Archive for the ‘Assumptions’ category

Major Regime Change – The Debt Crisis

May 24, 2011

A regime change is a corner that you cannot see around until you get to it.  It is when many of the old assumptions no longer hold.  It is the start of a new set of patterns.  Regime changes are not necessarily bad, but they are disruptive.  Many of the things that made people and companies successful under the old regime will no longer work.  But there will be completely new things that will now work.

The current regime has lasted for over 50 years.  Over that time, debt went all in one direction – UP.  Most other financial variables went up and down over that time, but their variability was in the context of a money supply that was generally growing somewhat faster than the economy.

Increasing debt funds some of the growth that has fueled the world economies over that time.

But that was a ride that could not go on forever.  At some point in time the debt servicing gets to be too high in comparison to the capacity of the economy.  The economy has gone through the stage of hedge lending (see Financial Instability) where activities are able to afford payments on their debt as well as repayment of principal long ago.  The economy is in the stage of Speculative Finance where activities are able to afford payments on the debt, but not the repayment of principal.  The efforts to pay down debt will tell us whether it is possible to reverse course on that.  If one looks ahead to the massive pensions crisis that looms in the moderate term, then you would likely judge that the economy is in Ponzi Financing land where the economy can neither afford the debt servicing or the payment of principal.

All this seems to be pointing towards a regime change regarding the level of debt and other forward obligations in society.  With that regime change, the world economy may shift to a regime of long term contraction in the amount of debt or else a sudden contraction (default) followed by a long period of massive caution and reduced lending.

Riskviews does not have a prediction for when this will happen or what other things will change when that regime change takes place.  But risk managers are urged to take into account that any models that are calibrated to historical experience may well mislead the users.  And market consistent models may also mislead for long term decision making (or is that will continue to mislead for long term decision making – how else to characterize a spot calculation) until the markets come to incorporate the impact of a regime change.

This may be felt in terms of further extension of the uncertainty that has dogged some markets since the financial crisis or in some other manner.

However it materializes, we will be living in interesting times.

Advertisements

Systemic Risk, Financial Reform, and Moving Forward from the Financial Crisis

April 22, 2011

A second series of essays from the actuarial profession about the financial crisis.  Download them  HERE.

A Tale of Two Density Functions
By Dick Joss

The Systemic Risk of Risk Capital (Or the "No Matter What" Premise)
By C. Frytos &I.Chatzivasiloglou

Actuaries and Assumptions
By Jonathan Jacobs

Managing Financial Crises, Today and Beyond
By Vivek Gupta

What Did We Learn from the Financial Crisis?
By Shibashish Mukherjee

Financial Reform: A Legitimate Function of Government
By John Wiesner

The Economy and Self-Organized Criticality
By Matt Wilson

Systemic Risk Arising from a Financial System that Required Growth in a World with Limited Oil Supply
By Gail Tverberg

Managing Systemic Risk in Retirement Systems
By Minaz Lalani

Worry About Your Own Systemic Risk Exposures
By Dave Ingram

Systemic Risk as Negative Externality
By Rick Gorvette

Who Dares Oppose a Boom?
By David Merkel

Risk Management and the Board of Directors–Suggestions for Reform
By Richard Leblanc

Victory at All Costs
By Tim Cardinal and Jin Li

The Financial Crisis: Why Won't We Use the F(raud) Word?
By Louise Francis

PerfectSunrise–A Warning Before the Perfect Storm
By Max Rudolph

Strengthening Systemic Risk Regulation
By Alfred Weller

It's Securitization Stupid
By Paul Conlin

I Want You to Feel Your Pain
By Krzysztof Ostaszewski

Federal Reform Bill and the Insurance Industry
By David Sherwood

What’s Next?

March 25, 2011

Turbulent Times are Next.

At BusinessInsider.com, a feature from Guillermo Felices tells of 8 shocks that are about to slam the global economy.

#1 Higher Food Prices in Emerging Markets

#2 Higher Interest Rates and Tighter Money in Emerging Markets

#3 Political Crises in the Middle East

#4 Surging Oil Prices

#5 An Increase in Interest Rates in Developed Markets

#6 The End of QE2

#7 Fiscal Cuts and Sovereign Debt Crises

#8 The Japanese Disaster

How should ideas like these impact on ERM systems?  Is it at all reasonable to say that they should not? Definitely not.

These potential shocks illustrate the need for the ERM system to be reflexive.  The system needs to react to changes in the risk environment.  That would mean that it needs to reflect differences in the risk environment in three possible ways:

  1. In the calibration of the risk model.  Model assumptions can be adjusted to reflect the potential near term impact of the shocks.  Some of the shocks are certain and could be thought to impact on expected economic activity (Japanese disaster) but have a range of possible consequences (changing volatility).  Other shocks, which are much less certain (end of QE2 – because there could still be a QE3) may be difficult to work into model assumptions.
  2. With Stress and Scenario Tests – each of these shocks as well as combinations of the shocks could be stress or scenario tests.  Riskviews suggest that developing a handful of fully developed scenarios with 3 or more of these shocks in each would be the modst useful.
  3. In the choices of Risk Appetite.  The information and stress.scenario tests should lead to a serious reexamination of risk appetite.  There are several reasonable reactions – to simply reduce risk appetite in total, to selectively reduce risk appetite, to increase efforts to diversify risks, or to plan to aggressively take on more risk as some risks are found to have much higher reward.

The last strategy mentioned above (aggressively take on more risk) might not be thought of by most to be a risk management strategy.  But think of it this way, the strategy could be stated as an increase in the minimum target reward for risk.  Since things are expected to be riskier, the firm decides that it must get paid more for risk taking, staying away from lower paid risks.  This actually makes quite a bit MORE sense than taking the same risks, expecting the same reward for risks and just taking less risk, which might be the most common strategy selected.

The final consideration is compensation.  How should the firm be paying people for their performance in a riskier environment?  How should the increase in market risk premium be treated?

See Risk adjusted performance measures for starters.

More discussion on a future post.

Where to Draw the Line

March 22, 2011

“The unprecedented scale of the earthquake and tsunami that struck Japan, frankly speaking, were among many things that happened that had not been anticipated under our disaster management contingency plans.”  Japanese Chief Cabinet Secretary Yukio Edano.

In the past 30 days, there have been 10 earthquakes of magnitude 6 or higher.  In the past 100 years, there have been over 80 earthquakes magnitude 8.0 or greater.  The Japanese are reputed to be the most prepared for earthquakes.  And also to experience the most earthquakes of any settled region on the globe.  By some counts, Japan experiences 10% of all earthquakes that are on land and 20% of all severe earthquakes.

But where should they, or anyone making risk management decisions, draw the line in preparation?

In other words, what amount of safety are you willing to pay for in advance and what magnitude of loss event are you willing to say that you will have to live with the consequences.

That amount is your risk tolerance.  You will do what you need to do to manage the risk – but only up to a certain point.

That is because too much security is too expensive, too disruptive.

You are willing to tolerate the larger loss events because you believe them to be sufficiently rare.

In New Zealand,  that cost/risk trade off thinking allowed them to set a standard for retrofitting of existing structures of 1/3 of the standard for new buildings.  But, they also allowed 20 years transition.  Not as much of an issue now.  Many of the older buildings, at least in Christchurch are gone.

But experience changes our view of frequency.  We actually change the loss distribution curve in our minds that is used for decision making.

Risk managers need to be aware of these shifts.  We need to recognize them.  We want to say that these shifts represent shifts in risk appetite.  But we need to also realize that they represent changes in risk perception.  When our models do not move as risk perception moves, the models lose fundamental credibility.

In addition, when modelers do things like what some of the cat modeling firms are doing right now, that is moving the model frequency when people’s risk perceptions are not moving at all, they also lose credibility for that.

So perhaps you want scientists and mathematicians creating the basic models, but someone who is familiar with the psychology of risk needs to learn an effective way to integrate those changes in risk perceptions (or lack thereof) with changes in models (or lack thereof).

The idea of moving risk appetite and tolerance up and down as management gets more or less comfortable with the model estimations of risk might work.  But you are still then left with the issue of model credibility.

What is really needed is a way to combine the science/math with the psychology.

Market consistent models come the closest to accomplishing that.  The pure math/science folks see the herding aspect of market psychology as a miscalibration of the model.  But they are just misunderstanding what is being done.  What is needed is an ability to create adjustments to risk calculations that are applied to non-traded risks that allow for the combination of science & math analysis of the risk with the emotional component.

Then the models will accurately reflect how and where management wants to draw the line.

Risk Management Success

March 8, 2011

Many people struggle with clearly identifying how to measure the success of their risk management program.

But they really are struggling with is either a lack of clear objectives or with unobtainable objectives.

Because if there are clear and obtainable objectives, then measuring success means comparing performance to those objectives.

The objectives need to be framed in terms of the things that risk management concentrates upon – that is likelihood and severity of future problems.

The objectives need to be obtainable with the authority and resources that are given to the risk manager.  A risk manager who is expected to produce certainty about losses needs to either have unlimited authority or unlimited budget to produce that certainty.

The most difficult part of judging the success of a risk management program is when those programs are driven by assessments of risk that end up being totally insufficient.  But again the real answer to this issue is authority and budget.  If the assumptions of the model are under the control of the risk manager, that is totally under the risk manager’s control, then the risk manager would be prudent to incorporate significant amounts of margin either into the model or into the processes that use the model for model risk.  But then the risk manager is incented to make the model as conservative as their imagination can make it.  The result will be no business – it will all look too risky.

So a business can only work if the model assumptions are the join responsibility of the risk manager and the business users.

But there are objectives for a risk management program that can be clear and obtainable.  Here are some examples:

  1. The Risk Management program will be compliant with regulatory and/or rating agency requirements
  2. The Risk Management program will provide the information and facilitate the process for management to maintain capital at the most efficient level for the risks of the firm.
  3. The Risk Management program will provide the information and facilitate the process for management to maintain profit margins for risk (pricing in insurance terms) at a level consistent with corporate goals.
  4. The Risk Management program will provide the information and facilitate the process for management to maintain risk exposures to within corporate risk tolerances and appetites.
  5. The Risk Management program will provide the information and facilitate the process for management and the board to set and update goals for risk management and return for the organization as well as risk tolerances and appetites at a level and form consistent with corporate goals.
  6. The Risk Management program will provide the information and facilitate the process for management to avoid concentrations and achieve diversification that is consistent with corporate goals.
  7. The Risk Management program will provide the information and facilitate the process for management to select strategic alternatives that optimize the risk adjusted returns of the firm over the short and long term in a manner that is consistent with corporate goals.
  8. The Risk Management program will provide information to the board and for public distribution about the risk management program and about whether company performance is consistent with the firm goals for risk management.

Note that the firm’s goals for risk management are usually not exactly the same as the risk management program’s goals.  The responsibility for achieving the risk management goals is shared by the management team and the risk management function.

Goals for the risk management program that are stated like the following are the sort that are clear, but unobtainable without unlimited authority and/or budget as described above:

X1  The Risk Management program will assure that the firm maintains profit margins for risk at a level consistent with corporate goals.

X2  The Risk Management program will assure that the firm maintains risk exposures to within corporate risk tolerances and appetites so that losses will not occur that are in excess of corporate goals.

X3  The Risk Management program will assure that the firm avoids concentrations and achieve diversification that is consistent with corporate goals.

X4  The Risk Management program will assure that the firm selects strategic alternatives that optimize the risk adjusted returns of the firm over the short and long term in a manner that is consistent with corporate goals.

The worst case situation for a risk manager is to have the position in a firm where there are no clear risk management goals for the organization (item 4 above) and where they are judged on one of the X goals but which one that they will be judged upon is not determined in advance.

Unfortunately, this is exactly the situation that many, many risk managers find themselves in.

Regime Change

February 18, 2011

In risk modeling, the idea of regime change is a mathematical expression.  A change from one mathematical rule to another.

But in the world, Regime Change can have a totally different meaning.  Like what is happening in Egypt.

When someone sits atop a government for 30 years, it is easy to assume that next week they will still be on top.

Until that is no longer true.

When there is a regime change, it happens because the forces that were in a stable equilibrium shift in some way so that they can no longer support a continuation of the past equilibrium.  In hindsight, it is possible to see that shift.  But the shift is often not so obvious in advance.

Again, as when the Soviet Union fell apart, the intelligence services were seemingly taken by surprise.

But is there really any difference between the two types of regime change?  Is it any easier to actually notice an impending regime change on a modeled risk than an impending political risk?

Why are we so bad at seeing around corners?

In the area of public health, it is well known that diseases follow a standard path called an S curve.  That is the path of a curve plotting the number of people infected by a disease over time.  The path has a slight upward slope at first then the slope gets much, much steeper and eventually it slows down again.

When a new disease is noticed, some observers who come upon information about the disease during that middle period during the rapid upward slope will extrapolate and predict that the disease incidence will grow to be much higher than it ever gets.

The reason for the slowdown in the rate of growth of the disease is because diseases are most often self limiting because people do not usually get the disease twice.  Diseases are spread by contact between a carrier and an uninfected person.  In the early stages of a disease, the people who make the most contacts with others are the most likely to become infected and themselves become carriers.  Eventually, they all lose the ability to be carriers and become immune and the number of times that infected carriers come into contact with uninfected persons starts to drop.  Eventually, such contacts become rare.

It is relatively easy to build a model of the progression of a disease.  We know what parameters are needed.  We can easily estimate those that we cannot measure exactly and can correct our estimates as we make observations.

We start out with of model of a disease that assumes that the disease is not permanent.

We plan for regime change.

Perhaps that is what we need for the rest of our models.  We should start out by assuming that no pattern that we observe is permanent.  That each regime carries the seeds of its own destruction.

If we start out with that assumption, we will look to build the impermanence of the regime into our models and look for the signs that will show that whatever guesses we had to make initially about the path of the next regime change can be improved.

Because when we build a model that does not include that assumption, we do not even think about what might cause the next regime change.  We do not make any preliminary guesses.  The signs that the next change is coming are totally ignored.

In the temperate zones where four very different seasons are the norm, the signs of the changes of seasons are well known and widely noticed.

The signs of the changes in regimes of risks can be well known and widely noticed as well, but only if we start out with a model that allows for regime changes.

Sins of Risk Measurement

February 5, 2011
.
Read The Seven Deadly Sins of Measurement by Jim Campy

Measuring risk means walking a thin line.  Balancing what is highly unlikely from what it totally impossible.  Financial institutions need to be prepared for the highly unlikely but must avoid getting sucked into wasting time worrying about the totally impossible.

Here are some sins that are sometimes committed by risk measurers:

1.  Downplaying uncertainty.  Risk measurement will always become more and more uncertain with increasing size of the potential loss numbers.  In other words, the larger the potential loss, the less certain you can be about how certain it might be.  Downplaying uncertainty is usually a sin of omission.  It is just not mentioned.  Risk managers are lured into this sin by the simple fact that the less that they mention uncertainty, the more credibility their work will be given.

2.  Comparing incomparables.  In many risk measurement efforts, values are developed for a wide variety of risks and then aggregated.  Eventually, they are disaggregated and compared.  Each of the risk measurements are implicitly treated as if they were all calculated totally consistently.  However,  in fact, we are usually adding together measurements that were done with totally different amounts of historical data, for markets that have totally different degrees of stability and using tools that have totally different degrees of certitude built into them.  In the end, this will encourage decisions to take on whatever risks that we underestimate the most through this process.

3.  Validate to Confirmation.  When we validate risk models, it is common to stop the validation process when we have evidence that our initial calculation is correct.  What that sometimes means is that one validation is attempted and if validation fails, the process is revised and tried again.  This is repeated until the tester is either exhausted or gets positive results.  We are biased to finding that our risk measurements are correct and are willing to settle for validations that confirm our bias.

4.  Selective Parameterization.  There are no general rules for parameterization.  Generally, someone must choose what set of data is used to develop the risk model parameters.  In most cases, this choice determines the answers of the risk measurement.  If data from a benign period is used, then the measures of risk will be low.  If data from an adverse period is used, then risk measures will be high.  Selective paramaterization means that the period is chosen because the experience was good or bad to deliberately influence the outcome.

5.  Hiding behind Math.  Measuring risk can only mean measuring a future unknown contingency.  No amount of fancy math can change that fact.  But many who are involved in risk measurement will avoid ever using plain language to talk about what they are doing, preferring to hide in a thicket of mathematical jargon.  Real understanding of what one is doing with a risk measurement process includes the ability to say what that entails to someone without an advanced quant degree.

6.  Ignoring consequences.  There is a stream of thinking that science can be disassociated from its consequences.  Whether or not that is true, risk measurement cannot.  The person doing the risk measurement must be aware of the consequences of their findings and anticipate what might happen if management truly believes the measurements and acts upon them.

7.  Crying Wolf.  Risk measurement requires a concentration on the negative side of potential outcomes.  Many in risk management keep trying to tie the idea of “risk” to both upsides and downsides.  They have it partly right.  Risk is a word that means what it means, and the common meaning associated risk with downside potential.  However, the risk manager who does not keep in mind that their risk calculations are also associated with potential gains will be thought to be a total Cassandra and will lose all attention.  This is one of the reasons why scenario and stress tests are difficult to use.  One set of people will prepare the downside story and another set the upside story.  Decisions become a tug of war between opposing points of view, when in fact both points of view are correct.

There are doubtless many more possible sins.  Feel free to add your favorites in the comments.

But one final thought.  Calling it MEASUREMENT might be the greatest sin.


%d bloggers like this: