
3	identify
3	establish
3	common
3	discussion
2	world
2	values
2	supranational
2	support
2	services
2	risk
2	relevant
2	provide
2	program
2	professionalism
2	professional
2	prioritize
2	principles
2	organizations
2	organization
2	mission
2	march
2	management
2	links
2	issues
2	internationale
2	help
2	fields
2	facilitate
2	countries
2	contact
2	conduct
2	areas
2	area
2	approved
2	among
2	actuaries
2	actuarielle
1	voluntary
1	vision
1	understanding
1	transparency
1	traditional
1	stakeholders
1	soundness
1	society
1	social
1	skills
1	sections
1	scope
1	scientific
1	role
1	review
1	research
1	reputation
1	relationship
1	regional
1	recommended
1	recognized
1	recognition
1	quality
1	public
1	protection
1	promotion
1	process
1	procedures
1	presidents
1	offered
1	objectivity
1	objectives
1	needs
1	model
1	members
1	knowledge
1	jurisdictions
1	involvement
1	integrity
1	improve
1	guidelines
1	forums
1	forum
1	financial
1	feasibility
1	experiences
1	expansion
1	examine
1	ensure
1	enhance
1	disciplinary
1	developing
1	developed
1	designation
1	decisions
1	decision
1	credential
1	create
1	cooperation
1	convergence
1	contributing
1	continuing
1	constructing
1	code
1	changing
1	availability
1	audiences
1	active
1	achieve
1	accountability
1	access

With the help of WriteWords we first create (on line) a frequency table. Next we cut out irrelevant words like 'and', 'the', etc.

Here are the results:
(1) a scrollable frequency table of all relevant words
(2) a 'Top 22 words' frequency table

In most cases - like this one - the result of simply putting the first 10 to 15 words in the top of the frequency table behind each other, is astonishing: It creates a kind of 'Identity Statement'. Here's the result for IAA's strategic plan, where even more than 20 words give a beautiful comprised identity statement:

IAA's Strategic Plan (Identity Statement comprised with WriteWords)
Actuarial strategic develop associations. Standards, priorities plans objective action. Promote profession member international. IAA association practice maintain key. Global encourage education worldwide.

Avatar Analysis: Comparison 'Deutsche Bank' - 'Bank of America'

Let's now go back to our banking case and compare 'Deutsche Bank' (DB) and the 'Bank of America' (BOA) with the help of a simple Avatar Ratio Analysis.

The Avatar Ratio Analys presents the word frequency (absolute numbers) and their relative frequency (= word frequency / total number of word in document). Here is the result:

Avatar Ratios	Deutsche Bank		Bank of America
	Freq.	Perc.	Freq.	Perc.
Governance	109	0.06%	25	0.02%
Risk	1458	0.79%	852	0.53%
Control	273	0.15%	156	0.10%
Total G+R+C	1840	1.00%	1033	0.64%
------------------
Client/Customer	359	0.20%	250	0.15%
Shareholder	169	0.09%	162	0.10%
------------------
Transparent	15	0.01%	2	0.00%
------------------
Employee	153	0.08%	63	0.04%
Director	40	0.02%	23	0.01%
------------------
Profit, Income	1001	0.54%	835	0.52%
------------------
Tot. nr. of words	161579	100%	184048	100%

Although I'll leave the final conclusions up to you, here are some remarkable observations:

Total number of words
Both companies (DB and BOA) need an enormous amount of words to explain their environment (clients, shareholders, rating agencies, etc) the essentials about what's going on in their company in a modest calendar year.

To read an annual report of about 170,000 words, it would take an average reader (reading speed 200 to 250 words per minute) about 10-12 hours.

Perhaps you, as an actuary, can read faster ( test it!: speed reading test ), but even at a speed of 500 wpm it would be an enormous task (5-6 hours) to fulfill.
Governance, Risk & Control
It's clear that DB puts much more energy (+60%) in communicating about themes as Governance Risk and Control than BOA. Also is clear that DB is far more transparent in its communication than BOA. This does (of course) not imply that BOA's risk and control frame is inferior to DB's. It could even be the opposite. It just shows that (and how) BOA handles and communicates differently (less open) from DB.
Profit, Income, Shareholders + Clients and Employees
DB and BOA weight Profit, Income and shareholders on more or less the same level. Both rank client/customer above shareholders. DB gives 'clients/customers' as well as employees double the attention of BOA!

At last
Next time you report to your board, include an Avatar Analysis of your report in your presentation!

Humor: FoxTrot Actuarial Models

2011-11-02T22:26:00.000+01:00

Sources:
- Foxtrot Comic Strips
- Foxtrot on Gocomics

Sustainable Discount Rates

2011-11-01T13:37:00.009+01:00

Steering pension funds on a 'one point' Coverage Ratio is like trying to proof global warming on a hot summer day...... It's useless.

Why?

First of all the complete pension fund balance sheet is based on market value.

As there is no substantial market for pension liabilities, this implies that pension liabilities have to be valued on basis of some kind of arbitrary (artificial) method.

In the U.S. this has led to the (irresponsible) high discount rate of 8% for state pension funds based on the 'expected' long term return without a kind of correction (subtraction) for 'risk'.

In de Dutch market, pension funds have to rate their liabilities on basis of a maturity dependable risk free interest rate, the ‘Nominal interest Rate Term Structure’ (RTS), as ordered by DNB (the Dutch Regulator).

Here's the outcome of this risk free interest rate (RTS) over the past 10 years, including the 10-y average RTS...

Ever since DNB ordered this 'artificial discounting method', pension fund board members didn't get a good night sleep. As the RTS juggles on a daily basis, every morning pension members wake up with the latest 'RTS news surprise of the day'.

You can play the RTS juggle (worm) here:

As coverage ratios are based on the RTS, they shuttle hither and thither as well and executing a long term pension fund strategy becomes more or less like riding the famous (market) bull in a rodeo show.

On a Dutch IPE congress, Angelien Kemna - chief investment officer of the €270bn asset manager APG - warned that the current swap-curve discount criterion forces pension funds to take unwise "significant long-term measures".

Kemna favors an average yield curve or a more straightened version of the current one for discounting liabilities.

The new Dutch Pensions Agreement foresees that pension funds can choose their own discount rate, as pensions are no longer guaranteed!

Indeed, it's time to stop this complex discount circus. But it's also time to stop 'one point estimate' Coverage Ratio steering.

A new look
Let's take a look at a characteristic discount rate dependence of a traditional pension fund like ABP.

Valuing ABP at an (derived average) RTS of 2.69% (September 2011), ABP's discounted assets fail to meet the discounted liabilities, leading to a coverage ratio of around 90%.

However this kind of risk free valuing is - for sure - too conservative, as ABP's aims at an underpinned strategic expected return of 6,1% on the long term and has a convincing track record of 5 and 10-year moving average returns:

Returns (%) Pension Fund ABP 2993-2010
Year	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010
Yearly Return	16.5	-1.0	16.4	11.8	11.9	12.9	10.0	3.2	-0.7	-7.2	11.0	11.5	12.8	9.5	3.8	-20.2	20.2	13.5
5Y MA Return					10.9	10.2	12.6	9.9	7.3	3.4	3.0	3.3	5.2	7.2	9.7	2.7	4.2	4.4
10Y MA Return										7.1	6.6	7.8	7.5	7.3	6.5	2.9	3.8	4.8

Or in Graphics:

As long as a pension fund (like ABP) continues to perform (on 5 or 10-years moving average) rates that outperform the (derived average) risk free discount rate, it's seems ridiculous to force such a pension fund to discount at a 'risk free rate', as this obliges the fund to change his strategic asset mix to a less risky mix and an suboptimal return.
In turn, these suboptimal returns will lead to an asset shortage. With a vicious cycle of decreasing risk as a fatal result in the end.

Sustainable Discount Rates
In an excellent discussion paper (2006) Jürg Tobler-Oswald proves that the optimal discount rate lies between the risk free rate (RFR) and the investment strategy’s expected return (ER) depending on how good the hedge against the fund’s cash flow provided by its investments is:

Discount Rate₁ = RFR + F_{Cash Flow}(RFR-ER)

Another - more simple and practible - discount rate could be defined as the average between the free discount rate and the X-year (e.g. X=5, or 10) Moving Average Return of the last X-Years (MAR(X)).

Discount Rate₂ = [ RFR + MAR(X) ] /2

As long as MAR(10), MAR(5) and ER stay larger than the interest rate that matches a coverage ratio of 100%, discounting by means of one of the new sustainable discount methods seems sound and safe......

Whats left is that the average (geometric) risk premiums during the last 10 years have turned out negative:

Historical Equity Risk Premiums (ERP)
	ERP: Stocks minus T.Bills		ERP: Stocks minus T.Bonds
Period	Arithmetic	Geometric	Arithmetic	Geometric
1928-2010	7.62%	5.67%	6.03%	4.31%
1960-2010	5.83%	4.44%	4.13%	3.09%
2000-2010	1.37%	-0.79%	-2.26%	-4.11%

This implies (moreover) that it is important that the discounting rate of a pension fund should be based on a sustainable sound weighted mix of:
(1) proven historical performance
(2) a 'save' risk free rate
(3) realistic future return assumptions

Related Links/ Sources
- Kemna IPE article (2011)
- An investment based valuation approach for pension fund cash flows (2006)
- Ignoring the risk in risk premium in State Pensions(2011)
- DB: What went wrong? (2011)
- Actuary.org: Pension Fund Valuation and Market Values (2000)
- Aswath Damodaran: Equity-risk-premiums-2011-edition
- Dutch: ABP coverage ratio

What's a Greek Tragedy?

2011-10-23T01:07:00.001+02:00

As actuaries we do not believe in miracles, or do we?

According to a 'strictly confidential' document from the Troika (= EC, IMF & ECB), Greek's Debt/GDP ratio suddenly raised from 149% to 186% in 2013!

This new insight causes a 'potential need for additional official financing' ranging up to €440 billion!! (are you still with me?)

Let's take a look at how Debt/GDP ratio developed in the past and the new optimistic Troika forecast (red line).

Just to help the Troika, I've added a non-miracle 'Maggid' forecast based on simple and more realistic economic principles.

Not a word in the Troika report about the drivers and cultural changes that are necessary to achieve a long term decrease of the Debt/GDP ratio. Everything is based on suggestive mathematical art.

Continue throwing good money after bad, is not the way forward. Greece will first have to show that it is not only willing, but also achieving debt reduction. Current measures are insufficient. Start for example to raise retirement age to 65 as a beginning...

Let's pray European leaders give up Keynesian miracle thinking and take the right decision:

Stop helping Greece to finance their debt, unless Greece shows strong progress in reducing debt itself every month .

If not.., the line 'A Greek Tragedy' will get a new meaning....

Sources/Links:
- Troika report
- Zerohedge: Greece
- Retirement around the globe blog

Humor: Actuary Scrooge

2011-10-14T22:32:00.001+02:00

Today's Brainer:What's the difference between a pension fund and an investment fund?

Actuary $crooge shows...

source

On Line DIY European Stress Test

2011-10-09T09:34:00.000+02:00

Thomson Reuters' Breakingviews now presents an on line DIY stress test. Change the Tier 1 ratio and haircuts of the PIIGS countries and find out the capital shortfall of Europe and the shortfal of individual European banks.

An explanation can be found here and there is also an Excel spreadsheet.

Enjoy stress testing!

What's a world without Jobs?

2011-10-08T08:50:00.003+02:00

On Wednesday night 5th October, Apple co-founder, former CEO and chairman Steve Jobs, passed away..

Steve Jobs' life is an example to all of us. In an excellent and catching speech, Steve urged graduates to pursue their dreams and pick up the opportunities in life's setbacks at the university's 114th Commencement on June 12, 2005.

What - besides Steve's phenomenal contributions to computer technology and marketing - did Steve contribute to the profession of Risk Management?

Steve Jobs' Risk Management Lessons
Here are (derived from his 2005 Stanford speech) some inspiring lessons from Steve. Lessons we can apply 'one to one' on Risk Management (my comments in Italic):

Connect 'the dots' in life
It's impossible to connect the dots looking forward,you can only connect them looking backwards, later in life. Do so!

To turn Risk Management into an opportunity, we can't look in a crystal ball. We'll have to explore and have to allow ourselves some experiments and non-conventional ideas to finally see the bigger picture that turns marginal new business developments into one new final integral success!

Try to develop 'Risk Oversight' (connecting the dots) as Risk Oversight is negatively related to risk and positively related to shareholder value (Research Stanford University).
Trust
You have to trust that the dots will somehow connect in your future.
Believe in something and follow your heart, even if it leads you of the well-worn path..

Make Risk management supportive and not dominant to what you want to achieve in life or business. It's positive when companies Ideas and Vision sometimes conflict with inner and outer notions.

To grow a plant (company) in soil (society) is takes opposite 'nutrients' (and circumstances) like water and sun that feed your seed (idea).

Accept that your heart, gut feeling and helicopter view are sometimes more leading than the rationale of your Risk management (what your brain thinks). The more and the longer you are able to manage this paradox, the more likely success will come your way eventually.

Keep all the above decision elements in ('a paradoxical') place. Remember Shareholder Value and Sustainability are a function of Risk, so don't pull the plug too soon!
Love and Loss
Making mistakes is an inherent part of life and doing business.

If you (or something you started) fails, start over!

The effect of less sureness by 'starting over', inspires for exploring new directions and becoming creative again.

'Love what you do' is the most important leading statement to proceed in life and business.

'Sometimes life hits you with a brick'. Don’t lose faith.Your time is limited, so don’t waste it living someone else’s life.

Risk Management exists by the grace of losses that occur. Accept that as a fact. Therefore, if no losses occur anymore, your Risk Management program is actually dead without a clue. It will certainly fail eventually.

Getting knocked down by a 'brick' like in the current financial crisis, is a sign that we have to redesign our Risk Management programs instead of intensifying existing programs like Basel II /III and Solvency II. Get out!

New Risk Management will have to focus on how to prevent and to DEAL with risk, instead of sophisticated capitalizing risk as Dead Risk Capital. Rather than focus on reducing risk, risk-transformation — that is, capitalizing risk in such a way that its value creation potential is maximized - seems the right way forward.
Death
If you live each day as if it was your last, someday you'll most certainly be right. Remembering you'll die is the most important tool to help you make the big choices in life. Because almost everything — all external expectations, all pride, all fear of embarrassment or failure - these things just fall away in the face of death, leaving only what is truly important.

Remembering that you are going to die is the best way to avoid the trap of thinking you have something to lose.

Risk Management is about making choices and giving up less important issues for more important.
It's about generating focus on what really matters for sustainability or results, instead of trying to manage everything.

Good Risk management therefore urges for CEO and Board rewards that reflect the downside risk of a company's default instead of just rewarding upward and short term profit.

Company bonuses should therefore be positive as well as negative performance related.

Remember, just like Steve Jobs, Risk Management is about 'failing better than anyone else' .....

Related/Sources:
- Steve Jobs: He Thinks Different (2004)
- Was Steve Jobs Practicing Proactive Risk Management? (2010)
- The Role of the Board in Corporate Risk Oversight (Stanford University 2010)
- Dead Risk Capital

Pension Gamification

2011-09-29T20:07:00.004+02:00

For years you deny it, then you doubt it, then you know for sure:

Life is a Game

This blog is specially written for (1) those who are still in the denial phase and (2) 'actuarial life gamers' who just want to enjoy actuarial gaming....

Pension Game
Games are an excellent way to involve people (employees) in a complex and (two fold) 'low interest product' like pension.

Pension games stimulate clear communication and understanding of pensions (The Nest Phrasebook:Clear communication about pensions Version 1.1).

Games, like the above pension game, conquer the world more and more.

Gamification
It looks like everything that has to be sold or communicated, succeeds better with the help of a game. Gamification gets people more engaged, helps change behaviors and stimulates innovation. In other words:

Gamification rules our life

As an example of gamification, Gartner cited the U.K.’s Department for Work and Pensions, which created an innovation game called Idea Street to decentralize innovation and generate ideas from its 120,000 people across the organization. Idea Street is a social collaboration platform with the addition of game mechanics, including points, leaderboards and a “buzz index.”

The employees went wild for it. Within 18 months, Idea Street had approximately 4,500 users and had generated 1,400 ideas, 63 of which had gone forward to implementation.

Other gamification examples are the U.S. military’s “America’s Army” video-game recruiting tool, and the World Bank-sponsored Evoke game, which crowdsources ideas from players globally to solve social challenges.

All and more of this in the 2011 report of Gartner that states that by 2015, more than 50% of organizations tat manage innovation processes will gamify those processes.

Consequences

Mainly as a consequence of the overdose of gamification in our society, people get confused and lose sight on the difference between reality and illusion.

This confusion is exacerbated by the fact that negative effects of the current financial crisis have been 'managed away' in stead of letting people and organizations 'perceive' and 'experience' the (negative) financial consequences of their handling.

The 'Hocus Pocus Society'

This way, we gradually created a 'Hocus Pocus Society' where all our (actuarial) models and convictions are doomed to fail as the 'game of life' seems to be to:

challenge the established (good governance) rules to raise profit and returns to an unrealistic level, by introducing uncontrolled and uncontrollable mechanisms and financial instruments like 'market value', 'derivatives', 'sub-prime mortgages', 'High Frequency Trading', etc.
try - at the same time - to capture and control these volatile 'unwanted' effects of these mechanisms and instruments by an overdose of hypocritical additional regulation (Solvency (II), Governance, etc.)
transfer and lay back fundamental complex risk to consumers and communicating this in such a (so called) 'transparent' but oversimplified 'way', that consumers for sure lose their trust in financial institutions as a whole.
end up in new, for the financial institutions, 99,9% risk free financial products and offerings on the marketplace with a non corresponding stock holders dividend level.

This illusory way of communication about pensions is well demonstrated in the next 'Pension game' video: The myth of your (401K) pension

Way out

To get out of this down spiral cycle in the fiancial industry, we'll have to learn from other industries.

Just like in the case of introducing new medicines , new financial products will have to meet a number of tests and need explicit approval by in and external regulators before they are allowed to be introduced on the market place.

Anyhow: Don't end up like a 'Hocus Pocus Actuary' and game up your actuarial life!

Related and additional links:
- Idea Street
- Gartner: Over 50% firms may gamify processes
- Youtube: The Pension Game
- The Annuity Game - Heads Government Wins Tails Pensioner's Lose
- 5 Cent "Old Age Pension" Dice Game

Calculators:
- life expectancy calculator
- Retirement Withdrawal Calculator

Small Population Compliance Samples

2011-09-26T22:28:00.002+02:00

My last post, Compliance Sample Size, demonstrated the set up of an efficient sample method for compliance tests in case of large populations.

What if population size is relatively small ?, some actuaries asked me....

In this case you can ( instead of the beta distribution) make use of the hypergeometric distribution for calculating confidence levels.

Here's the same example as I used in my blog 'Compliance Sample Size', but now for a population of 100 .

'Compliance Check' Example (N=100)
As you probably know, pension advisors have to be compliant and meet strict federal, state and local regulations.

On behave of the employee, the sponsoring employer as well as the insurer or pension fund, all have a strong interest that the involved 'Pension Advisor' actually is, acts and remains compliant.

PensionAdvice
A professional local Pension Advisor firm, 'PensionAdvice' (fictitious name), wants 'compliance' to become a 'calling card' for their company. Target is that 'compliance' will become a competitive advantage over its rivals.

You, as an actuary, are asked to advise on the issue of how to verify PensionAdvice's compliance....... What to do?

Step 1 : Compliance Definition
First you ask the board of PensionAdvice what compliance means.
After several discussions compliance is in short defined as:
1. Compliance Quality
  Meeting the regulator's (12 step) legal compliance requirements
  ('Quality Advice Second Pillar Pension')
2. Compliance Quantity
  A 100% compliance target of PensionAdvice's portfolio, with a 5% non-compliance rate (error rate) as a maximum on basis of a 95% confidence level.
.
Step 2: Check on the prior believes of management
On basis of earlier experiences, management estimates the actual NonCompliance rate at 8% with 90% confidence that the actual NonCompliance rate is 8% or less:

If management would have no idea at all, or if you would not (like to) include management opinion, simply estimate both (NonCompliance rate and confidence) at 50% (= indifferent) in your model.
Step 3: Define Management Objectives
After some discussion, management defines the (target) Maximum acceptable NonCompliance rate at 5% with a 95% confidence level (=CL).
Step 4: Define population size
In this case it's simple. PensionAdvice management knows for sure the portfolio they want to check for compliance, consists of 100 files: N=100.

This is how step 2 to 4 look in your spreadsheet...
Step 5 : Define Sample Size
Now we get to the testing part....

Before you start sampling, please notice how prior believes of management are rendered into a fictitious sample (test number = 0) in the model:

In this case prior believes match a fictitious sample of size 25 with zero noncompliance observations.
This fictitious sample corresponds to a confidence level of 77% on basis of a maximum (population) noncompliance rate of 5%.

[ If you think the rendering is to optimistic, you can change the fictitious number of noncompliance observations from zero into 1, 2 or another number (examine in the spreadsheet what happens and play around).]

To lift the 77% confidence level to 95%, it would take an additional sample size of 20 - with zero noncompliance outcomes (you can check this in the spreadsheet).
As sampling is expensive, your employee Jos runs a first test (test 1) with a sample size of 10 with zero noncompliance outcomes. This looks promising!
The cumulative confidence level has risen from 76% to over 89%.

You decide to take another limited sample with a sample size of 10. Unfortunately this sample contains one noncompliant outcome. As a result, the cumulative confidence level drops to almost 75% and another sample of size 20 with zero noncompliant outcomes is necessary to reach the desired 95% confidence level.

You decide to go on and after a few other tests you finally arrive at the intended 95%cumulative confidence level. Mission succeeded!

Evaluation
The interesting aspects of this method are:

Prior (weak or small) samples or beliefs about the true error rate and confidence levels, can be added in the model in the form of an (artificial) additional (pre)sample.
As the sample size increases, it becomes clear whether the defined confidence level will be met or not and if adding more samples is appropriate and/or cost effective.

This way unnecessary samples are avoided, sampling becomes as cost effective as possible and auditor and client can dynamically develop a grip on the distribution. Enough talk, let's demonstrate how this works.

Another great advantage of this incremental sampling method is that if noncompliance shows up in an early stage, you can

stop sampling, without having made major sampling cost
Improve compliance of the population by means of additional measures on basis of the learnings from the noncompliant outcomes
start sampling again (from the start)

If - for example - test 1 would have had 3 noncompliant outcomes instead of zero, it would take an additional test of size 57 with zero noncompliant outcomes tot achieve a 95% confidence level. It's clear that in this case it's better to first learn from the 3 noncompliant outomes, what's wrong or needs improvement, than to go on with expensive sampling against your better judgment.

D. Conclusions

On basis of a prior believe that - with 90% confidence - the population is 8% noncompliant, we can now conclude that after an additional total sample of size 40, PensionAdvice's noncompliance rate is 5% or less with a 95% confidence level.

If we want to be 95% sure without 'prior believe', we'll have to take an additional sample of size 25 with zero noncompliant outcomes as a result.

E. Check out: DOWNLOAD EXCEL
You can download the next Excel spreadsheets to check the Demo or tot set up your own compliance test:

- Small population Compliance test DEMO
- Small population Compliance test BLANK
- Large population Compliance test

Enjoy!

Compliance: Sample Size

2011-09-25T08:29:00.080+02:00

How to set an adequate sample size in case of a compliance check?

This simple question has ultimately a simple answer, but can become a "mer à boire" (nightmare) in case of a 'classic' sample size approach.....

In my last-but-one blog called 'Pisa or Actuarial Compliant?', I already stressed the importance of checking compliance in the actuarial work field.

Not only from a actuarial perspective compliance is important, but also from a core business viewpoint:

Compliance is the main key driver for sustainable business

Minimizing Total Cost by Compliance
A short illustration: We all know that compliance cost are a part of Quality Control Cost (QC Cost) and that the cost of NonCompliance (NC Cost) increase with the noncompliance rate.

Mainly 'NC cost' relate to:

Penalties or administrative fines of the (legal) regulators
Extra cost of complaint handling
Client claims
Extra administrative cost
Cost of legal procedures

Sampling costs - on their turn - are a (substantial) part of QC cost.

More in general now it's the art of good practice compliance management, to determine that level of maximal noncompliance rate, that minimizes the total cost of a company.

Although this approach is more or less standard, in practice companies revenues depend strongly on the level of compliance. In other words: If compliance increases, revenues increase and variable costs decrease.

This implies that introducing 'cost driven compliance management' - in general - will (1) reduce the total cost and (2) mostly make room for additional investments in 'QC Cost' to improve compliance and to lower variable and total cost.

In practice you'll probably have to calibrate (together with other QC investment costs) to find the optimal cost (investment) level that minimizes the total cost as a percentage of the revenues.

As is clear, modeling this kind of stuff is no work for amateurs. It's real risk management crafts-work. After all, the effect of cost investments is not sure and depends on all kind o probabilities and circumstances that need to be carefully modeled and calibrated.

From this more meta perspective view, let's descend to the next down to earth 'real life example'.

'Compliance Check' Example
As you probably know, pension advisors have to be compliant and meet strict federal, state and local regulations.

On behave of the employee, the sponsoring employer as well as the insurer or pension fund, all have a strong interest that the involved 'Pension Advisor' actually is, acts and remains compliant.

PensionAdvice
A professional local Pension Advisor firm, 'PensionAdvice' (fictitious name), wants 'compliance' to become a 'calling card' for their company. Target is that 'compliance' will become a competitive advantage over its rivals.

You, as an actuary, are asked to advise on the issue of how to verify PensionAdvice's compliance....... What to do?

Step 1 : Compliance Definition
First you ask the board of PensionAdvice what compliance means.
After several discussions compliance is in short defined as:
1. Compliance Quality
  Meeting the regulator's (12 step) legal compliance requirements
  ('Quality Advice Second Pillar Pension')
2. Compliance Quantity
  A 100% compliance target of PensionAdvice's portfolio, with a 5% non-compliance rate (error rate) as a maximum on basis of a 95% confidence level.
The board has no idea about the (f)actual level of compliance. Compliance was- until now - not addressed on a more detailed employer dossier level.
Therefore you decide to start with a simple sample approach.
Step 2 : Define Sample Size
In order to define the right sample size, portfolio size is important.
After a quick call PensionAdvice gives you a rough estimate of their portfolio: around 2.500 employer pension dossiers.

You pick up your 'sample table spreadsheet' and are confronted with the first serious issue.
An adequate sample (95% confidence level) would urge a minimum of 334 samples. With around 10-20 hours research per dossiers, the costs of this size of this sampling project would get way out of hand and become unacceptable as they would raise the total cost of PensionAdvice (check this, before you conclude so!).

Lowering confidence level doesn't solve the problem either. Sample sizes of 100 and more are still too costly and confidence levels of less than 95% are of no value in relation to the clients ambition (compliance= calling card).
The same goes for higher - more than 5% - 'Error Tolerance' .....

By the way, in case of samples for small populations things will not turn out better. To achieve relevant confidence levels (>95%) and error tolerances (<5%), samples must have a substantial size in relation to the population size.

You can check all this out 'live', on the next spreadsheet. Use the 'Click to Edit' button to change the next spreadsheet to modify sampling conditions to your own needs. If you don't know the variability of the population, use a 'safe' variability of 50%. Click 'Sample Size II' for modeling the sample size of PensionAdvice.

Step 3: Use Bayesian Sample Model
The above standard approach of sampling could deliver smaller samples if we would be sure of a low variability.

Unfortunately we (often) do not know the variability upfront.

Here comes the help of a method based on efficient sampling and Bayesian statistics, as clearly described by Matthew Leitch.

A more simplified version of Leitch's approach is based on the Laplace's famous 'Rule of succession', a classic application of the beta distribution ( Technical explanation (click) ).

The interesting aspects of this method are:
1. Prior (weak or small) samples or beliefs about the true error rate and confidence levels, can be added in the model in the form of an (artificial) additional (pre)sample.
2. As the sample size increases, it becomes clear whether the defined confidence level will be met or not and if adding more samples is appropriate and/or cost effective.

Sample Demonstration

The next sample is contained in an Excel spreadsheet that you can download and that is presented in a simplified Zoho spreadsheet at the end of this blog. You can modify this spreadsheet (on line !) to your own needs and use it for real life compliance sampling. Use it with care in case of small populations (n<100).

A. Check on the prior believes of management

Management estimates the actual NonCompliance rate at 8% with 90% confidence that the actual NonCompliance rate is 8% or less:

If management would have no idea at all, or if you would not (like to) include management opinion, simply estimate both (NonCompliance rate and confidence) at 50% (= indifferent) in your model.

B. Define Management Objectives

After some discussion, management defines the (target) Maximum acceptable NonCompliance rate at 5% with a 95% confidence level (=CL)

C. Start ampling
Before you start sampling, please notice how prior believes of management are rendered into a fictitious sample (test number = 0) in the model:

In this case prior believes match a fictitious sample of size 27 with zero noncompliance observations.
This fictitious sample corresponds to a confidence level of 76% on basis of a maximum (population) noncompliance rate of 5%.

[ If you think the rendering is to optimistic, you can change the fictitious number of noncompliance observations from zero into 1, 2 or another number (examine in the spreadsheet what happens and play around).]

To lift the 76% confidence level to 95%, it would take an additional sample size of 31 with zero noncompliance outcomes (you can check this in the spreadsheet).
As sampling is expensive, your employee Jos runs a first test (test 1) with a sample size of 10 with zero noncompliance outcomes. This looks promising!
The cumulative confidence level has risen from 76% to over 85%.

You decide to take another limited sample with a sample size of 10. Unfortunately this sample contains one noncompliant outcome. As a result, the cumulative confidence level drops to almost 70% and another sample of size 45 with zero noncompliant outcomes is necessary to reach the desired 95% confidence level.

You decide to go on and after a few other tests you finally arrive at the intended 95%cumulative confidence level. Mission succeeded!

The great advantage of this incremental sampling method is that if noncompliance shows up in an early stage, you can

stop sampling, without having made major sampling cost
Improve compliance of the population by means of additional measures on basis of the learnings from the noncompliant outcomes
start sampling again (from the start)

If - for example - test 1 would have had 3 noncompliant outcomes instead of zero, it would take an additional test of size 115 with zero noncompliant outcomes tot achieve a 95% confidence level. It's clear that in this case it's better to first learn from the 3 noncompliant outomes, what's wrong or needs improvement, than to go on with expensive sampling against your better judgment.

D. Conclusions

On basis of a prior believe that - with 90% confidence - the population is 8% noncompliant, we can now conclude that after an additional total sample of size 65, PensionAdvice's noncompliance rate is 5% or less with a 95% confidence level.

If we want to be 95% sure without 'prior believe', we'll have to take an additional sample of size 27 with zero noncompliant outcomes as a result.

E. Check out
Check out 'on line', the next spreadsheet. Use the 'Click to Edit' button to change the sample spreadsheet to modify sampling conditions to your own needs or download the Excel spreadsheet.

Finally
Excuses for this much too long blog. I hope I've succeeded in keeping your attention....

Related links / Resources

I. Download official Maggid Excel spreadsheets:
- Dynamic Compliance Sampling (2011)
- Small Sample Size Calculator

II. Related links/ Sources:
- 'Efficient Sampling' spreadsheet by Matthew Leitch
- What Is The Right Sample Size For A Survey?
- Sample Size
- Epidemiology
- Probability of adverse events that have not yet occurred
- Progressive Sampling (Pdf)
- The True Cost of Compliance
- Bayesian modeling (ppt)

Humor: Actuarial Stress Test

2011-09-14T22:32:00.000+02:00

Calvin and Hobbes as Manager and Actuary....

Original source: Tonks17
Homepage UK Calvin and Hobbes

Pisa or Actuarial Compliant?

2011-09-12T00:39:00.001+02:00

When we talk about actuarial compliance, we usually limit this to our strict actuarial work field.
In a broader sense as 'risk managers', we (actuaries) have a more general responsibility for the sustainability of the company we work for.

Compliance is not just about security, checks, controls, protection, preventing fraud, ethical behavior. Moreover compliance is the basis of adequate risk management and delivering high standard service and products to your companies clients.

Pisa Compliant
No matter how brilliant and professional our calculations, if the data - on which these calculations are based on - are 'limited', 'of insufficient quality' or 'too uncertain', we as actuaries will finally fail.

Therefore , building actuarial sandcastles is great art, however completely useless. Matthew 7:26 tells us : it's a foolish man who builds his actuarial house on the sand....

And so, let's take a look if we have indeed become 'Pisa Compliant' by checking if our actuarial compliance is build on sand or on solid ground. In other words: let's check if actuarial compliance itself is compliant...nd.

Actuarial Data Governance
To open discussion, let's start with some challenging Data Governance questions:

Data quality compliance
How is 'data quality compliance' integrated in your actuarial daily work? Have you addressed this issue? And if so, do you just rely on statements and reports of others (auditors, etc), can you agree upon the data quality standards (if there are any). In other words: are the data, processes and reports you base you calculations on, 100% reliable and guaranteed? If not, what's the actual confidence level of your data en do you report about this confidence level to the board?
Data quality Conformation
Have you checked your calculation data set on bases of samples or second opinions?

And if so, do you approve with the methods used, the confidence level and the outcome of the data audit?

Or do you just 'trust' on the blue eyes of the accountant or auditor and formally state you're "paper compliant"?

Did you check if client information, e.g. pension benefit statement, are not only in line with the administrative data, but also in line with insurance policy conditions or pension scheme rules?
Up to date, In good time
To what quantitative level is the administrative data 'up to date' and is it transparent?

Do you receive administrative backlog and delays reporting and tracking and if so, how do you translate these findings in your calculations?
Outsourcing
From a risk management perspective, have you formulated quantitative and qualitative demands (standards) in outsourced contracts, like 'asset management', 'underwriting' and 'administration' contracts?

Do you agree on these contracts, do 'outsourcing partners' report on these standards and do you check these reports regularly on a detail level (samples)?

And some more questions you have to deal with as an actuary:

Distribution Compliance
Is the intermediary and are the employers and customers your company deals with, compliant? What's the confidence level of this compliance and in case of partially noncompliance, what could be the financial consequences? (Claims)
Communication Compliance
Is communication with employees, customers, regulators, supervisors and shareholders compliant? Has your board (and you!) defined what compliance actually means in quantitative terms?

Is 'communication compliance' based on information (delivery and check) or on communication?

In this case, have you've also checked if (e.g.) customers understood what you tried to tell them?

Not by asking if your message was understood, but by quantitative methods (tests, polls, surveys, etc) that undisputed 'prove' the customer really understood the message.

Effective Communication Practice
Never ask if someone has understood what you've said or explained. Never take for granted someone tells you he or she 'got the picture'.

Instead act as follows: At the end of every (board) presentation, ask that final and unique question of which the answer assures you, your audience has really understood what your tried to bring across.

Checking Compliance

Now we get to the quantitative 'hard part' of compliance:

How to check compliance?

This interesting topic will be considered in my next blog.... ;-)

To lift a little corner of the veil, just a short practical tip to conclude this blog:

Compliance Sample Test
From a large portfolio you've taken a sample of 30 dossiers to check on data quality. All of them are found compliant. What's the upper limit of the noncompliance rate in case of a 95% confidence level?

This type of question is a typical case of:

“If nothing goes wrong, is everything alright?”

Answer.

The upper limit can be roughly estimated by a simple rule of thumb, called 'Rule of three'....

'Rule of three for compliance tests'

If no noncompliant events occurred in a compliance test sample of n cases, one may conclude with 95% confidence that the rate of noncompliance will be less than 3/n.

In this case one can be roughly 95% sure the noncompliance rate is less than 10% (= 3/30). Interesting, but slightly disappointing, as we want to chase noncompliance rates in the order of 1%.

Working backwards on the rule of three, a 1% noncompliance rate would urge for samples of 300 or more. Despite the fact that research for 46 international organizations showed that on average, noncompliance cost is 2.65 times the cost of compliance, this size of samples is often (perceived as) too cost inefficient and not practicable.

Read my next blog to find out how to solve this issue....

Related Links:
- Actuarial Compliance Guidelines
- What Is The Right Sample Size For A Survey?
- Epidemiology
- Probability of adverse events that have not yet occurred
- The True Cost of Compliance (2011)
- 'Rule of three'
- Compliance testing: Sampling Plans (accounting standards) or Worddoc

Humor: Merkozy, It's too late

2011-09-09T23:33:00.003+02:00

Comparing 5 year exchange rates USD/EUR (decline : 17%) and USD/CNY (decline 21%) clearly shows the negative outlook of the US Dollar.

Both U.S. and Europe, are facing severe debt problems they can not solve with more debt.

Desperate actions
President Obama tries to stimulate economy by creating 1.5 mln new jobs with a $ 450 billion investment (American Job Act).

In Europe president Merkel (Germany) and Sarkozy (France) have joint their strengths and totally different characters into 'one personality', to create not only a strong financial but also economic European union.

This new economic union is necessary to establish a firm grip on the measures that weak financial European countries like, Greece, Italy, Ireland, Spain and Portugal have to take to recover from their debt.

It's too late
Unfortunately there's no support for such an initiative. Unluckily, no Merkozy will be able to prevent Europe from a financial meltdown.

The only way out seems a European split in relative strong and weak countries.

Make up your mind on the geographic spread of the assets of your company. Get out before it's too late....

Irrational Risk

2011-09-07T01:24:00.007+02:00

Actuarial work is demanding..., so you're arriving late at your hotel that night. The hotel manager has only two rooms left. These two rooms are exactly the same, except for one aspect: The fire alarm.....

The manager tells you that in the event of a nighttime fire due to the usual causes, guests in Room 1, equipped with Alarm 1, have an actuarial calculated 2% chance of dying. Guests in Room 2, equipped with Alarm 2, have only a 1% chance of dying.

However - things in life are always complicated - there's a slight problem.....

According to the manager...... The wiring of Alarm 2 is such that it sometimes causes electrical fires that increase the risk of dying in a nighttime fire by an additional 0.01%.

In other words, Alarm 1 is associated with a 2% risk of death and Alarm 2 is associated with a 1% + 0.01% (betrayal) risk of death.

What room do you choose as a professional actuary?

Outcome
According to a study by Gershoff and Koehler, most participants choose the room with Alarm 1. This, even though this room 1 has double the increased risk of fire death, according the researchers. Reason: most participants found the tiny risk of "betrayal" (product malfunction) much more frightening than the much larger risk of actually dying. When people get upset by a tiny risk, they often paradoxically choose the much larger risk.

Personally I think a more imaginable risk 'weighs' stronger than a non-specific abstract risk and in general people are unaware of conditional probability effects......

Conclusion

This simple example proofs that emotion has a strong influence on risk decisions.

Just like in our actuarial profession, risk decisions are often irrational.

It is our duty as actuaries to demystify and to rationalize risk. However, sometimes we're victim of the same emotional bias....

Read more about this interesting subject on:

- Vaccination and betrayal aversion (2011)
- Safety First? The Role of Emotion in Safety Product Betrayal Aversion (2011)

- The Risk-as-feelings hypothesis in a Theory-of-planned-behaviour
- Behavioral economics: the missing link in the financial crisis-
- Decisions are Never Emotional

U.S. Debt Autopsy

2011-08-07T00:18:00.007+02:00

Coming back from vacation, the world seems lost. You don't need to be an actuary to grasp that the recent decision to lift the U.S. debt ceiling is first class trickery and completely inadequate.

What the Chinese rating agency Dagong already concluded back in November 2010, is only now (August 5, 2011) reluctantly and partly followed by S&P:

U.S. AAA status = Dead.

It's interesting to see which countries Dagong rates lower than the three famous rating Agencies in the U.S. (download complete Dragon report).

Meanwhile Dagong downgraded the U.S. again to an ordinary A-status on august 2, 2011.

The arguments for country degrades (as the U.S.) are as much clear as simple: if lifting debt ceilings is not at the same time combined with serious debt reduction measures (spending cuts), you go DOWN!

The outlook on the U.S. is still negative.

Outlook
Let's take look at what happened during 2011 and what 2012 will bring..

This chart instantaneously makes clear what's happening:

Jan 2011 - half May 2011
Although the whole world can figure out that the original debt ceiling of $14.294 trillion will be reached within a few months, no measures or actions are taken by the U.S. Treasury to prevent a debt default,.
May 16, 2011 - August 1, 2011
Treasury Secretary Timothy Geithner informs Congress he will start tapping into federal pension funds on Monday to free up borrowing capacity as the nation hits the $14.294 trillion legal limit on its debt.

By these and (possible) other optical actions the actual debt is kept artificially stable, slightly above the first ceiling. Of course the factual debt will (non reporting or visible) continue to keep growing.
August 1&2, 2011
The U.S. House of Representatives and the U.S. Senate pass the Budget Control Act on Aug 2, 2011.The debt ceiling is immediately raised by $400 billion, to $14.694 trillion.

A second debt ceiling increase allows the current new ceiling to grow by an additional $500 billion, to $15.194 trillion, so that government can pay its bills until the end of February 2012. However, Congress has the authority to reject this second increase.
August 5, 2011 - March 2012
TresuryDirect reports show the debt catch-up effects on August 5, 2011.

Already $271 billion of the $400 billion debt ceiling lift turns out to be 'consumed'. Another $129 billion is left.

As my two year old son can calculate: If no measures will be effective, around mid September 2011 a new ceiling crisis and media lift-show shall start.

After agreeing in September to the second ceiling of $15.194 trillion the muppet debt show will start again in March 2012, when the second ceiling will break.

The party is over
I'm not a pessimistic person by nature, but the U.S. is running out of possible solutions.

It looks like the financial space flight program is over.

We'll have to build a society on new ethical financial principles.

If real measures stay out and claims on other countries or banks (as was the case with the sub prime debacle) are limited, the U.S. will unfortunately default in the end.

This U.S. default will take along most western countries.

It will result in a worldwide financial meltdown.

They only way out that seems left is:

Inflation

Let's hope for the best or a miracle. God bless America!

Related Links and Resources:
- Spreadsheet (Excel) with 2011 Debt Data
- S&P Report, August 5, 2011
- TreasuryDirect (U.S. Debt development)
- Debt Ceiling Increase of 2011
- Alert - Just So We Don't Get Confused As To The Source Of Our Little Problem

Humor: Actuarial Mind

2011-07-06T11:46:00.002+02:00

In July 2011 holidays - instead of blogs - are ahead...

Just chew this month on the next actuary no-brainer:

The smartest actuary in the world

The Pope, a well seasoned actuary and a student nurse are flying on an airplane. The captain comes back and says that he has some bad news and some really bad news. The bad news is that the plane is going to crash! As he puts on a parachute and jumps out he says that the really bad news is that there are only 2 more parachutes.

The actuary says: “I am the smartest man in the world. I've just calculated my life expectancy to be more than fifteen years. Excuse me...” With that he puts on a parachute and jumps out.

The Pope says: “Well, my child, I would love to live, but I believe that my time is up. Please take the other parachute and save yourself.”

The student nurse says: “Not to worry Holy Father. Right now the smartest man in the world is trying to find the rip-cord on my back pack!”

Impact or Probability?

2011-06-27T01:18:00.034+02:00

We all are more than familiar with the definition of Risk:

Risk = Probability × Impact= P×I

This way of measuring risk is a nice, simple, explainable and intuitive way of ordering risks in board or bath rooms, but unfortunately quite useless.

To demonstrate the limits of this kind of typical Risk definition, let's take a look at the next story:

The Risk of bicycling

You decided to start a 3 year math study at City University in London. From your brand new apartment in Southall, it's a 12.5 mile drive to the University at Southhampton Street. As a passionate cyclist you consider the risk of cycling through London for the next three years.

Based on your googled " DFT's Reported Road Casualties 2009" research (resulting in a cycling death rate of 36 per billion vehicle miles), you first conclude that the probability of getting killed in a cycle accident during your three year study is relatively low : 0.1% (≈ 3[years] × 365[days] × 25[miles] × (36 [Killed] ÷ 10⁹[vehicle miles]).

Subjective probability

After this factfinding you start to realize it's YOU getting on the bike and it's YOUR 0.1% risk of DYING in the next three years of your study....

Hmmmm...this comes closer; it makes things a little different, doesn't it?

Its looks like 'subjective probability' - on reflection - is perhaps somewhat different from 'objective probability'.

While your left and right brain are still in a dormant paradoxical state of confusion, your left (logical) brain already starts to cope with the needs of the right (emotional) half that wants you on that bike at all costs!

Russian Roulette

Now your left brain tells you not to get emotional, after all it is 'only' an additional 0.1% risk. Already your left brain starts searching for reference material to legitimate the decision you're about to take.

Aha!.... Let's compare it with 'Russian Roulette', your left brain suggests. Instead of 6 chambers we have thousand chambers with one bullet. Heeee, that makes sense, you talk to yourself.

With such a 1000 chambers Russian gun against my head I would pull the trigger without hesitating.... Or wouldn't I?..... No.., to be completely honest, 'I wouldn't risk it', my right brain tells me.

Hé... my left brain now tells me my right brain is inconsistent: It wants me on the bike but not to take part in a equal 'death probability game' of Russian roulette. Why not?

In Control
My left half concludes it must be the 'feeling' of my right side that makes me feel I'm 'in control' on my bike, but not in case of Russian Roulette. That makes sense, tells my left brain me. Of course! Problem solved! My right and left brain finally agree: It's only a small risk and it's I who can control the outcome of a healthy drive. Besides, this way the health benefits of cycling massively outweigh the risks as well, my right brain convinces me superfluous.

A final check by my right brain tells me: If I can't trust myself, who can I?
This rhetorical question is the smashing argument in stepping on the bike and to enjoy a wonderful ride through London City.
As ever...,

My left brain is always right!

Aftermathematics
After returning from my accidentless bike trip, I enjoy a drink with a colleague of mine, the famous actuary Will Strike [who doesn't know him? ;-)].

After telling him my 'bike decision story' he friendly criticizes me for my non-professional approach in this private decision problem. Will tells me that I should not only have analyzed the probability (P), but also the Impact (I) of my decision. Remember the equation: Risk=P×I?

Yes of course, Will is right. How could I forget? ..., the probability of getting a deathly accident was only 0.1%.

Yet, 'when' a car hits you full, the probability of meeting St. Petrus at heaven's gate is 100% and the Impact (I) is maximal (I=1; you're dead ...)

Summarized:

Risk[death on bike;25 miles/day; 3 years] =
Probability × Impact = 0.1% × 1=0.1%

From this outcome it's clear that, even though the Impact is maximal (1=100%) , on a '0% to 100% Risk scale' this 3 year 'London-Bike Risk Project' seems negligible and by no means a risk that would urge my full attention.

I'm finally relieved... it always makes a case stronger to have a taken decision verified by another method. In this case the Risk=P×I method confirmed my decision taken on basis of my left-right brain discussion. Pff....

Afteraftermath
The next morning, after my subconscious brain washed the 'bike dishes' of the day before, I wake up with new insights. Suddenly I realize I tried to take my biking decision on the wrong variable: Probability, instead of Impact.

Actually, in both cases and without realizing, I took my decision finally on basis of the Impact and the possible 'Preventional Control' (not damage control !!!) I could exert before and during my bike trip.

I had to conclude that in cases of high Impact (I>0.9), nor my left-right brain chat, nor the 'Risk=PxI' formula lead to a sound decision, because both are too much based on probability instead of Impact. In other words:

In case of high Impact, probability is irrelevant

In case of high Impact, only control counts

From now on this 'bike conclusion' will be engraved in my memory and I will apply it in my professional work as well.

P.S. for disbelievers, the tough ones!
If you're convinced you would take the risk of firing the 1000 chamber Russian gun against your head, you probably valuate the fun of the bicycle trip higher than probability of the loss of your life or good health.

In this case, suppose someone would offer you an amount of money if you would take part in a 1000 chamber Russian roulette instead of a bicycle tour. At which amount would you settle?

Let's assume you would settle at € 10.000.000 (I wouldn't settle for less). In this case you really value your bicycle trip!!!!

As we've seen in banking business as well : extreme low probabilities and high impact situations are tricky! That's why stress tests focus on impact and not on probability.

The different faces of Risk
Another issue when looking at risk is that risk is always conditional.
'The' probability of death or 'the' mortality rate doesn't exist. Mortality depends on a number of variables, such as age (the run down state of your DNA quality), the DNA-quality you where born with and lifestyle. Secondly mortality also depends on a number of uncertain events in your life.

To demonstrate this 'Chameleon property' of probability, lets take a look at the probability of a meteor hitting good old earth.

The initial probability of an asteroid devastating the earth within a 10 year time frame is around 0.1%. A typical case of low probability and high impact. Once we've become aware of a spotted meteor in our direction, the probability suddenly changes from a general probability in a time frame to a asteroid specific probability during his actual passage of the earth.
In case of the asteroid '2011 MD' that will pass the earth at a minimal distance of 11000 km on June 27, 2011, this specific probability turns out 0.11% (remember the Russian Gun...).

With a diameter of around 8 meter, this asteroid is no big threat to our civilization.

Here's a short impression what's coming flying in on us within the next decades (Source: Nasa; asteroid>50 meter or minimum distance< 100,000km):

Apart from some 'big asteroids' in the next decade, this picture puts our minds at rest. Yet we should keep in mind that most asteroids are discovered only a few weeks before a possibe collaps...

Risk Maps
A nice example of the limits of the Risk=P×I model in combination with a nice aleternative, is demonstrated by Fanton and Neil in in a document called: 'Measuring your Risks: Numbers that would make sense to Bruce Willis and his crew'.

In their document they analyze the case of the film Armageddon, where an asteroid of the size of Texas is on a direct collision course with the earth and Harry Stamper (alias Bruce Willis) saves the world by blowing it up.

Trying to fill in the Risk=P×I model in this Armageddon case is useless.

In this case, Risk is defined as:

Risk = [Probability of Impact] × [Impact of asteroid striking the earth]

Fanton and Neil conclude:

We cannot get the Probability number.
The probability number is a mix up. In general it makes no sense and it's too difficult for a risk manager to give the unconditional probability of every ‘risk’ irrespective of relevant controls, triggers and mitigants.
We cannot get the Impact number.
Impact (on what?) can't be unconditional defined without considering also the possible mitigating events.
Risk score is meaningless.
Even if we could get round the two problems above, what exactly does the resulting number mean?
It does not tell us what we really need to know.
What we really need to know is the probability, given our current state of knowledge, that there will be massive loss of life.

Instead of the Risk=P×I model, Fanton and Neil propose (Measuring risks) the use of causal models (risk maps) in which a risk is characterised by a set of uncertain events.

Each of these events has a set of outcomes and the ‘uncertainty’ associated with a risk is not a separate notion (as assumed in the classic approach).
Every event (and hence every object associated with risk) has uncertainty that is characterised by the event’s probability distribution.

Examples:

The Initial risk of meteor strike
The probability of loss of life (meaning at least 80% of the world population) is about 77%:

In terms of the difference that Bruce Willis and his crew could make there are two scenarios: (1) the meteor is blown up and (2) where it is not.

Reading off the values for the probability of “loss of life” being false we find that we jump from 8.5% (meteor not blown up) to 82% (meteor blown up). This near tenfold increase in the probability of saving the world clearly explains why it merited an attempt.

Lessons learned
Use (Bayesian) Risk Maps rather than the Probability Impact Model or Risk Heat Maps, if you want to take decisions on facts instead of your intuition.

P.S. Many thanks to Benedict Escoto, who attended me on a wrong interpretation of the bicycle risk on bases of the Biomed info.
See document: Deaths of Cyclists in London: trends from 1992 to 2006
I rewrote this blog on information of DFT.

Related Links:
- DFT's Reported Road Casualties 2009
- Pedal cyclist casualties in reported road accidents: 2008
- Is Cycling Dangerous?
- Cycling in London – How dangerous is it? (2011)
- Nasa: Small Asteroid to Whip Past Earth on June 27, 2011
- Nasa: Close (future) asteroid approaches...
- Nasa: Differences between Asteroid, Comet, Meteoroid, etc.
- Nasa: Search asteroid approaches in data base
- Nasa: Impact Probability of asteroids
- Fanton & Neil: Measuring risks
- Fanton & Neil: Bayesian networks explained (pdf)
- Neil: Using Risk Maps!

Adds:
Using Risk Maps

Deathly bike accedents in London

Actuary Garfield

2011-06-13T00:50:00.000+02:00

There's not a lot of 'Actuary Humor' on the Internet. Here's one...

Actuary Garfield explains how actuaries think...

Great and lots of humor, those Garfield cartoon strips, (especially those about actuaries....).

Original Sources:
- Garfield Snow
- Garfield Snowman

Short Term Longevity Risk

2011-06-05T23:02:00.001+02:00

As well-born actuaries we all know the long term risks of longevity:

Lots of actuaries keep expending their energy on calculations of 50 years ahead mortality probabilities.... And indeed..., this is challenging....

Some research reports predict a decline in life expectation, others and more serious recent reports show a steady increase of life expectation.

Mission Impossible

Fact of actuarial life is that - although long term research is useful and educational - we are no Actuarial Magicians.

We should never suggest that we're able to value a bunch of complex and systemic risks (liabilities, assets,mortality, costs, demographics, etc) into a reliable consistent model that predicts reality.

It's a farce!

What CAN we do?

Instead trying to compress a complex of long term risky cash flows into one representing unique value, we need to:

Analyze and model the short term risks
Develop a method (system) that enables boards of directors to manage and control their risky cash flows (profit share systems, experience rating, etc.).

Example: Short Term Longevity Risk

As a 2011 report of the National Research Council clearly shows: The previous 50 years we've seen a 3 months yearly increase of lifespan every calendar year.

Instead of recalculating, checking and pondering this trend, let's take a look at the short term effects of this longevity increase trend.

Effect of 'one year life expectancy' increase
First we take a look at the cost effect of the increase of 'one year of life expectancy' on a single-premium of a (deferred) life annuity (paid-up pensions)...
( Life table total population: United States, 2003 )

Depending on the discounting interest rate, a one year improvement of longevity for a 65 old person demands a 2,3% to 4,0% increase of the liabilities.

Of course the increase of the liabilities of a portfolio (of a pension fund) depends on the (liability weighted) age distrubution of the corresponding portfolio.

Here's a simple example:

This comes close to the rule of thumb as mentioned by AEGON:

10% mortality improvement adds one year to life expectancy, and one year of life expectancy adds 4% to the required value of a pension fund’s reserves

Conclusion

From the above presented visual sensitivity analysis we may conclude that for general (distributed) portfolio's a 'one year lifetime increase' will demand approximately 4-5% of the actual liabilities.

A three to four months yearly longevity-increase - as is still the actual trend - will therefore demand roughly a substantial 1,5% (yearly) of the liabilities.
This implies that in case your contribution is calculated at 4% and your average portfolio return is 7%, there's 3% left for financing longevity and indexation (=method). As 'longevity growth' in the near future will probably cost about 1,5%, there's only 1,5% left for indexation on the long run.

Case closed

Related links:
- Spreadsheet (xls) with data used in this blog
- Forecasting longevity of Dutch pension scheme members using postcodes
- Increasing life expectancy at pension funds (uvt;2011)
- Life Tables for the United States Social Security Area 1900-2100
- Valuing Pension Fund Liabilities on the Balance Sheet
- No limits to life expectancy?
- Broken Limits to Life Expectancy
- NRC: Explaining divergent levels of longevity (pdf;2011)
- Wolfram Alpha: Longevity U.S.
- AEGON: Longevity Rule of thumb

Google Hits on Actuary

2011-05-25T23:12:00.000+02:00

Google can be a great help for actuaries. Especially 'Google Insights' and 'Google Trends' are two useful applications for retrieving relative Google Search Hits data from the Internet.

Google Insights Example
Let's dive a little deeper into Google Insights and start with researching the relative development of the number of hits on the word 'Actuary'.
Here is the result (period 2004-2011-May, extracted csv-file, Excel-Graph):

Explanation
The numbers on the graph reflect how many searches have been done for a particular term (e.g. 'Actuary'), relative to the total number of searches done on Google over time. They don't represent absolute search volume numbers, because the data is normalized and presented on a scale from 0-100. Each point on the graph is divided by the highest point, or 100.

Conclusion

Clear is that the search for (the word) actuary is relatively declining from 2004 to May 2011.

To keep the actuarial profession virtually alive we'll need to make more noise as actuaries on the Internet.

Step outside, spread the (acturial) word, make yourself visible in the outer world and let people wonder: 'who's that?', 'what a professional', 'what's his job?', 'Actuary?', 'I will google it!'.

So let's Twitter and Blog to get more actuarial exposure...

Actual Data

Apart from generating these kind of relative time-data, Google Insights can generate actual data anywhere on any web-application or presentation.

This way your data will always be up to date!
Moreover Google Insights is easy to handle without any code knowledge.....

Some examples....

(1) Actual relative development of the number of hits on the word 'Actuary'

(2) Top searches and rising searches on Google for the word 'Actuary'

More applications

The next example shows how you may use Google Highlights as a market crash predictor.

It turns out that in advance of the 2008 market crash, Google searches on "Stock market crash" increased...

Make you own discoveries, highlights or trends (e.g 'Solvency II') and enjoy!

Related Links:
- Actuaries on Twitter
- Google Insights
- S&P 500 Data
- How Google Trends and Internet Searches Correlate with Asset Prices
- Google trends: 21 May 2011: End of the world, predicted by Harold Camping

Actuarial Proverbs: Will Europe Survive?

2011-05-15T00:18:00.006+02:00

According to Eurostat, Europe - especially the Euro (€) 'Coin' Countries that put all their Euro eggs in one basket - face a difficult time. In a world where money seems to grow on trees, it's hard to take the right measures to prevent Greece from a financial meltdown with unknown consequences.

Questions
Even for actuaries it's hard to understand what's happening and what makes sense or not, It's over our 'actuarial' head....

Should 'Europe donor countries' support Greece fore more than the '110 billion Euro rescue' in 2010?
Is Greece’s 10-year bond rate of 15% an adequate risk premium?
Will restructuring Greece's debt solve anything, devaluate the Euro, or pose other incalculable risks to the overall Euro zone?

Difficult questions that are hard too answer....

Debt-Deficit Comparison
Let's take an actuarial look at the facts by comparing 2010 Government Debt with Deficit (all in % GDP):

From this chart it's clear that not only Greece is in the danger zone, but also Ireland and the US as well... Moreover, the UK is not free from worries, to put it mildly...

The blind are leading...
Another chart-conclusion might be that the blind are leading the blind'. Relative strong less-weaker countries like Germany and France, have to carry the financial consequences of cheating and not-performing countries. Above all, we all know: one rotten apple spoils the barrel!!

In fact to save or revive 'Financial Europe' it would take some countries with no debt and a strong positive surplus (= negative deficit) instead of a deficit.

It seems neither sensible nor logical to restructure another country's debt if the outlook of the governments debt and deficit of the' helping country' is (slightly less) negative as well. But as we know: only fools rush in where angels fear to tread.

Trying to help other countries that fail to restructure themselves is like banging your head against a brick wall... No risk premium on government bonds can compensate that...

Countries with a strong relative debt and a deficit should restructure their own country and financial situation at once, before asking ore receiving any outside help.

Growth: The Solution?
Some argue that debt and deficits are not so bad as long as countries are growing. Let's dive into this argument with the next chart (data source: Eurostat):

Indeed, from this 'Growth-Believe' we can now understand why (only) Greece is seen as such a major problem.

From this chart it's also clear that if Ireland and Spain are not going to grow one way or the other, they will become the next big problem. These countries have to take the bull by its horns, before it's too late.

It's throwing caution to the wind when 'debt and deficit countries' with a positive 'Real GDP Growth Rate' try to save sicker country-brothers by lending them money.

Moreover, it's lending money you don't really possess or own, it's like robbing Peter (yourself) to pay Paul....

Combining the two Eurostat charts it becomes clear that that not all 'Garlic Countries' (Mediterranean countries:Greece, Spain, Portugal, Italy) can be lumped together.

Greece is indeed the greatest risk , secondly a non-garlic country: Ireland...
Spain, Portugal and Italy are relatively at arm’s length and could perhaps keep their head above water if they take the right measures in time.

U.S.' Fiscal Gap

Finally, don't forget about the U.S., as the U.S. Real GDP Growth Rate is already declining to 2.3% in Q1 2011.

According to Boston University economist Kotlikoff, the U.S. is broke. Kotlikoff doesn’t trust government accounting. He uses “Fiscal Gap,” not the accumulation of deficits, to define public debt. This "Fiscal Gap" is the difference between a government’s projected revenue and its projected spending .

By this measure, the U.S. government debt is $200-trillion – 840 percent of current GDP.

Conclusions

From all this it's clear Europe is stuck between a rock and a hard place...
Although ECB President Mr. Trichet thinks different, it looks like €-Europe has to choose between two blind goats (Irish saying):

(1) A complete Financial Europe Meltdown in case of endless financing default countries like Greece or

(2) Letting individual default countries go bankrupt, with unsure (systemic) consequences for local banks and other financial institutions that financed or invested in default countries.

How to decide? Guideline: Of two evils, always choose the less....
As option (1) is clearly putting the cart before the horse, and surely leads to a meltdown, only option 2 is left: QUIT!

Sources and related links:
- Spreadsheet: Used Data, Tables for this blog (xls)
- US Real GDP Growth Rate
- Government Debt and Optimal Monetary and Fiscal Policy (2010)
- English proverbs and sayings (!)
- English deficit (including time table)
- Shadowstats (for the real stats!)
- The U.S. is broke?
- Eurostat: Euro area government deficit at 6.0% GDP (2011)
- BILD: Interview with Jean-Claude Trichet, President ECB, 15 January 2011

Oversized Supervision?

2011-05-14T15:20:00.001+02:00

In April 2011 EIOPA published the findings of its 2010 survey:

REPORT ON REPORTING REQUIREMENTS TO SUPERVISORY AUTHORITIES

applicable to the Institutions for Occupational Retirement Provision (IORPs) in the context of the IORP Directive.

The report analyses several interesting differences in reporting among member states.

I'll will confine myself in this blog to two remarkable results....

1. Difference in number of Supervision employees per country
It's remarkable (and not directly explainable) to see that the UK and The Netherlands outnumber the other European countries on number of supervision employees....

2. Influence Actuarial Reporting
The survey provides a large number of reporting and monitoring issues that aim to monitor or mitigate several types of risk.
I'll provide a short report that shows the connection between some actuarial reports and types of risk.

Clearly the risk of funding is one of the most important issues with regard to actuarial reporting. Perhaps it's even a little bit overweighted......

Anyhow, check your reports with regard to the above risks, especially if your living in an oversized supervision country like the UK or The Netherlands....

Homo Actuarius Bayesianis

2011-05-10T20:40:00.006+02:00

Bayesian fallacies are often the most trickiest.....

A classical example of a Bayesian fallacy is the so called "Prosecutor's fallacy" in case of DNA testing...

Multiple DNA testing (Source: Wikipedia)

A crime-scene DNA sample is compared against a database of 20,000 men.

A match is found, the corresponding man is accused and at his trial, it is testified that the probability that two DNA profiles match by chance is only 1 in 10,000.

Sounds logical, doesn't it?
Yes... 'Sounds'... As this does not mean the probability that the suspect is innocent is also 1 in 10,000. Since 20,000 men were tested, there were 20,000 opportunities to find a match by chance.

Even if none of the men in the database left the crime-scene DNA, a match by chance to an innocent is more likely than not. The chance of getting at least one match among the records is in this case:

So, this evidence alone is an uncompelling data dredging result. If the culprit was in the database then he and one or more other men would probably be matched; in either case, it would be a fallacy to ignore the number of records searched when weighing the evidence. "Cold hits" like this on DNA data-banks are now understood to require careful presentation as trial evidence.

In a similar (Dutch) case, an innocent nurse (Lucia de Berk) was at first wrongly accused (and convicted!) of murdering several of her patients.

Other Bayesian fallacies
Bayesian fallacies can come close to the actuarial profession and even be humorous, as the next two examples show:

Pension Fund Management
It turns out that from all pension board members that were involved in a pension fund deficit, only 25% invested more than half in stocks.

Therefore 75% of the pension fund board members with a pension fund deficit invested 50% or less in stocks.

From this we may conclude that pension fund board members should have done en do better by investing more in stocks....
The Drunken Driver
It turns out that of from all drivers involved in car crashes 41% were drunk and 59% sober.

Therefore to limit the probability of a car crash it's better to drink...

It's often not easy to recognize the 'Bayesian Monster' in your models. If you doubt, always set up a 2 by 2 contingency table to check the conclusions....

Homo Actuarius
Let's dive into the historical development of Asset Liability Management (ALM) to illustrate the different stages we as actuaries went through to finally cope with Bayesian stats. We do this by going (far) back to prehistoric actuarial times.

As we all know, the word actuary originated from the Latin word actuarius (the person who occupied this position kept the minutes at the sessions of the Senate in the Ancient Rome). This explains part of the name-giving of our species.

Going back further in time we recognize the following species of actuaries..

Homo Actuarius Apriorius
This actuarial creature (we could hardly call him an actuary) establishes the probability of an hypothesis, no matter what data tell.

ALM example: H₀: E(return)=4.0%. Contributions, liabilities and investments are all calculated at 4%. What the data tell is uninteresting.
Homo Actuarius Pragmaticus
The more developed 'Homo Actuarius Pragamiticus' demonstrates he's only interested in the (results of the) data.
ALM example: In my experiments I found x=4.0%, full stop.
Therefore, let's calculate with this 4.0%.
Homo Actuarius Frequentistus
In this stage, the 'Homo Actuarius Frequentistus' measures the probability of the data given a certain hypothesis.

ALM example: If H₀: E(return)=4.0%, then the probability to get an observed value more different from the one I observed is given by an opportune expression. Don't ask myself if my observed value is near the true one, I can only tell you that if my observed value(s) is the true one, then the probability of observing data more extreme than mine is given by an opportune expression.
In this stage the so called Monte Carlo Methods was developed...
Homo Actuarius Contemplatus
The Homo Actuarius Contemplatus measures the probability of the data and of the hypothesis.

ALM example:You decide to take over the (divided!) yearly advice of the 'Parameters Committee' to base your ALM on the maximum expected value for the return on fixed-income securities, which is at that moment 4.0%. Every year you measure the (deviation) of the real data as well and start contemplating on how the two might match...... (btw: they don't!)
Homo Actuarius Bayesianis
The Homo Actuarius Bayesianis measures the probability of the hypothesis, given the data. Was the Frequentistus' approach about 'modeling mechanisms' in the world, the Bayesian interpretations are more about 'modeling rational reasoning'.

ALM example: Given the data of a certain period we test wetter the value of H₀: E(return)=4.0% is true : near 4.0% with a P% (P=99?) confidence level.

Knowledge: All probabilities are conditional
Knowledge is a strange phenomenon...

When I was born I knew nothing about everything.
When I grew up learned something about some thing.
Now I've grown old I know everything about nothing.

Joshua Maggid

The moment we become aware that ALL probabilities - even quantum probabilities - are in fact hidden conditional Bayesian probabilities, we (as actuaries) get enlightened (if you don't : don't worry, just fake it and read on)!

Simple Proof: P(A)=P(A|S), where S is the set of all possible outcomes.

From this moment on your probabilistic life will change.

To demonstrate this, examine the next simple example.

Tossing a coin

When tossing a coin, we all know: P (heads)=0.5
However, we implicitly assumed a 'fair coin', didn't we?
So what we in fact stated was: P (heads|fair)=0.5
Now a small problem appears on the horizon: We all know a fair coin is hypothetical, it doesn't really exist in a real world as every 'real coin' has some physical properties and/or environmental circumstances that makes it more or less biased.
We can not but conclude that the expression
'P (heads|fair)=0.5' is theoretical true, but has unfortunately no practical value.
The only way out is to define fairness in a practical way is by stating something like: 0.4999≥P(heads|fair)≤0.5001
Conclusion: Defining one point estimates in practice is practically useless, always define estimate intervals (based on confidence levels).

From this beginners example, let's move on to something more actuarial:

Estimating Interest Rates: A Multi Economic Approach

Suppose you base your (ALM) Bond Returns (R) upon:
μ= E(R)=4% and σ=2%
Regardless what kind of brilliant interest- generating model (Monte Carlo or whatever) you developed, chances are your model is based upon several implicit assumptions like inflation or unemployment.

The actual Return (R_t) on time (t) depends on many (correlated, mostly exogenous) variables like Inflation (I), Unemployment (U), GDP growth(G), Country (C) and last but not least (R_[t-x]).

A well defined Asset Liability Model should therefore define (R_t) more on basis of a 'Multi Economic Approach' (MEA) in a form that looks more or less something like: R_t= F(I,U,G,σ,R_[t-1],R_[t-2],etc.)
In discussing with the board which economic future scenarios will be most likely and can be used as strategic scenarios, we (actuaries) will be better able to advice with the help of MEA. This approach, based on new technical economic models and intensive discussions with the board, will guarantee more realistic output and better underpinned decision taking.

Humor: Scrambled Actuarial Reporting

2011-05-01T20:49:00.000+02:00

Some actuaries are convinced that adding more important details really helps. With more details and more information you are able to explain you models better and as we all know: better communication is key in actuarial science.

Here is an example of detailed information (click on the image!)

Some(times) details don't matter
Unfortunately more information and more details generally disturb efficient decision making. The next text shows that some details don't really matter.

Smoe acaruites are covcnined taht adding mroe imnrpotat deaitls rlaely hleps. Wtih more dleitas you are albe to eplaxin you mlodes bteter and as we all konw: btteer cmniutcoiaomn is key in aratiuacl sieccne.

Sirnpigrulsy tihs is not ture. Tihs txet sowhs taht smoe daeilts dno't rlaley mttear.

The arutacial aidnceue isn't rlaley istretneed in the daeilts, but in caelr ipunt (fsrit ltteer of a wrod) and oumotces (last letetr of a word). The dtilaes (letetrs) in bweteen can be mexid up in evrey rodnam oerdr you lkie. Keep in mnid tihs iponmatrt lsosen in your nxet peeiatntsorn.

Explanation
According to a study at Cambridge University, to read and understand a text well, it doesn't matter in what order the letters in a word are placed. The only condition is that the first and last letter of each word remain the same. The rest can be a total mess up. This is because the human mind does not read every letter by itself but the word as a whole.

DIY
Let's conclude with an 'example text' for the opening-slide of you next board presentation:

Daer Board mrebmes,

Agtlhouh we hvae to tkae fetdanmaunl dniecioss tdoay, it wlil not be ncseresay to udasnertnd or dcssius all knid of tcihcenal dtileas.

The relust of my avicde is pertseend in scuh a way as to esurne taht we can stcik to the mian ptinos and hneieadls.

The vrey fcat that you wree albe
to raed and udnreastnd tihs txet,
greauetans taht we wlil hvae a
sefscuucsl mtineeg.

Yuor aivdosr

Scramble your own opening-slide text for your next presentation at:

Words Scrambler

No doubt, your next report will be actuarial scrambled.... ;-)

Related sources and links
- Words Scrambler
- MRC Cognition and Brain Sciences Unit
- All My Faves

The Ten Actuarial Commandments

2011-05-01T00:17:00.002+02:00

We all (think to) know The Ten Commandments from the holy scripts by heart, do we?

Now close your eyes to see how far you can get in quoting those simple ten guidelines in life.............

The Ten Commandments for Investors
Just like the Ten Commandments for Man, God - more specific - created The Ten Commandments for Investors. Let's compare the two, while - at the same time - you can check out your Commandment-Memory on Man as well:

Risk-Return-Supervision Development
As you may have noticed, The Ten Commandments are a mix of rules-based and principles-based principles.

Just as in our own life, it's interesting to see how we apply and implement these two different kind of rules during the evolution of a financial institution (insurance company, pension fund, bank, etc.):

In time, the ideal supervision model consists of three phases:

Phase I: No rules
In this phase we cannot value or the company. Chances are substantial the company is 'at risk'.
Phase II: Rules-Based Supervision
In phase Ia 'Rules' are mostly perceived as 'Have to's" . As a result Risk will be reduced, but Return as well. Once the board, actuaries and financial specialists are becoming aware and will see the advantages and new possibilities of managing risk. 'Have to's" will develop into 'Want to's" . The Risk-Return Ratio will increase and even a better Return will result.
Phase III: Principles-Based Supervision
Just like with the implementation of Rules-based Supervision, in case of Principles-Based Supervision, the Financial Institution needs time to adept to the new situation. At first there might be a unbalance between Risk and Return. It takes time to calibrate Risk and Return again.

After a while actuaries, investors and management will translate Rules-Based principles into own rules that fits the company's specific risk in an optimal way. The company will be able to take more risk and to optimize its own Risk-Return Ratio.

Take a look at your own company's development and see for yourself where you fit in on the Risk-Return-Supervision lines....

It might be possible that you have to conclude that you aren't able to increase your Risk-Return ratio in the end. In this case it's likely you've become (so called) 'Supervisory Compliant': Your risk appetite probably corresponds more or less with the supervisor's minimal risk view. Instead of redefining your own risk appetite and restructuring your products from a risk-management perspective you merely implied new regulations and supervisor guidelines. As a result your Return and Risk-Return Ratio implode....

Ten Actuarial Commandments
Having learned the possible effects of supervisory rules in practice, we may now conclude with The Ten Commandments for Actuaries.

The Ten Commandments for Actuaries

There's only one God, as he's omnipotent he's also an actuary.
As you're only an actuary: be humble..... Remember: As God wants something in Return, you'll have to take Risk!!
Reality can't be comprised in a model.
Use your brains. A model is a help, not a decision machine. Don't mix up God with Risk or Chaos. Chaos for us humans (actuaries) can be defined as "Unrecognized Order" (quote).
Never blame anything or anyone than yourself for an unexpected or negative outcome.
Be consistent, act sustainable. But change your opinion just in time, if circumstances or facts urge you to do so.
Alway show respect to others, even if you think different. Appreciate where you come from. Nobody is perfect, not even you.
As there is no 'right' model, never criticize other models, actuaries or other people. Try to give your opinion without slaughtering the other.
Never advice or state anything you do not really mean or cannot defend.If you're not sure or don't know, tell it or get help.
Always cite your sources or give credits to others that helped you.
Don't 'steal' the advice.
Never include the final decision to be taken in your advice. Wrap up arguments, consequences and present scenario's so the board has to make a choice and not you.
Don't get carried away by results, reports or performances of others.
Stick to your own consistent approach.

Apply supervisory rules and actuarial commandments in a conscious way...

Risk Quotes

2011-04-25T00:29:00.006+02:00

I'll not even try to give a definition of 'Risk Management'.
More than the word Risk, Risk Management is full of traps and paradoxes.

Just to mention some.....

Risk Management is...

not primarily about risk that can be calculated with a 99,x% confidence level
dealing with Risks you know will come, but can't be calculated
more about correlation in time than mean estimates and standard deviation
more about prevention, foreseeing and managing risk than capitalisation of risk
more about taking risks to benefit, than trying to exclude risks
fighting risk instead of excluding risk
making Plans B and C, in case your confidence level fails

Avoiding Risk

One of the trickiest parts of Risk Management is that we often are trying to avoid Risk at any price.

By doing so, we introduce a new risk: It gets harder to achieve shareholder and client value.

Often returns will decline because of over-capitalisation and a risk-return unbalance.

Finally we have to compete in new risk areas we're not experienced in.

It's all well expressed in a cartoon on cartoonstock:

'We've considered every potential risk, except the risks of avoiding all risks.'

Personally I prefer the challenging Risk Management quote of Jos Berkemeijer, that states:

"Risk Management: the art of foreseeing hindsight."

Better than trying to define Risk or Risk Management, it is to study and get inspired by Risk Quotes.

Therefore I conclude this Blog with a link to the Blog 'Risk Quotes'

You can place a random quote like this one:

Random Risk Quote

on your website or Blog by copying the next javascript code.

Install Instructions

Copy above JavaScript code (select;CTRL-C).
Paste (CTRL-V) the code on your webpage or Blog
Blogger: Go to Design Tab, Click on Add a gadget;
Click on 'HTML/Javascript' Gadget
Paste the above code in the gadget and Save.

Actuary beats Chimp (or not?)

2011-04-18T16:22:00.000+02:00

Is your joy for stats just as big as Hans Rosling's enthusiasm shows?

Just watch how Hans tells the developing story of Lifespan against Income in more than 200 years, showing around 200 countries in a 120.000 numbers flowing chart!

It's clear, we actuaries can learn from Hans with his (1) 'sticky enthusiasm' and (2) 'keeping the issue on headlines'.....

You can play for your own with the data Hans uses on Gapminder World

No doubt..., your next board presentation will be dynamic and flowing.

To conclude... If you as an actuary think you know more about the actuarial world than a chimp, please take Hans Rosling's

Beat the Chimp test

on facebook.

Let's hope for the 'best'.....

Related links:
- Gapminder World

Fun: Actuarial Dasboard Crash

2011-04-11T00:31:00.000+02:00

Last week I gave a Risk Management training about pension funds. After illustrating several times the importance of adequate risk management dashboards, one of the attendees suddenly stated:

'No matter how impressive your dashboard, you should keep your eyes on the road!'........

Right he was! A driver who's constantly focused on his dashboard will sooner or later end up in the bush and finally crash.

We, actuaries and risk managers all trust on our dashboards, but at the same time we should keep our eyes open to anticipate on coming events in a changing marketplace.

Sometimes it's even better to just leave the road, as the next video shows...

Police Risk management

David | Myspace Video

Anyhow, keep your eyes open, to prevent an Actuarial Dashboard Crash.....

Related Links:
- Alfa Romeo Spider Veloce: Don’t Let Dashboards Drive You Crazy

Stress test stress test

2011-04-03T16:57:00.001+02:00

How did you interpret the title of this Blog......?

Can you read it in more than one way? In how many ways can you read it?

Still confused?

Enough questions to start this blog.

In short: the more ways you are able to read this title, the more successful you'll probably be in defining and executing 'Stress Tests" in practice.

Let's dive a little deeper to illustrate this important 'multi interpretation talent' you need, to make stress testing a success.

Although there are far more ways (please add some interesting suggestions as comments to this blog) to interpret the title 'stress test stress test', we'll analyze in this blog two interesting interpretations that follow from the fact that 'stress test' can be interpreted as a noun or as a verb.

1. stress test [noun] stress test [noun]

Interpreting the title as two nouns could:

make you aware of the importance of stress tests
emphasize the importance of repetitive execution of stress tests
illustrate the feeling of disinterest and apathy that occur when important words are repeated to often without enough plowing depth..

2. stress test [verb] stress test [noun]

This perhaps the most interesting interpretation.
How can you really stress test your stress test?

The way we stress test at financial institutions like banks, insurance companies and pension funds, is basically more or less as follows:

Project historical crisis crash-data into the future. Simulate what would happen and take a look at the consequences
Test crash scenarios on basis of the question: What would happen if.... (prices go down, S&P 500 collapses, etc., etc.)
Take several economic scenarios. Project them on your balance sheet and see what happens.

To stress-test a stress test we have to develop a different view on stress tests.

A view based on the answer of the next leading question:

How many sides has a coin?

Let's demonstrate this new crucial view on a stress test.

A Different View on Stress Tests
Some examples:

Inverted Stress Test
An interesting way of stress testing is 'working the other way around': Try to define financial situations where you never want to end up in (e.g. equity< -5%, etc.) and try to imagine scenarios that could lead to this unwanted financial situation Paul Duijsens, ALM Principal Mercer Investment Consulting, mentions this approach).
Idiot Proof Stress Test
Andrea Enria, chairman of Europe’s new banking regulator stated recently:

A stress test is only as good as the scenarios you plug into it

Therefore, make stress tests 'idiot proof' as much as possible.
Once a stress test is developed, don't present it to the board directly. Organize a 'second opinion' from a professional company that's undependable and critical enough to seriously test and analyze your stress test and its assumptions.

Presenting a stress test without clear statements about the limits, vulnerabilities, constraints and shortcomings (every test has shortcomings) is like playing with fire and offering your board 'the wrong end of the stick'.

So we can add another conclusion quote:

A good stress test transparently presents its weaknesses

If nobody can find a weak spot spot in your stress test: ask a 5 year old child to ask some simple questions.....
Compare Stress Tests
Please think about :

'One stress test' = 'No stress test'

Comparing successively executed stress tests on assumptions, methods and outcomes is essential for a correct understanding of the impact and consequences.

Not only compare tests of your own company, compare also with tests of other financial institutions. Questions like: why do we as a [pension fund] have different assumptions and methods than an international [bank], are key to a correct understanding of your own risks.
Surpass Regulator Constructed Stress Tests
Regulator Constructed Stress Tests(RCS-tests) seem relatively easy to implement.
As a risk manager or board member you don't have to think about scenarios or methods. That's all been taken care of by the Regulator. Easy, isn't it?......... Wrong!

Heedlessly implementing RCS-tests is risky. First of all, the regulator's principles are partly biased. As an example, take the risk of treasury bonds on your balance sheet. Treasury bonds are commonly seen (and valued) as save (AAA-rating). However, some countries (Greece, Spain,Ireland etc.) have already been downgraded. Which countries will follow? Does the RCS-test includes this non-hypothetical risk? No? Does your own test includes this risk?

By definition regulators have to act and communicate in a responsible and 'prudent' way about government financial issues. If they wouldn't, world wide financial chaos would be the inevitable result.

The other side of this 'prudent coin' is that the actual risks are probably larger than can be concluded from the government (treasury) interest rates and interest spreads in a particular country. Here you'll have to develop your own risk model or - if data fail - formulate your own risk approach (get out!).

Key is that, given the general level of systemic risk, all financial institutions must be able to withstand haircuts on all their own sovereign debt holdings.

A 'third side' of this coin is the fact that regulators (in time) might decrease risks on certain asset categories that are not in line with your own risk view. Stay awake to prevent from becoming 'Supervisory Stress Compliant'.........

Unmask Derivatives
Market valuation with respect to derivatives is tricky business and probably only valid as long as there's a 'normal' market activity. Nobody is able to value derivatives under severe market conditions as is the case in stress tests. So, depending on the size and characteristics of a stress test, don't hesitate to to unmask your derivatives by applying a large discount on the value of your derivatives.

Conclusion
Stress testing is not for dummies, but for professionals.
It turns out that the more you're able to look different, critical and 'out of the box', the more stress testing will be successful.

Making your audience aware that a coin has three sides instead of two, is probably the essence of an actuary's or risk manager's profession.

It has become clear that analyzing assumptions, models, outcomes,constraints and shortcomings of a stress test is no superfluous luxury. So stress test your stress test!

Related links:
- KAS BANK develops stress test for UK pension funds
- Concerns over latest EU bank stress tests
- EU bank stress tests, a joke (2011)
- Lateral Thinking: US Economy Stress test (2011)
- World Wide Interest Spread by Country (2011)
- Government Bonds yields 10 Year Notes
- How many sides has a coin?
- Worst-Case Scenario Survival Card Game

Zero Problems Risk Management

2011-03-27T00:40:00.003+01:00

More and more we actuaries and risk managers become aware that our risk models can't just be based on numbers and statistics exclusively.

Some examples:

Systemic risk

The recent financial crisis made it clear that a 'mono risk approach' on a sole risk-object (mortgage, fund-investment) is insufficient.

Investments and loans are embedded in a worldwide sea of connected financial instruments and reinvestments. Systemic risk has to be included in our models.

Main challenge here is that systematic risk essentially depends on macroeconomic and (mostly) irrational factors. Further, systemic risk is related to the structure and dynamics of the market. More than numbers.....

Supervisory Herding Risk

In their effort to control and support financial institutions like banks, pension funds and insurance companies, country supervisors, regulators and 'accounting standards boards', defined a meticulously set of guidance rules (Basel I/II/II, Solvency I/II, Qis-I-V, IFRS, FAS, AIFMD, FTK, FIRM, etc.,etc.)

Financial institutions not only confirmed and adopted to those new rules, but - in their rush and driven by cost and time pressure - also implicitly (and often unintentionally) declared those same imposed rules and rationales as their own business 'Risk Appetite'. This way, most financial Institutions became so called: 'Supervisory Compliant'.

Instead of expliciting their specific company-targets and successively developing their own correspondent risk appetite and risk framework, they incorporated the supervisor's risk philosophy.

Without a sound own (board) risk vision that would undoubtedly have included some extra safety on 'company specific risk issues', financial institutions became - like a herd - all in the same way extremely vulnerable to (less defined) external risks.

Summarized:

Overregulation increases Herding Risk

Financial institutions all measure and respond to regulated risks in the same way. Supervisory Herding Risk is born.....

Too Much Focus Risk

As a consequence of pre-subscribed risk categories and ruling by law or (accounting) standards, there's the risk of 'too much focus' on specific risks while forgetting, denying or neglecting other important risks. Remember, the devil is in the (correlating) details....

Here's a useful, but not exhaustive, checklist to keep track on your risk models...

Average Premium Risk	Diversification Risk	Matching Risk
Commodity risk	Employer Continuity Risk	Operational risk
Compliance Risk	Environmental Risk	Outsourcing Risk
Compliance Risk	Equity Risk	Oversight Risk
Concentration Risk	Herding Risk	Price Inflation Risk
Counterparty Risk	Interest rate risk	Property Derivatives Risk
Coverage Ratio Risk	IT Risk	Reinsurance Risk
Credit Risk	Legal risk	Reinvestment risk
Culture Risk	Legislative Risk	Reputation risk
Currency Risk	Liability Risk	Sex Calculation risk
Default Risk	Liquidity risk	Strategic risk
Deflation risk	Longevity Risk	System Risk
Disaster Risk	Market Risk	Systemic Risk
Discount Risk	Matching Risk	Wage Cost Inflation Risk

ALM Simplifying Risk

Univariate models are killing and even multivariate models have proven to be too vulnerable and too limited in the recent crisis. It's not just about correlation and covariance matrices. What we need is an self-explaining model. A model that predicts or generates expected values in an economic context, depending on exogenous economic variables like inflation rate, GDP-Level, etc. and that is based on the same structured historical economic data-set.

We need 'Asset Liability Modeling New Style' and not only Stress Testing or
advanced and excellent Crash Modelling as well explained by EMB.

Geopolitical Risk

With Europe and Japan as recent examples, it's clear that risks come from everywhere around the world.

The consequence of earthquakes (Japan, Australia), a possible country default (Ireland, Greece, Portugal, ..), political instability (Libya, Ivory Coast, ..), war threat (Vietnam,Iraq, ..), financial easing (US, Europe,...), on our economic system, prices and financial institutions seems substantial and - moreover- predictable.

More than just trying to catch and capitalize these kind of risks in our risk models, we need to develop (financial) mechanisms and products that can cope as best as possible with these kind of risks.

The Riskmap 2011, Managing Risk | Maximising Opportunity, offers a good description of the actual risks that influence our lives and risk models.

A nice example is the recent (unexpected) leading role that France took in action against Libya. 'Riskmap 2011' mentions the 'Arabic Poll 2010' that clearly shows (despite the lack of sympathy for president Sarkozy) the trust and sympathy for France. France clearly outperforms the US and president Obama unfortunately has lost the trust of the Arabic world... Take a look at the next slide summary (or the original complete pdf):

Arab Public Opinion Poll 2010 Summary

The Arabic poll shows that the prime minister of Turkey, Erdogan, has clearly gained the confidence and trust of the Arabic countries. With Ergodan, Turkey - at the cross road between East and West - takes a leading role in the 'World Risk Management Process'. Ergodan's Risk Philosophy, invented by the Turkish Foreign Minister Ahmet Davutoglu, is 'Zero Problems'.....

Perhaps that should be the philosophy of actuaries too...

Zero Problems

Conclusion

From now on 'Modeling Risk' is more than just a financial exercise.
It's building scenario's, mechanisms and products that can cope with this risky world. Success as actuary or risk manager!

Related Links:

- Committee (behaviour) assessment tool
- Control Risks:Riskmap 2011
- Arabic Poll 2010
- Supervisory Compliant
- Maplecroft Risk Maps
- EMB: How to Model a Crash (REVO)

Fukushima Risk Management

2011-03-16T23:14:00.004+01:00

With all due respect for the Japanese risk managers, engineers and the Japanese people in general: The latest 2011 M=8.9 Earthquake in Japan made clear that the current Risk Models, as well as Risk Management itself, have tragically failed.

Shortcomings
Shortcomings in headlines:

Underestimation of the probability of a M=8.9 (M>8) event
Risk Modeling mainly focused on 'direct' earthquake effects
Underestimation of cumulative correlated devastating effects that occurred as a consequence of a combination of Earthquakes, Tsunamis, Nuclear Disasters and Physical Concentration (4 reactors in a row!).

Frequency?
It's true, the worldwide annual frequency of a serious earthquake with a magnitude of 8 or more (M>8) seems small....

Yet - no matter how low the probability- the consequences (loss) is unacceptable if the damage in case of an event (like an earthquake M>8) is not manageable, exceeds a country's financial recuperation power, or devastates thousands of lives...

End of Time?

Lots of worrywarts think the end of time has come, as severe earthquakes are increasing.

Simple statistics show that this is not (yet ?) the case:

The expected average Magnitude value of all earthquakes with M>=7 over the period 1950-2011 (March) is M_a=7.6 with a standard deviation of SD= 0.4. The average value of the last 10 years turns out M_a=7.4 with the same SD (0.4).

Nevertheless, when we examine the graphic more closely, there seems a light (significant?) increase in large magnitude earthquakes in recent decades.....

Back to the year 0
For what it's worth, the average magnitude for M>=7 earthquakes over a longer period from 0 to 2011 (March) , turns out in line with M_a=7.6 and a SD=0.44. Or in graphics:

History Earthquakes in GoogeMaps
Finally, take a look at the history of all earthquakes with a magnitude of 7 or higher on GoogleMaps... (take look at your country!)

Earthquakes, Magnitude> 7, years 0-2011 weergeven op een grotere kaart

Let's hope and pray for the Japanese people that that the brave engineers who are fighting the current meltdown at Fukushima will succeed and survive.....

Related links
- Spreadsheet (Excel) Earthquakes 0-2011 (March), M>=7
- Crash Course Earthquake calculation by Professor Nicholas Pinter
- Effect of Seismic Risk Measures on Japanese Housing Prices
- Earthquake Software
- Download Earthquake data from USGS
- Earthquake Safety of Nuclear Power Plants
- PPT:Japan’s Nuclear Energy Program(2003-2004)
- Design criteria Japanes Nuclear Plants
- Prediction of ground motion
- Seismic Risk Evaluation (2004)
- Earthquake Facts
- Earthquake FAQS
- GeoBatch: Earthquakes (history M>=7)
- GoogleMaps: Earthquakes (history M>=7)

Groupthink

2011-03-11T23:03:00.012+01:00

IMF evaluated its role and performance in the recent financial and economic crisis.

Cause

In a 2011 crisis report with the short title: 'IMF Performance in the Run-Up to the Financial and Economic Crisis:IMF Surveillance in 2004–07 ', IMF concludes that the main cause of their inadequate response during the crisis was:

Groupthink

IMF’s ability to detect important vulnerabilities and risks and alert the membership, was undermined by a complex interaction of factors, many of which had been flagged before but had not been fully addressed.

The IMF’s ability to correctly identify the escalating risks was hindered by:

A high degree of groupthink
Intellectual capture
A general mindset that a major financial crisis was unlikely
Inadequate analytical approaches
Weak internal governance
Lack of incentives to work across units and raise contrarian views
A review process that did not “connect the dots” or ensure follow-up
Some impact of 'political constraints'....

Recommendations

IMF suggests some recommendations on how to strengthen its ability to discern risks and vulnerabilities and to warn in the future. Main point is to enhance the effectiveness of surveillance: it is critical to clarify the roles and responsibilities of the Board, Management, and senior staff, and to establish a clear accountability framework.

Looking forward, IMF needs to

Create an environment that encourages candor and considers dissenting views
Modify incentives to “speak truth to power”
Better integrate macroeconomic and financial sector issues
Overcome the silo mentality and insular culture; Deliver a clear, consistent message on the global outlook and risks.

Recognize Groupthink
Groupthink is not just something happening to IMF or 'other organisations'. We, financial institutions, all suffer somehow or somewhat from the Groupthink Virus.

How can we recognize Groupthink?
Derived from an article by Irving Janis, the inventor of the word Groupthink, let's take a look at some explicit signs of Groupthink:

Winning Mood syndrome
A common illusion of success (Folie à deux), invulnerability, over-optimism, unanimity and risk-taking as a consequence.
Collective rationalization
Managers, employees discount warnings and do not reconsider their assumptions
Repression or Ridicule
Direct pressure on and ridicule of individuals who express disagreement with or doubt about the majority view or the view of the leader
Fear
Fear of disapproval for deviating from the group consensus. Fear from or doubt about expressing your opinion.
Manipulating
Remaining silent in a discussion is implicitly interpreted as agreeing.Obviously 'wrong' arguments are used to achieve a certain goal or policy.
Disrespect
Stereotyped views of out-groups or enemy leaders as evil, weak or stupid. Good or serious ideas of colleagues are rejected on basis of the source instead of 'judged by the facts'.
Moral Blindness
Unquestioned belief in the inherent morality of the in-group. Lack of discussion about ethical or moral aspects of certain decision.
Miscommunication and Misinformation
Information, bottom up or top-down is (deliberately) strongly filtered
Idolization
Idolization of the leader or of certain five star employees.

Lessons Learned
If you recognize some of the above signs in your organization, it is time for action.
Discuss it, do not accept it and if you cannot change it... LEAVE!

A humorous example of Misinformation are the quotes of Iraq's minister of (Mis)Informaton, Al-Sahaf, during the 2003 Iraq war.
Enjoy, laugh and learn.....

Make sure your board presentation is not based on' sahaf-statements' but on simple provable actuarial facts....

Related links/sources:
- 8 signs of groupthink
- What is Groupthink?
- IMF Crisis Report 2011

Actuary Bill Gates

2011-03-06T00:24:00.003+01:00

For those of you that -just like me - didn't know that Bill Gates is actually a qualified actuary....

Bill Gates.., a man with a great vision and the same size of philanthropic heart. More information about Bill on the 'Bill and Mellinda Foundation' website, were another actuarial statement is launched:

All Lives Have Equal Value

With all due respect for Obama: Bill gates for president!

Links:
- 2010 Annual Letter from Bill Gates

Supervisory Compliant, is it enough?

2011-03-05T00:29:00.001+01:00

Risk management is tricky business... Being 'Officially Compliant', 'Just Compliant' or in other words "Supervisory Compliant", is not enough to help your CEO survive with your company in the complex market battle!

Whether you're an Actuary or Risk Manager of an Insurance company, Bank or a Pension Fund, the risk of being 'Supervisory Compliant' is simply : bankruptcy!

Becoming 'Supervisory Compliant' in complex programs like Solvency-II, Basel III or Legal Pension Fund Risk Frameworks, consumes so much time and effort, that almost no time seems to be left for contemplating or doing the essential Risk Management work properly.

Just being 'Supervisory Compliant' implies: constantly running after the Supervisor to become 'just in time' officially compliant and not having enough time to think about the (f)actual relevant risks.

Supervisory Compliance becomes very frighting when Risk Appetite and Valuations are rashly based upon the minimum Supervisory requirements, as is (e.g.) the case in the Dutch Pension Fund legal framework. Boards stop thinking about the actual risks and feel compliant and satisfied once the Supervisory Compliance Boxes are checked.

A new look at compliance
Let's take a look from a new point of view at the complete Risk Management Compliance Field:

In basis there are three types of 'being compliant':

Supervisory Compliant
When you're Supervisory Compliant, you officially comply to all legal Risk Management compliance requirements. Your Supervisor is happy...
Professional Compliant
You comply to your own professional Risk Management standards. You are happy... but what about your Supervisor? Comply or Explain....
Success Compliant
Being Success Compliant implies that all Risk Management requirements that are key to have success - e.g. key to survive in the market on the long run - are met.

Let's zoom in at some specific areas in this chart:

Bias areas

It's perhaps hard to admit, but in our attempt to be complete, we define and manage a lot of (small) risks that do actually exist, but are in fact not really or limited relevant with regard to company continuity.

Distinctive Character area

The Distinctive Character area is perhaps the most interesting area. To get grip on this area urges us to 'Think outside the Circle'.

By doing so we'll be able to manage risks that our competitors fail to do. Here we can achieve 'Distinctive Character' by managing risks more efficient or by turning risks into profits. Examples are: Derivatives that limit our investment risks. Specialized experience rating (rate making) on your portfolio on basis of characteristic and unique risk profiles.

Tricky area
The tricky area is the area that consists of Supervisory Risks you tend not to find important, but that are very important for achieving success in the market. Tricky areas could e.g. be: Deflation Risk, Longevity Risk or Take Over Risk.

Reversed Thinking area
This is perhaps the most interesting risk area.

To explore this area you'll not only have to 'think outside of your circle', but - just like in reversed stress tests with Banks - try to think backwards, to find out what could cause a certain event or loss.

This reversed thinking process succeeds best as a group. Group members should be professionals and non-professionals from different types of business, education and background.

A successful group mix could e.g. consist of : an actuary, an accountant, a manager, a marketing manager, a compliance officer, an employee, a client, a shareholder representative and last but not least the receptionist.

Finally.....
Try to find time to manage your company to new heights and stop being just 'Supervisory Compliant'.....

Gold: Risk or Rescue?

2011-02-27T21:54:00.003+01:00

For those of you who are still doubting...we live in a crazy world....

The Dutch Central Bank (DNB) has ordered (by court !) the glass-workers pension fund (SPVG) to decrease its 13% Gold allocation to less than 3% within two months.

DNB and Court arguments in short:

An investment of 13% is not in line with the Prudent Person Rule, which includes the principle that: assets must be invested in such a manner as to ensure the security, quality, liquidity and profitability of the portfolio as a whole.
Gold is a commodity and holding 13% is classified as 'overweight' in comparison to the 2.7% average that Dutch pension funds have invested in commodities.
15% allocation in Gold is a 'concentration risk' that could lead to a coverage shortage if the gold price imploded (volatility of Gold is relatively large).

At first, it seems unbelievable that important decisions, with substantial financial impact - even in Court - are not based on financial facts, but on 'general principles' and the way the market 'used to do it'.

A decision based on an argument that refers to 'the average pension fund,' would more or less imply that pension funds would not be allowed to base their investment strategy on their own specific situation or a changing market outlook. Pension Fund Boards appear to be 'captured' by the market and a Supervisor who obviously has a hard time to develop 'own standards'....

Secondly, DNB actually takes over the investment responsibility of the pension Board. One could wander if DNB is (sufficiently) aware of the possibility that it can be hold financially responsible for the effect of a negative outcome if it turns out in the near future that SPVG has suffered a substantial financial loss, caused by this DNB-designation.

Is Gold really a risk?.... or a rescue?

Checking the facts....
Let's just check if DNB's and Court's arguments are valid.....

Yearly Return
We start by comparing the yearly returns of Gold, the S&P-500 Index and '10-Y Treasury Bonds' over the period 1971-2010.

To make Bonds risk-comparable with Gold and the S&P-500 Index, the yearly average Bond interest rate is translated into a yearly Market Value performance. This is done by assuming that each year, all '10-Y Bonds' bought in a specific year are valued, and sold at the average interest rate one year later (approximation).

Here is the result:

To bring some sense and order into this chart, we calculate the 'Moving Compound Annual Growth Rate' (MCAGR).
We start in 2010 and calculate the compound average yearly return backwards moving up (year by year) to 1971. This is the result:

Now, this looks better... and a bit surprising as well!!! On the long term Gold (μ=9.2%) and the S&P-500 (μ=10.2%) are tending to a rough 9-10% yearly return...... A little bit Surprising is that Bonds (μ=7.6%) get along very well with their big risky brothers...
Take your time to 'absorb' the impact of this chart.....

Risk
Next, we take a look at Risk. We define Risk at first as the Standard Deviation (SD). We directly cut trough to the 'Moving Risk' (Moving SD).

We might conclude here that during recent years there was an increase of risk with regard to the S&P-500 (the 'red' crisis 'Mount K2' is clearly visible). Note that also for a longer period, i.c. the last 30 years, the S&P-500 Risk is substantial higher than the Risk of Gold and much higher than the Risk of Bonds. Only looking at a period of 40 years, Gold shows 'optical' up as more risky (SD=σ=25.8%) than the two other asset categories, Bonds (SD=σ=6.9%) and S&P-500 (SD=σ=18.1%).

However this way of presenting Risk is strongly discussable. Another view of Risk that comes closer to what we naturally 'perceive' as Risk, is to define Risk as only as the Downside Standard Deviation (look up : Sortino ratio ), where all positive yearly returns are eliminated (DSD) or set to zero (DSDZ).....
Let's have a look:

Now, these charts give us a quite a different sight on Risk-reality....
It shows that -on the long term - not Gold (DSD=Dσ=7.5%) is the riskiest asset, but the S&P-500 (DSD=Dσ=10.6%). Bonds (DSD=Dσ=0.5%), as aspected, have the least volatility and are therefore less risky.

Perhaps the Risk of Bonds is a bit underestimated (very few observations) by the DSD-method (excluding positive yearly returns). In this case the downside deviation of yearly Bond-returns, replacing positive returns by zero, which generates a standard deviation of 3.2%, gives a better indication of a more likely standard deviation on the long run.

Why Gold?
Although these simple calculations already put the DNB conclusions in a different light, let's get to the main point that should be addressed in defending why Gold should be a substantial part of any Pension Fund portfolio:

Gold Reduces VaR

In a 2010 (october) publication the World Gold Council published a document called Gold: Hedging Against Tail Risk. This interesting report concludes:

Gold is first and foremost a consistent portfolio diversifier
Gold effectively helps to manage risk in a portfolio, not only by means of increasing risk-adjusted returns, but also by reducing expected losses incurred in extreme circumstances such tail-risk events (VaR).

Following this excellent WGC report, let's test the balancing and risk-reducing power of Gold by analyzing (classical) Risk (SD) in combining Gold with different allocations (0% up to 100%) in an asset mix with Bonds, respectively investments in S&P-500 stocks.

This chart clearly shows that Gold has the power to reduce the S&P-500 Risk (SD) from18.1% to 13,3% with an optimal asset location mix of approximately 60% S&P-500 and 40% Gold.

In case of Bonds the Risk (SD) is reduced from 6.9% to 4.8% with an optimal mix of 80% Bonds and 20% Gold.

Asset Liability Model (ALM)
In practice it is necessary to optimize, by means of an adequate ALM study, the allocation mix of stocks, Bonds and Gold. Just as a 'quick & dirty' excercise, let's take a look at the next asset-combination scenarios, based on data over the period 1971-2010:

Just some head line observations:

From scenario M1 it becomes clear that even a 100% Bond scenario is't free from Risk. So diversification with other assets is a must.
Looking at M2-M5 we find that the optimal mix, defined as the mix that best maximizes Return (Compound Annual Growth Rate) and Sharpe Ratio (at a Risk free rate of 3% or 4%) and minimizes Risk (Standard deviation), is something something in the order of: 70% Bonds, 15% stock and 15% Gold.
Scenarios M6-M8 and M9-M11 take todays most common (but strongly discussable!) practice as a starting point. Most pension funds have allocated around 50% or 40% to Bonds and 50% or 60% in more risky asset categories (stocks, etc.). It's clear that even in this situation Risk can be reduced and Return can be optimized, if Stocks are exchanged to Gold with a maximum allocation of 20% or 30%.

Notifier

Although this 'rule of thumb exercise' on this website provides some basic insights, please keep in mind that finding the optimal mix is work for professionals (actuaries).

A serious ALM Study is always necessary and should not only take into account a broad range of diversified asset categories, but should also focus and optimize on:

The impact of the liabilities (duration) and coverage ratio volatility
The Timing: Mean values and Standard Deviations are great, but the expected return highly depends on the actual moment of investment or divestment in the market.
Future expectations. In the current market situation (2011) the risk of interest rates going up and therefore Bond market value going strongly down, isn't hypothetical. Secondly, the stock market has been pumped up by trillions of 'investments' (?) in the US economy. Once this crisis-aid definitely stops, the question is if these 'cement investments' will be strong enough to keep stocks up. Personally I fear the worst...
Not to mention a scenario with declining stock rates in combination with increasing interest rates and inflation......
Who said the life of an actuary was easy???

Conclusion
We may conclude that:

Investing in Gold up to a 10% to 15% allocation, reduces the Risk of a portfolio consisting of Bonds and S&P-500 Stocks substantially.
Gold is less Risky than investing in S&P-500 Stocks

Therefore the 'not with facts' underpinned intervention of DNB looks - to put it euphemistically - at least strongly discussable....

A wise and modest underpinned allocation of Gold is no Risk, it's a Rescue!

Related Links:
- Spreadsheet with Data used in this Blog
- Prudent person Rule
- IPE: Dutch regulator orders pension scheme to dump gold
- GOLD: HEDGING AGAINST TAIL RISK
- Downside Risk:Sortino ratio
- Dutch Central Bank Orders Pension Fund To Sell Its Gold
- Pension Fund Benchmarking
- Strategic Risk Managment and Risk Monitoring for Pension Funds

Bonus: Gold, Hedging against Tail Risk Video

Pension Fund Weigh House

2011-02-22T00:19:00.000+01:00

Investment Benchmarking of Pension Funds has been made extremely difficult.

Just ask your Pension Fund's actuary whether your Pension Fund has achieved a 'market conform investment performance'... For sure you'll get a dazzling multiform and relative answer. It's all about 'market indexes' (stock and bond indexes), risk appetites, asset mixes, derivatives, uncertainty and lots of other interesting complex stuff that underpins the fact that the final answer to this simple question is nuanced, complex and relative.

A simple question
Ahead of all this growing complexity and 'levels of detail', a first key question has to be answered by every Pension Fund:

Was it worth setting up a complex multi fund investment plan instead of simply investing in 10-Years Government (Treasury) Bonds over an arbitrary period of (at least) the last 10 years?

Even this simple question, will probably not lead to a simply answer from your fund's investment manager or actuary.

Pension Fund Weigh House Help
This is where the help of the 'Pension Fund Weigh House' comes in...

Just look up the yearly return over the last ten years in your Pension Fund's annual report. Next, do the test at 'Pension Fund Weigh House' (PFWH) and see for yourself whether your Pension Fund has performed better than the simple benchmark: 10-Y Bonds.

Did your Pension Fund perform better than Bonds? (the compound mean over the last 10 years) Congratulations!
Was it worth the risk? Well..., just look at the Risk (Standard Deviation) or - even better - the Sharpe Ratio at different levels of possible 'Risk Free Rates' to find out. The Higher the Sharpe Ratio, the more it was worth to take the risk.

Market Value

To compare Bonds 'fair' with Market Value based Pension Fund performance, the yearly Bond interest rate is translated into a yearly Market Value performance. This is done by assuming that each year, all '10-Y Bonds' bought in January of a specific year are valued, and sold at the interest rate one year later.

Do it yourself

The standard example as presented on PFWH concerns the performance of the Dutch pension fund ABP, the third largest pension fund of the world. Answer the key question 'Was it worth?' for ABP for yourself.

ABP (Pfd-R) Performance 2001-2010

Go to PFWH and change the numbers and 'heads' in the application to fit the numbers of your own (pension) fund or change both columns (Bonds & PFD-R) to compare two pension funds .
Compare your pension fund to either '10-Y Euro Government Bonds', '10-Y US Treasury Bonds' or the 'S&P 500 Index'.

From now on you may answer this extremely difficult question "How did my pension fund perform?" yourself in a 5 minute weigh house test.

Have (professional) fun!

Dutch Pension Muppet Show

2011-02-09T23:08:00.004+01:00

There's a lot of fuzz about the performance of the largest (€ 246 billion assets) Dutch Pension Funds ABP and the somewhat smaller (€ 91 billion) PFZW (former PGGM). According the Dutch television program Zembla and Bureau Bosch Asset Consultants, Dutch pension funds would have consistently underperformed.

ABP commented: "The yearly return of 7.1% on average since 1993 is much higher than returns on government bonds would have been and is in part thanks to our equity investments."

PFZW overshoots ABP wit the comment: "PFZW's calculations show a return of 8.4% on average during the past 20 years which is much higher than the 10-year Dutch government bonds of 5.3% on average during the same period."

Great statements, but who's right?

Performance Test
Let's quickly "do the proof" by comparing (benchmarking) the 'modest' yearly performance of ABP with the yearly performance of 10 year Government Euro Bond Yield Benchmark as provided by the ECB.

Both pension funds are not limited to the Dutch market, therefore performance is not related to Dutch Government Bonds, but to 10-Y Euro Government Bonds.

As the yearly performance of ABP in a particular year is in fact a kind of 'compound performance' of the years before, it's more realistic to relate ABP's (yearly) performance to the 10-years moving average of 10-Y Euro Bonds.

What becomes clear from is that ABP's volatility overshadows the 10-year Bond's volatility by far. As a consequence ABP's out-performance should be significant.

Let's test this by looking at the YTD (Year To Date) performance of ABP on the long run:

The average performance of ABP 1993-2010 indeed turns out exactly 7.1% as published, but hardly outperforms the 10-year Euro Bonds Moving average of 6.8%.

0.3% '18-years out-performance' (OP-18) for such a high volatility is strongly discussable. The long term out-performance 1994-2010 (OP-17) was 0.0%. The out-performances of shorter periods (OP-[18-x]) are not stable and strongly swap from positive to negative.

Benchmarking Pension funds performance with Euro Bonds 0f 20 years or longer would be even more adequate and in line with the duration of pension fund's liabilities. Taken into account that 20 year Bonds on average score a 0.25% à 1.00% higher return than 10 year Bonds, it can be concluded that Dutch pension funds on average do not out-perform Government Bonds. Not to mention the influence of the yearly investment-costs of at least 0.2% on the returns.....

Pension Fund PFZW

Pension Fund PFZW is completely lost on their non-transparent and backwards changing performance of 8.4% over the last 20 years.

From their annual (inconsistent) accounts it can be concluded that their 2001-2010 performance came down to 4,8%. This performance is exactly the same as the performance op ABP in that period and underperforms the moving average 10-years Euro Bonds with 0.7% !!!

Conclusion

It's clear that pension funds don't convince in the outperformance of Government Bonds and that the pension industry is in desperate need for an impartial benchmark with regard to out or underperformance of Bonds.

The comments from ABP and PFZW, Boenders and Cocken are like 'shooting from the hip' and must be qualified as highly unprofessional.

Dutch pension fund members are watching an extra edition of the Muppet show. Who's gonna stop this pension media madness and bring some order in the pension room?

Related Links and Sources:

- Source: 10 year Government Euro Bond Yield Benchmark
- 'grave miscalculations' in Zembla (Boender aand Kocken
- Watch: Zembla
- Download: Spreadsheet with calculations as presented
- IPE: Heavyweights ABP, PFZW come out swinging against Zembla
- Bloomberg: 10-year, - - 30-year performance Gv. Bonds