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Showing posts sorted by date for query calculator. Sort by relevance Show all posts

Oct 23, 2022

Why VaR fails and actuaries can do better

Perhaps the most important challenge of an actuary is to develop and train the capability to explain complex matters in a simple way. One of the best examples of practicing this 'complexity reduction ability' has been given by David Einhorn, president of Greenlight Capital. In a nutshell David explains with a simple example why VaR models fail. Take a look at the next excerpt of David's interesting article in Point-Counterpoint.

Why Var fails
A risk manager’s job is to worry about whether the bank is putting itself at risk in unusual times - or, in statistical terms, in the tails of the distribution. Yet, VaR ignores what happens in the tails. It specifically cuts them off. A 99% VaR calculation does not evaluate what happens in the last1%. This, in my view, makes VaR relatively useless as a risk management tool and potentially catastrophic when its use creates a false sense of security among senior managers and watchdogs.
VaR is like an airbag that works all the time, except when you have a car accident
By ignoring the tails, VaR creates an incentive to take excessive but remote risks.
Example
Consider an investment in a coin flip. If you bet $100 on tails at even money, your VaR to a 99% threshold is $100, as you will lose that amount 50% of the time, which obviously is within the threshold. In this case, the VaR will equal the maximum loss.

Compare that to a bet where you offer 127 to 1 odds on $100 that heads won’t come up seven times in a row. You will win more than 99.2% of the time, which exceeds the 99% threshold. As a result, your 99% VaR is zero, even though you are exposed to a possible $12,700 loss.

In other words, an investment bank wouldn’t have to put up any capital to make this bet. The math whizzers will say it is more complicated than that, but this is the idea. Now we understand why investment banks held enormous portfolios of “super-senior triple A-rated” whatever. These securities had very small returns. However, the risk models said they had trivial VaR, because the possibility of credit loss was calculated to be beyond the VaR threshold. This meant that holding them required only a trivial amount of capital, and a small return over a trivial capital can generate an almost infinite revenue-to-equity ratio. VaR-driven risk management encouraged accepting a lot of bets that amounted to accepting the risk that heads wouldn’t come up seven times in a row. In the current crisis, it has turned out that the unlucky outcome was far more likely than the backtested models predicted. What is worse, the various supposedly remote risks that required trivial capital are highly correlated; you don’t just lose on one bad bet in this environment, you lose on many of them for the same reason. This is why in recent periods the investment banks had quarterly write-downs that were many times the firm-wide modelled VaR.

The Real Risk Issues
What. besides the 'art of simple communication', can we - actuaries - learn from David Einhorn? What David essentially tries to tell us, is that we should focus on the real Risk Management issues that are in the x% tail and not on the other (100-x)%. Of course, we're inclined to agree with David. But are we actuaries truly focusing on the 'right' risks in the tail? I'm afraid the answer to this question is most often: No! Let's look at a simple example that illustrates the way we are (biased) focusing on the wrong side of the VaR curve.

Example Longevity
For years (decades) now, longevity risk has been structurally underestimated. Yes, undoubtedly we have learned some of our lessons. Today's longevity calculations are not (anymore) just based on simple straight-on mortality observations of the past. Nevertheless, in our search to grasp, analyze and explain the continuous life span increase, we've got caught in an interesting but dangerous habit of examining more and more interesting details that might explain the variance of future developments in mor(t)ality rates. As 'smart' longevity actuaries and experts, we consider a lot of sophisticated additional elements in our projections or calculations. Just a small inventory of actuarial longevity refinement:
  • Difference in mortality rates: Gender, Marital or Social status, Income or Health related mortality rates
  • Size: Standard deviation, Group-, Portfolio-size
  • Selection effects, Enhanced annuities
  • Extrapolation: Generation tables, longitudinal effects, Autocorrelation, 'Heat Maps'
X-Tails In our increasing enthusiasm to capture the longevity monster, we got engrossed in our work. As experienced actuaries we know the devil is always in the De-Tails, however the question is: In which details? We all know perfectly well that probably the most essential triggers for longevity risk in the future, can not be found in our data. These triggers depend on the effect of new developments like :

It's clear that investigating and modeling the soft risk indicators of extreme longevity is no longer a luxury, as also an exploding increase in lifespan of 10-20% in the coming decades seems not unlikely. By stretching our actuarial research to the medical arena, we would be able to develop new (more) future- and shock-proof longevity models and stress tests. Regrettably, we don't like to skate on thin ice..... Ostrich Management If we - actuaries - would take longevity and our profession as 'Risk Manager' more seriously, we would warn the world about the global estimated (financial) impact of these medical developments on Pension- and Health topics. We would advise on which measures to take, in order to absorb and manage this future risk. Instead of taking appropriate actions, we hide in the dark, maintaining our belief in Fairy-Tails. As unworldly savants, we joyfully keep our eyes on the research of relative small variances in longevity, while neglecting the serious mega risks ahead of us. This way of Ostrich Management is a worrying threat to the actuarial profession. As we are aware of these kinds of (medical) future risks, not including or disclaiming them in our models and advice, could even have a major liability impact. In order to be able to prevent serious global loss, society expects actuaries to estimate and advise on risk, instead of explaining afterward what, why and how things went wrong, what we 'have learned' and what we 'could or should' have done. This way of denying reality reminds me of an amusing Jewish story of the Lost Key...

The lost Key
One early morning, just before dawn, as the folks were on their way to the synagogue for the Shaharit (early morning prayer) they notice Herscheleh under the lamp post, circling the post and scanning the ground. “Herschel” said the rabbi “What on earth are you doing here this time of the morning?” “I lost my key” replied Herscheleh “Where did you lose it?” inquired the rabbi “There” said Herscheleh, pointing into the darkness away from the light of the lamp post. “So why are looking for your key in here if you lost it there”? persisted the puzzled rabbi. “Because the light is here Rabbi, not there” replied Herschel with a smug.





Let's conclude with a quote, that - just as this blog- probably didn't help either:

Risk is not always apparent,
but its invisibility is no longer an excuse for ignoring it.

-- Bankers Trust on risk management, 1995 --


Interesting additional links:


Dec 21, 2014

Actuarial Readability

As an actuary, accountant or financial consultant, deep knowledge, expert skills and experience are key to writing an interesting article or paper advice.

However, no matter how much you're an expert, finally you're as good as you can get your message across to your audience.

The art of the expert is to simplify the complexity of his/her research into simple, and for the audience understandable text.

In practice this implies that the expert will have to measure the readability of his papers before publishing.

The two most important issues to tackle are 'readability' and 'text-level'.

Although there are many sorts of tests, both topics are simply covered by the so called  Flesch-Kincaid Readability Test.

Let's take a look ate the two simple test formulas of this test:



Flesch-Kincaid Readability Test



Flesch Reading Ease Score

FRES = 206.835 – (1.015 x ASL) – (84.6 x ASW)



Flesch-Kincaid Grade Level

FKGL = (0.39 x ASL) + (11.8 x ASW) – 15.59


With:
ASL  = average sentence length
number of words divided by the number of sentences

ASW = average number of syllables per word

number of syllables divided by number of words


Texts with a FRES-score of 90-100 are easily understandable by an average 5th grader and scores between 0 and 30 are best understood by college graduates.

Some examples of readability index scores of magazines:
- Reader's Digest Magazine: FRES = 65
- Time magazine: FRES = 52
- Harvard Law Review: FRES = 30

The FRES-test has become a U.S. governmental standard. Many government agencies require documents or forms to meet specific readability levels. Most states require insurance forms to score 40-50 on the test.


Where to test your documents?

Besides matching the FRES and FKTL scores in your document, as a guideline try to establish the next English text-test-characteristics
  • Average sentence length 15-20 words, 25-33 syllables and 75-100 characters.
  • Characters per word: < 7
  • Syllables per word: 1.5 - 2.0
  • Words per sentence: 15 - 20

This blog text resulted in scores:
- Flesch-Kincaid Reading Ease 64.7
- Flesch-Kincaid Grade Level 7.2
- Characters per Word 4.4
- Syllables per Word 1.5
- Words per Sentence 11.8


Example
As an example we test the readability of one of the articles of the Investment Fallacies e-book, as published by the Society of Actuaries (SOA) :

By Max J. Rudolph, published in 2014

The readability outcome is as follows:


Readability Score 'The Best Model Doesn’t Win'

Reading Ease
A higher score indicates easier readability; scores usually range between 0 and 100.

Readability Formula
Score
48.1

Grade Levels

A grade level (based on the USA education system) is equivalent to the number of years of education a person has had. Scores over 22 should generally be taken to mean graduate level text.

Readability Formula
Grade
10.3
12.9
14.2
9.5
__________________________
10.2
____
Average Grade Level
11.4

Text Statistics
Character Count 7,611
Syllable Count 2,531
Word Count 1,495
Sentence Count 98
Characters per Word 5.1
Syllables per Word 1.7
Words per Sentence 15.3


Actuarial Texts
With regard to public financial or actuarial publications a FRES-score of around 50 assures, that your publication reaches a wide audience. Even in case you're publishing an article at university level, try to keep the FRES-score as high as possible.

If you write an academic paper, you may use the online application Word and Phrase to measure the percentage of academic words. Try to keep this percentage below 20% to keep your document readable. The publication 'The Best Model Doesn’t Win' would score 17% on academic words......


Finally
Next time you write a document or make a PPT presentation, don't forget to




Links:
WORD AND PHRASE

May 4, 2014

Discussing Life-Cycle Pensions & Longevity

In this blog I'm going to discuss two persistent pension topics:

  1. One of the most common misunderstandings in pension fund land is that an individual (member) investment policy weighs up to a collective investment approach.
  2. Is there a rule of thumb that expresses 'longevity risk' in terms of the yearly return?  

1. Collective vs. Individual Investing Approach
In case of a 'healthy pension fund', new members will join as time continues. In a mature pension fund the balance of contributions, investment returns, paid pensions and costs will stabilize over time.

Therefore the duration of the obligations of a pension fund will more or less stabilize as well. The duration of an average pension fund varies often between 15 and 25 years. Long enough to define a long term investment strategy based on a mix of risky equities (e.g. 60%) and fixed income (e.g. 40%). Regardless of age or status, all members of a pension fund profit from this balanced investment approach.




In case of an individual (member) investment strategy, the risk profile of the individual investments has to be reduced as the retirement date comes near. In practice this implies that 'equities' are reduced in favor of 'fixed income' after a certain age. As the age of a pension member progresses, the duration of the individual liabilities also decreases, with an expected downfall in return as a consequence.

Let's compare three different types of investment strategies to get a clear picture of what is happening:

  1. Collective Pension Fund Strategy Approach: Constant Yearly Return
    40% Fixed Income à 4% return + 60% Equities à 6% = 5.2% return yearly
     
  2. Life Cycle I Approach ('100-Age' Method)
    Yearly Return (age X): X% Fixed Income à 4% + (100-X)% Equities à 6%
     
  3. Life Cycle II Approach (Decreasing equities between age 45 and age 65)
    Yearly Return (age X) = MIN(MAX((6%+(44-X)*0.1%);4%);6%)

All visually expressed in the next chart:


Pension Outcomes
Now lets compare the pension outcomes of these three different investment strategies with help of the Pension Excel Calculator on basis of the next assumptions:
- Retirement age: 65 year
- Start ages 20 and 40
- 3% and 0% indexed  contributions and benefits
- Life Table NL Men 2012 (NL=Netherlands)

Results Pension Calculations (yearly paid pension):




Conclusion  I
From the above table we can conclude that switching from a collective investment approach to an individual investment approach will decrease pension benefits with roughly 10%. Think twice before you do so!



2. Longevity Risk Impact
To get an idea of the longevity impact on the pension outcomes, yearly paid pensions are calculated for different forecasted Dutch life tables (Men).

Life Tables



Forecast Life Table 2062 is calculated on basis of a publication of the Royal Dutch Actuarial Association.

The Forecast Life Table 2112 is (non-official; non scientific) calculated on basis of the assumption that for every age the decrease in mortality rate over the period 2062-2112 is the same as over the period 2012-2062.

Pension Outcomes per Life Table
Here are the yearly pension outcomes on basis of the forecasted life tables:













From the above table, we may conclude that the order of magnitude effect of longevity over a fifty to seventy year period is that pensions will have to be cut  roughly by 25%-30%.


Another way of looking at this longevity risk, is to try to fund the future increase in life expectation from the annual returns.

The next table shows the required return to fund the longevity impact for different forecasted life tables:



Roughly speaking, the expected long-term longevity effects take about 0.7%-1.2% of the yearly return on the long run.


Finally
Instead of developing a high tech approach, this blog intended to give you some practical insights in the order of magnitude effects of life-cycle investments and longevity impact on pension plans in general.

Hope you liked it!




Links/Downloads:

Nov 11, 2013

QIS: Longevity Risk Sharing

In a recent discussion about the future and fundamentals of the Dutch pension system I discussed the importance of solidarity.

As expected, the participants quickly came up with the various forms of solidarity, including solidarity between:
– higher and less educated people
– women and men
– old versus young people

Longevity Risk Sharing
Remarkably non of the participants had any idea about the financial impact of one of the most fundamental forms of risk sharing in case of a life annuity: Longevity Risk Sharing. Let's call it in general 'mortality solidarity'.

When asked, most participants strongly underestimated the impact of mortality (mortality share) as part of the yearly payment in the form of a life annuity. On the other hand, they overestimated the impact of 'return'.

Some of the participants had the idea that they would be 'better of' with a traditional individual investment plan in combination with a little more investment risk (and return) ...

Life Annuity Composition
So let's do a mini QIS (Quantitative Impact Study) of 'mortality solidarity' by examining the development of the composition of an annual lifetime annuity, regarding three basic elements: Mortality, Return and Desaving.

Here is the result for a Dutch man, age 65, with a lifetime annuity based on an average 5% yearly return:




Translated in table form:

Yearly Payment CompositionCumulative Composition
AgeMortality Return DesavingMortality Return Desaving
6516%51%33%16%51%33%
6617%50%34%16%50%34%
6718%48%34%17%50%34%
6819%46%34%17%49%34%
6921%45%35%18%48%34%
7022%43%35%19%47%34%
7124%41%35%20%46%34%
7226%39%35%20%45%34%
7328%38%35%21%45%34%
7430%36%34%22%44%34%
7532%34%34%23%43%34%
7634%33%33%24%42%34%
7736%31%33%25%41%34%
7838%30%32%26%40%34%
7941%28%31%27%40%34%
8043%27%30%28%39%34%
8145%25%29%29%38%33%
8248%24%29%30%37%33%
8350%22%28%31%36%33%
8452%21%27%32%36%32%
8555%20%26%33%35%32%
8657%18%25%34%34%32%
8760%17%23%35%33%31%
8862%16%22%36%33%31%
8965%15%20%37%32%31%
9067%14%19%39%31%30%
9169%13%17%40%31%30%
9272%13%16%41%30%29%
9373%12%15%42%29%29%
9475%11%14%43%29%28%
9577%11%12%44%28%28%
9678%10%12%45%28%27%
9779%9%11%46%27%27%
9880%9%11%47%26%26%
9982%8%10%48%26%26%
10083%8%10%49%25%25%
10184%7%9%50%25%25%
10285%7%9%51%25%24%
10385%7%8%52%24%24%
10486%6%8%53%24%24%
10587%6%7%54%23%23%


Observations
As is clear from the table above :
  • Already at the start the start of the annuity, at age 65, 16% of the yearly payment is due to mortality risk sharing and 'only'  51% is related to the 'return'.
  • As a pension member continues to live, the  'mortality share' of the annual payment increases. At the age of 83 already 50% of his annuity is due to mortality effects and the 'return share'  is already down to 22%.
  • As from age 77 of, the 'mortality effect' on the annual payment exceeds the 'return effect'.

Conclusion
From some simple calculations, we can conclude that longevity (mortality) solidarity is a fundamental part of a life annuity.
 

AfterMath
Make your calculations with other interest rates, ages or life tables with the Pension Calculator (Excel).

You may download the pension calculator HERE

Links/Sources

Sep 2, 2013

Pension Egg Choice

Imagine you're a new pension fund member and your pension fund offers you the next simple proposal regarding your future pension income.

With closed eyes you are allowed to take out two 'pension eggs', either from nest I or nest II. Which nest do you choose?

Think about this proposal and remember: your complete financial old age depends solely on the nest of your choice.




I discussed the above dilemma  last week (august 2013) in a presentation with an across-section of Dutch pension representatives. This dilemma illustrates in a simple way the precarious choice Dutch pension funds and their members have to make in deciding between a traditional Nominal Pension with conditional CPI-indexation (nest I) and a fully CPI-indexed 'Real' Pension (nest II).

Key point is that to achieve a higher Real Pension, you have to put your Nominal Pension 'at risk'.
And who is consciously willing to put 'future income' substantial  at risk?

As 'pension income' is in fact 'deferred income', there's also a kind of implicit understanding that your future retirement income security should be 'in line' with your actual income security and not substantial lower.

Retirement Income Security   Actual Income Security ?

No wonder that all of the 23 attendees at my presentation chose Nest I (Nominal + Indexation) as favorite.

Remark
After the meeting one of the attendees stated that the '10'-valued egg in Nest II should have been valued at at least a value of 20 or higher to create an equal or higher average expectation, as higher risk would implicate also higher return.

I positively smiled for a moment... told him that his remark (and many others that followed) was formally right and suggested that he would test the 'Pension Egg Choice' in his pension board, including an extra voting with an 20-valued egg instead of a 10-valued egg. A day later he called me back and told me the extra voting didn't substantial change the voting outcome.......

Remember that more risk doesn't automatically imply more return. If volatility (risk) increases without a well-argued expected increase in 'average return', the 'compound average return' will (even) decrease with half of its variance.

Worldwide Pension Funds Alert
Not only Dutch pension funds face the Pension Egg Dilemma, but in fact all pension funds worldwide do. To fund their pension liabilities they have to make average returns of more than 5%, 6% or even 7% for more than 50 years on a row or more. And to achieve those kind of return levels with a (nominal) risk free rate and a treasury bill outlook, both varying between 2 to 3.5 percent, implies that they'll have to invest in risky asset classes.

As a consequence the ultimate pension outcome could be lower than on basis of a risk free approach that guarantees a nominal pension. In other words: your Nominal pension is at risk.

Example
To illustrate what is happening, let's look at a 30 year old Dutch pension fund member (Tom) with an retirement age of 65.

The pension fund (theoretically) offers Tom the next options. Tom values these options on basis of a 20 year period:
  1. Option 1
    Tom's contribution is invested in totally risk free assets at 3% (
    orange line), resulting in a sure (€,$,£,¥)  10000 yearly pension
     
  2. Option 2
    Tom's contribution is invested in 30% risk free and 70% risky assets (purple line), resulting in a 25.9% (100%-74.1%) change of an outcome below his yearly 10000 (nominal) pension, but also an almost 50% probability of a pension of around 23904 or more.

    Looking closer at the downside, there's also a 10% probability of ending up with a negative return, corresponding with a yearly pension of 4255 a year or less.

However, Tom suddenly realizes the limitations of a linear model approach. If the 'risk free asset part' of his investment  is really completely independent (can't be dragged down) from the risky part and also insensitive to market conditions, there's a downside risk limitation.  A 30% really 'completely market valued risk free' would in Tom's case  imply a total minimal guaranteed portfolio return of nearly 1% (30% of 3% = 0.9% ≈ 1%) , corresponding with a minimal yearly pension benefit level of around 5645.

In case of 70% risk free investment approach (green line), the downside return risk would be limited to a minimal 2.1% return corresponding with a minimal pension of around 7506, approximately 75% of Tom's nominal pension target.

This 70% risk free approach could be quite acceptable for Tom, as he realizes there'll be no extra return without taking extra risk...

Nevertheless..., pension fund life and its member's choices ain't easy. So Tom asks the pension fund's actuary what his pension outcome would be on a 50 year evaluation basis.... here it is


Now Tom's risk of ending up with a yearly pension outcome of 10000 or less has decreased to a 15.3% (100-84.7). Tom could decrease this downside risk further to 8.6% by choosing a less risky asset mix of 70% risk free and 30% risky assets. However, this drops his upside potential. On average (50%) his pension outlook of around 23904 will drop to a little less than 17850.

Now Tom fully starts to grasp the impact of long term return assumptions...  After all, is assuming a 6% or 7% 50-year return not way to optimistic?

Your own Pension Confidence Level Calculator
As shown in the examples above the key questions are i.a. :
  1. How much of your guaranteed* nominal pension P are you willing to risk to end up with a higher pension P+U
  2. How much uncertainty (100% - confidence) are you willing to accept that your pension is lower than a certain amount?
  3. What's the real (nonlinear) downside risk of my pension?

To find the answers to these kind of questions and to calculate your own pension perspective, you may download the

in Excel.

With the Pension Confidence Level Calculator you may calculate your pension confidence with all kind of asset mixes, co-variances, (pension) ages and several user definable life tables.

Remember the calculations are only illustrative and indicative approximations, to be used for instructional purposes. Ask your pension fund to make a more detailed and personal calculation.

Next
Now that you've experienced that most pension funds need an ambitious return that may put your nominal pension at risk, the question is what to do?

Main problem is that pension funds do not act in this alarming situation. As a kind of sitting duck they play a kind of 'waiting game' in the hope that bond yields and other markets recover.

Meanwhile you could at least do something to get the fuzzy pension picture clear. Simply follow this Cookbook :

Pension Fund Restructure Cookbook
  1. Your Retirement Income is not a one point estimate, so ask your pension fund's actuary:
    • to calculate what future average return rate is needed to (100%) fund the liabilities, given the actual market value of the assets of the pension fund
    • to calculate (estimate) your future pension at different constant future return rates
    • to estimate the probability level of achieving each future return rate or more (confidence level) for the rest of your life, in accordance with the applied actuarial models
  2. Next, ask your actuary to formulate his advised investment risk approach in line with the Pension Eggs presentation as presented in this blog, but now with more nests.
  3. Now let your board and pension members determine their risk appetite by voting which nest they choose
  4. Finally, let the actuary in cooperation with the investment advisory committee, propose an 'investment strategy' that is completely in line with the new defined risk appetite 
  5. Take a decision to (phase-wise) implement this new investment strategy.

Result
Perhaps the outcome of the above exercise will be a lower pension than you expected, but:
  • probably not as low as you would have got if you kept on gambling on uncertain high returns 
  • and certainly not lower than what you need and define as a decent minimum pension income 

Anyhow, enjoy the Pension Confidence Level Calculator....

Links/Downloads

Jun 28, 2013

Confidence Level Crisis

When you're - like me - a born professional optimist, but nevertheless sometimes worry about the unavoidable misery in the world, you ask yourself this question:

Why does God not act? 

Think about this question and try to answer it, before reading any further..



The answer to this question is very simple:

God does not act because he's conscious of everything  

The moral of this anecdote is that when you're fully aware of all the risks and their possible impact, chances are high you'll not be able to take any well-argued decision at all, as any decision will eventually fail when your objective is to rule out all possible risks.

You see, a question has come up that we can't agree on,
perhaps because we've read too many books.


Bertolt Brecht, Life of Galileo (Leben des Galilei)

On the other hand, if you're not risk-conscious at all regarding a decision to be taken, most probably you'll take the wrong decision.

'Mathematical Confident'
So this leaves us with the inevitable conclusion that in our eager to take risk-based decisions, a reasoned decision is nothing more than the somehow optimized outcome of a weighted sum of a limited number of subjective perceived risks. 'Perceived' and 'Weighted', thanks to the fact that we're unaware of certain risks, or 'filter', 'manipulate' or 'model' risks in such a way that we can be 'mathematical confident'. In other words, we've become victims of the "My calculator tells me I'm right! - Effect".

Risk Consciousness Fallacy
This way of taking risk based decisions has the 'advantage' that practice will prove it's never quite right. Implying you can gradually 'adjust' and 'improve' or 'optimize' your decision model endlessly.
Endlessly, up to the point where you've included so much new or adjusted risk sources and possible impacts, that the degrees in freedom of being able to take a 'confident' decision have become zero.


Risk & Investment Management Crisis
After a number of crises - in particular the 2008 systemic crisis - we've come to the point that we realize:
  • There are much more types of risk than we thought there would be
  • Most type of risks are nonlinear instead of linear
  • New risks are constantly 'born'
  • We'll not ever be able to identify or significantly control every possible kind of risk
  • Our current (outdated) investment model can't capture nonlinear risk
  • Most (investment) risks depend heavily on political measures and policy
  • Investment risks are more artificial and political based and driven, than statistical
  • Market Values are 'manipulable' and therefore 'artificial'
  • Risk free rates are volatile, unsure and decreasing
  • Traditional mathematical calculated 'confidence levels' fall short (model risk)
  • As Confidence Levels rise, Confidence Intervals and Value at Risk increase

Fallacy
One of the most basic implicit fallacies in investment modeling, is that mathematical confidence levels based on historical data are seen as 'trusted' confidence levels regarding future projections. Key point is that a confidence level (itself) is a conditional (Bayesian) probability .

Let's illustrate this in short.
A calculated model confidence level (CL) is only valid under the 'condition' that the 'Risk Structure' (e.g. mean, standard deviation, moments, etc.) of our analysed historical data set (H) that is used for modeling, is also valid in the future (F). This implies that our traditional confidence level is in fact a conditional probability : P(confidence level = x% | F=H ).

Example
  • The (increasing) Basel III confidence level is set at P( x ∈ VaR-Confidence-Interval | F=H) = 99.9% in accordance with a one year default level of 0.1% (= 1-99,9%).
  • Now please estimate roughly the probability P(F=H), that the risk structure of the historical (asset classes and obligations) data set (H) that is used for Basel III calculations, will also be 100% valid in the near future (F).
  • Let's assume you rate this probability based on the enormous economic shifts in our economy (optimistic and independent) at P(F=H)=95% for the next year.
  • The actual unconditional confidence level now becomes P( x ∈ VaR-Confidence-Interval) = P( x ∈ VaR-Confidence-Interval | F=H) × P(F=H) = 99.9% × 95% = 94.905%
Although a lot of remarks could be made whether the above method is scientifically 100% correct, one thing is sure: traditional risk methods in combination with sky high confidence levels fall short in times of economic shifts (currency wars, economic stagnation, etc). Or in other words:

Unconditional Financial Institutions Confidence Levels will be in line with our own poor economic forecast confidence levels. 



A detailed Societe Generale (SG) report tells us that not only economic forecasts like GDP growth, but also stocks can not be forecasted by analysts.


Over the period 2000-2006 the US average 24-month forecast error is 93% (12-month: 47%). With an average 24-month forecast error of 95% (12-month: 43%), Europe doesn't do any better. Forecasts with this kind of scale of error are totally worthless.

Confidence Level Crisis
Just focusing on sky high risk confidence levels of 99.9% or more is prohibiting financial institutions to take risks that are fundamental to their existence. 'Taking Risk' is part of the core business of a financial institution. Elimination of risk will therefore kill financial institutions on the long run. One way or the other, we have to deal with this Confidence Level Crisis.

The way out
The way for financial institutions to get out of this risk paradox is to recognize, identify and examine nonlinear and systemic risks and to structure not only capital, but also assets and obligations in such a (dynamic) way that they are financial and economic 'crisis proof'. All this without being blinded by a 'one point' theoretical Confidence Level..

Actuaries, econometricians and economists can help by developing nonlinear interactive asset models that demonstrate how (much) returns and risks and strategies are interrelated in a dynamic economic environment of continuing crises.

This way boards, management and investment advisory committees are supported in their continuous decision process to add value to all stakeholders and across all assets, obligations and capital.

Calculating small default probabilities in the order of the Planck Constant (6.626 069 57 x 10-34 J.s) are useless. Only creating strategies that prevent defaults, make sense.

Let's get more confident! ;-)

Sources/Links
- SG-Report: Mind Matters (Forecasting fails)
Are Men Overconfident Users?

Nov 17, 2012

Pension for Contribution

People are lost if it comes down to their pension. A recent (2012) Friends Life survey found that 68% of Britons do not know the collective value of their pension funds.....

This result is in line with a Dutch 2011 survey, that concludes that 66% has no knowledge of their pension.

Pension illiteracy is clearly a worldwide phenomenon. Pensions are a 'low interest' product. Unfortunately - nowadays - in the double sense of the latter words.

As an actuary, people often ask me at a birthday party : I'm paying a 1000 bucks contribution each year for my pension, but does it pay out in the end? Can you tell me?

Unfortunately most actuaries, including myself, answer this question by telling that this is a difficult question to answer straightforward and that the pension outcome depends on topics like age, mortality, return, inflation, gender, indexation, investment scheme, asset mix, etc., etc.....

Simplifying
To make a breakthrough in this pension communication paradox, let's try to create more pension insight with a simple approach. But remember - as with everything in life - the word 'simple' implies that we can not be complete as well as consistent at the same time. After all, Kurt Gödel's incompleteness theorems clearly show that nothing in life can be both complete and consistent at the same time.

Thanks to God and Gödel, we can stay alive on this planet by simplifying everything in life to a level that our brains can comprise. We'll keep it that way in this blog as well.

How much pension Benefits for how much contribution?
First thing to do, is to give the average low pension interested person on this planet an overall hunch on what a yearly investment of a 1000 bucks(first simplification: S1)until the pension age of 65 year (S2) delivers in terms of a yearly pension as of age 65 in case of an average pension fund.

If we state 'bucks' here, we mean your local general currency. We denote 'bucks' here simply as $, or leave it out. So $ stands for €, ¥ , £ or even $ itself.

Now let's calculate for different pension contribution start ages (S3)what a yearly contribution of $ 1000 (payable in months at the beginning of each month; S4), pays back in terms of a yearly pension (payable in months at the end of each month; S5) on basis of a set of different constant return rates (S6). The calculation is on a net basis (so without costs; S7), a Dutch (2008) mortality table (S8) and without any inflation (S9), any pension indexation (S10), any contribution indexation (S11), or any tax influence (S12).

Here's the simple table we're looking for:

TABLE 1
Yearly Pension at age 65 on basis of 1000 yearly contribution
Pension Indexation=0%, Contribution Indexation=0%, Inflation: 0%
StartNet Yearly Return Rate
Age0%1%2%3%4%5%6%7%8%
252692366950196898952113192183362555335681
30234531134134550373429812131331760123612
3519992584333543045555717192571194915421
40165420842614327340925109637079339867
45131116101964238828963502422550856107
5097211631380163219212254263530723570
5563874486098911321291146516571868
60312355400448499554612674738

In a graphical view on a logarithmic pension benefits scale, it looks something like this:

Example
To illustrate what is happening, a simple example:
When you join your pension fund at age 40 and start saving $ 1000 a year (the first of every month: $ 83.33) until your 65, you'll receive a yearly pension benefit of $ 4092 yearly ( $ 341 at the end of every month) from age 65 of, as long as you live.

From this table, we can already draw some very basic conclusions:
  • To build up a substantial pension, it pays out if you start early in life
  • The pension outcome is heavily dependent on the yearly return of your pension fund
  • Most pension funds operate on basis of a 'general employee and/or employer contribution' instead of individual employee contributions.
    This implies that younger employees pay more than they should have paid on an individual basis and older employees less. In other words, younger employees subsidize older employees. How much more, you can derive from the tables above and by comparing the individual contributions to the general contribution level of the pension fund.


Pension Indexation
As we all want to protect our pension against inflation, let's calculate the outcome of a 'real pension' instead of a 'nominal pension'. As long term yearly inflation rates vary between 2% and 3%, we make the same calculation as above, but now the yearly pension outcome (as from age 65) will be indexed with 3% (fixed) at the end of every year and the yearly contribution paid, will also be yearly indexed with 3%.
Here's the outcome:

TABLE 2
Yearly Pension at age 65 on basis of 1000 yearly contribution
Pension Indexation=3%, Contribution Indexation=3%, Inflation: 0%
StartNet Yearly Return Rate
Age0%1%2%3%4%5%6%7%8%
2536874914656688141188916112219332997841124
302947385950516624870711468151382002126526
35230929683803487262417994102401311916809
401760221827813479434454136735836810382
45128815901949238128973515425151276168
5088210661277152318072134251229443440
555366337418629981149131615021706
60243281321364411461515573634

To get grip at the comparison between a real and a nominal pension, we express the real pension (3% Indexed Pensions and Contribution) as a percentage of the nominal pension:

TABLE 3
Yearly Pension at age 65 on basis of 1000 yearly contribution
'3% P&C-Indexed Pensions' as percentage '0% P&C-Indexed Pensions'
StartNet Yearly Return Rate
Age0%1%2%3%4%5%6%7%8%
25137%134%131%128%125%122%120%117%115%
30126%124%122%120%119%117%115%114%112%
35116%115%114%113%112%111%111%110%109%
40106%106%106%106%106%106%106%105%105%
4598%99%99%100%100%100%101%101%101%
5091%92%93%93%94%95%95%96%96%
5584%85%86%87%88%89%90%91%91%
6078%79%80%81%82%83%84%85%86%

From this last table we can conclude that if you start saving for your pension below the age of 40 your indexed savings weight up to the indexed pension. Above the age of 45 it is the other way around.

The above figures are the kind of figures (magnitude) you'll find on your benefits statements. You can compare in practice whether your benefit statement is in line with the above tables....

The Inflation Monster
In the last given example, pension is 3% inflation protected as from the moment of retirement.

However, if pension is not also yearly fully indexed (in this case: 3%) during the contribution period, there still is a major potential inflation erosion risk left.

In this case it's interesting to examine what the value of a 3% indexed pension in combination with a 3% indexed contribution is worth in terms of actual money, as inflation would continue at a constant 3% level each year. Here's the answer:

TABLE 4
Yearly Pension at age 65 on basis of 1000 yearly contribution
Pension Indexation=3%, Contribution Indexation=3%, Inflation: 3%
StartNet Yearly Return Rate
Age0%1%2%3%4%5%6%7%8%
251130150720132702364549396724919012607
30104713711795235430944076538071159427
3595112231567200725713293421954056925
4084110591328166220752586321739974959
457138801079131816041946235428393415
5056668482097711601370161218902208
5539947155264274285597911171269
60210242277314355398445494547

What we notice is a substantial inflation erosion effect as the pension fund participants get younger.
Let's zoom in on an example to see what we can achieve with these tables.

Example
  • From table 2 we can conclude that - at a 4% return rate - a 40 year old starting pension fund member, with a $ 1000 dollar yearly 3% indexed contribution will reach a 3% yearly indexed pension of $ 4344 yearly at age 65.
  • From table 4 we can subsequently conclude that, based on an inflation rate of 3%, this $ 4344 pension has a 'real' value of $ 2075, if it's expressed in the value money had when the participant was 40 years old (so, at the start).
  • From table 4 we can also conclude that in order to 'compensate' inflation erosion for this pension member, the pension fund has to achieve a return of around 7.4%.
    This follows from simple linear interpolation:
    7,4% = 7% + 1% * (4344-3997)/(4959-3997)

I'll leave other examples to your own imagination.

The effect of a constant inflation on a pension is devastating, as the next table shows

TABLE 5
Inflation Erosion
  • Pension indexation=3%
    as of age 65
  • Contribution indexation=3%
  • Inflation=3%
Start
Age
Inflation
Erosion
2569%
3064%
3559%
4052%
4545%
5036%
5526%
6014%
From table 5 it becomes clear that Inflation erosion is indeed substantial.
If you have a fully indexed pension from age 65 (who has?) of and you're N years away from your retirement, an inflation of i% will erode your pension with E%. In formula:
         
Example
Set inflation to 3%. If you're 40 years old and about to retire at 65, you've got 25 years (N=25=65-40) ahead of you.

If your pension of let's say $ 10,000 a year is not indexed during this period, you can buy with this $ 10,000 no more than you could buy today with $ 4,800.

Your pension is eroded due to inflation with 52% = 1- 1.03^-25. So only 48% is left.....

Finally
I trust these tables and examples contribute a little to your pension insight. Just dive into your pension, it's financially relevant and certainly will pay out!
Remember that all results and examples in this blog are approximations and simplifications on a net base (no costs or taxes are included). In practice pension funds or insurers have tot charge costs for administration, asset management, solvency, guarantees, mortality risk, etc. . This implies that in practice the results could differ strongly with the results as shown in this blog. The examples in this blog are therefore for learning and demonstration purposes only.

The above calculations were made in a few minutes with help of the Excel Pension Calculator that was developed in 2011 and updated in 2012.
With help of this pension planner you can calculate all kind of variations and set different variables, including different mortality tables (or even define your own mortality table).

You can download the pension calculator for free and make your own pension calculations.
More information about pension calculating with this simple pension calculator at:


Enjoy your pension, beware of inflation....

Links & Sources: