Archive for the ‘Diversification’ category

The Big C is behind every great Risk

March 30, 2015

Concentration, defined broadly, is the source of all risk.

In an unconcentrated pool of activities, all with potential for positive and negative outcomes, provides the Big D – Diversification.

So it seems simple to avoid C – just do D.

But we have so many ways to concentrate.  And concentration is particularly tempting.

  • When things are going well, it makes sense to do more of whatever it is that is working best.  That increases concentration. 
  • Once we learn how to do something right, it makes sense to do more.  That increases concentration.
  • One supplier is almost always the cheapest, fastest and best quality.  So we give them more business.  That increases concentration. 
  • That one product has better margins than the rest and it sells better too.  So we plan to increase our capacity to make that product.  That increases concentration. 
  • Our best distributor runs rings around the rest.  We are working on giving her a larger territory.  That increases concentration. 

The alternative, the diversifying alternative just doesn’t sound so smart.

  • Hold back when things are going well.
  • Do more of the things that you haven’t quite mastered.
  • Buy from the second and third best suppliers.
  • Keep up capacity for the lower margin lower selling products.
  • Restrict your best distributor from selling too much.

Remember Blockbuster?  There were Blockbuster stores everywhere fifteen years ago.  They did that one thing, rent physical videos through physical stores and did it so well that they drove out most of their competition.  But they were totally Concentrated.  When they were faced with a new competitor, Netflix, the CEO proposed changes to their business practices, including diversifying into online rentals.  Their board decided against going into a new lower margin product and fired the CEO.  Five years later, Blockbuster was toast.

Concentration risk is often strategic.

In the financial crisis, we found a new sort of concentration risk.  It was a network risk.  The banks were all highly concentrated in the financial sector – in exposure to other banks.  This network risk is now often called systemic risk.  But this risk is necessary because of the strategic choices of business models of the banks.  They all choose to do business in such a way to take up each other’s slack on a daily basis.  They all think that is much more efficient than operating with an irregular amount of slack resources.  In times running up to the financial crisis, the interdependency changed from just taking up each other’s overnight slack to some banks using that overnight facility from other banks to fund major fraction of their business activity.  (And woe is all that much of that business activity was fundamentally a loser. But that lack of underwriting by the banks of each other is a different story.)

Why is concentration risk so deadly?  The answer to that is pretty simple arithmetic.  If your conglomerate amounts to four similar sized separate divisions that do not interact so much, it is quite possible that if one of those businesses fails, that the conglomerate will be able to continue operating – wounded but fully able to operate the other three divisions.  But if your cousin’s venture has just one highly profitable, highly successful business, then his venture will either live or die with that one business.

In insurance, we see this concentration risk all of the time.  If you are an insurer that only writes business throughout the Pacific islands in the 1700’s, but you find that your best salesperson is on Easter Island and your highest margin product is business interruption insurance for the businesses that do the carving of the massive Moai statues.  So you do more and more business with your best salesperson selling your best product, until you are essentially a one product, one location insurer.  And then the last tree is used (or rats eat the roots).  All of your customers make claims at once.  You thought that you were diversified because you had 300 separate customers.  But those 300 customers all acted like just one when the trees were gone.

So diversification is not just about counting.  It is about understanding the differences or similarities of your risks.  And failure to understand those drivers will often lead to dangerous concentration.  Just ask those banks or that Easter Island insurer.

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Too Much Risk

August 18, 2014

Risk Management is all about avoiding taking Too Much Risk.

And when it really comes down to it, there are only a few ways to get into the situation of taking too much risk.

  1. Misunderstanding the risk involved in the choices made and to be made by the organization
  2. Misunderstanding the risk appetite of the organization
  3. Misunderstanding the risk taking capacity of the organization
  4. Deliberately ignoring the risk, the risk appetite and/or the risk taking capacity

So Risk Management needs to concentrate on preventing these four situations.  Here are some thoughts regarding how Risk Management can provide that.

1. Misunderstanding the risk involved in the choices made and to be made by an organization

This is the most common driver of Too Much Risk.  There are two major forms of misunderstanding:  Misunderstanding the riskiness of individual choices and Misunderstanding the way that risk from each choice aggregates.  Both of these drivers were strongly in evidence in the run up to the financial crisis.  The risk of each individual mortgage backed security was not seriously investigated by most participants in the market.  And the aggregation of the risk from the mortgages was misunderestimated as well.  In both cases, there was some rationalization for the misunderstanding.  The Misunderstanding was apparent to most only in hindsight.  And that is most common for misunderstanding risks.  Those who are later found to have made the wrong decisions about risk were most often acting on their beliefs about the risks at the time.  This problem is particularly common for firms with no history of consistently and rigorously measuring risks.  Those firms usually have very experienced managers who have been selecting their risks for a long time, who may work from rules of thumb.  Those firms suffer this problem most when new risks are encountered, when the environment changes making their experience less valid and when there is turnover of their experienced managers.  Firms that use a consistent and rigorous risk measurement process also suffer from model induced risk blindness.  The best approach is to combine analysis with experienced judgment.

2.  Misunderstanding the risk appetite of the organization

This is common for organizations where the risk appetite has never been spelled out.  All firms have risk appetites, it is just that in many, many cases, no one knows what they are in advance of a significant loss event.  So misunderstanding the unstated risk appetite is fairly common.  But actually, the most common problem with unstated risk appetites is under utilization of risk capacity.  Because the risk appetite is unknown, some ambitious managers will push to take as much risk as possible, but the majority will be over cautious and take less risk to make sure that things are “safe”.

3.  Misunderstanding the risk taking capacity of the organization

 This misunderstanding affects both companies who do state their risk appetites and companies who do not.  For those who do state their risk appetite, this problem comes about when the company assumes that they have contingent capital available but do not fully understand the contingencies.  The most important contingency is the usual one regarding money – no one wants to give money to someone who really, really needs it.  The preference is to give money to someone who has lots of money who is sure to repay.  For those who do not state a risk appetite, each person who has authority to take on risks does their own estimate of the risk appetite based upon their own estimate of the risk taking capacity.  It is likely that some will view the capacity as huge, especially in comparison to their decision.  So most often the problem is not misunderstanding the total risk taking capacity, but instead, mistaking the available risk capacity.

4.  Deliberately ignoring the risk, the risk appetite and/or the risk taking capacity of the organization

A well established risk management system will have solved the above problems.  However, that does not mean that their problems are over.  In most companies, there are rewards for success in terms of current compensation and promotions.  But it is usually difficult to distinguish luck from talent and good execution in a business about risk taking.  So there is a great temptation for managers to deliberately ignore the risk evaluation, the risk appetite and the risk taking capacity of the firm.  If the excess risk that they then take produces excess losses, then the firm may take a large loss.  But if the excess risk taking does not result in an excess loss, then there may be outsized gains reported and the manager may be seen as highly successful person who saw an opportunity that others did not.  This dynamic will create a constant friction between the Risk staff and those business managers who have found the opportunity that they believe will propel their career forward.

So get to work, risk managers.

Make sure that your organization

  1. Understands the risks
  2. Articulates and understands the risk appetite
  3. Understands the aggregate and remaining risk capacity at all times
  4. Keeps careful track of risks and risk taking to be sure to stop any managers who might want to ignore the risk, the risk appetite and the risk taking capacity

Ignoring a Risk

October 31, 2013

Ignoring is perhaps the most common approach to large but infrequent risks.

Most people think of a 1 in 100 year event as something so rare as it will never happen.

But just take a second and look at the mortality risk of a life insurer.  Each insured has on average around a 1 – 2 in 1000 likelihood of death in any one year.  However, life insurers do not plan for zero claims.  They plan for 1 -2 in 1000 of their policies to have a death claim in any one year.  No one thinks it odd that something with a 1-2 in 1000 likelihood happens hundreds of times in a year.  No one goes around scoffing at the validity of the model or likelihood estimate because such a rare event has happened.

But somehow, that seemingly totally simple minded logic escapes most people when dealing with other risks.  They scoff at how silly that it is that so many 1 in 100 events happen in a year.  Of course, they say, such estimated of likelihood MUST be wrong.

So they go forth ignoring the risk and ignoring the attempts at estimating the expected frequency of loss.  The cost of ignoring a low frequency risk is zero in most years.

And of course, any options for transferring such a risk will have both an expected frequency and an uncertainty charge built in.  Which make those options much too expensive.

The big difference is that a large life insurer takes on hundreds of thousands and in the largest cases, millions of exposures to the 1-2 in 1000 risks. Of course, the law of large numbers turns these individual ultra low frequency risks into a predictable claims pattern, in many cases one with a fairly tight distribution of possible claims.

But because they are ignored, no one tries to know how many of those 1 in 100 risks that we are exposed to.  But the statistics of 20 or 50 or 100 totally unrelated 1 in 100 risks is exactly the same as the life insurance math.

With 100 totally unrelated independent 1 in 100 risks, the chance of one or more turning into a loss in any one year is 63%!

And the most common reaction to the experience of a 1 in 100 event happening is to decide that the statistics are all wrong!

After Superstorm Sandy, NY Governor Cuomo told President Obama that NY “has a 100-year flood every two years now.”  Cuomo had been governor for less than two full years at that point.

The point is that organizations must go against the natural human impulse to separately decide to ignore each of their “rare” risks and realize that the likelihood of experiencing one of these rare events is not so rare, what is uncertain is which one.

Diversification of Risks

January 22, 2013

There are records showing that the power of diversification of risks was known to the ancients.  Investors who financed trading ships clearly favored taking fractions of a number of ships to owning all of a single ship.

The benefits of diversification are clear.  The math is highly compelling.  A portfolio of n risks of the same size A that truly independent have a volatility that is a fraction of the volatility of totally dependent risks.

Here is a simple example.  There is a 1 in 200 chance that a house will be totally destroyed by fire.  Company A writes an insurance policy on one $500,000 house that would pay for replacement in the event of a total loss.  That means that company A has a 1 in 200 chance of paying a $500,000 claim.  Company B decides to write insurance that pays a maximum of $50,000 in the event of a total loss.  How many policies do you think that Company B needs to write to have a 1 in 200 chance of paying $500,000 of claims if the risks are all totally independent and exactly as prone to claims as the $500k house?

The answer is an amazing 900 policies or 90 times as much insurance!

When an insurer is able to write insurance on independent risks, then with each additional risk, the relative volatility of the book of insurance decreases.  Optimal diversification occurs when the independent risks are all of the same size.  For insurers, the market is competitive enough that the company writing the 900 policies is not able to get a profit margin that is proportionate to the individual risks.  The laws of micro economics work in insurance to drive the profit margins down to a level that is at or below the level that makes sense for the actual risk retained.  This provides the most compelling argument for the price for insurance for consumers, they are getting most of the benefit of diversification through the competitive mechanism described above.  Because of this, things are even worse for the first insurer with the one policy.  To the extent that there is a competitive market for insurance for that one $500k house, that insurer will only be able to get a profit margin that is commensurate with the risk of a diversified portfolio of risks. 

It is curious to note than in many situations, both insurers and individuals do not diversify.  RISKVIEWS would suggest that may be explained by imagining that they either forget about diversification when making single decisions (they are acting irrationally), or that they are acting rationally and believe that the returns for the concentrated risk that they undertake are sufficiently large to justify the added risk.

The table below shows the degree to which individuals in various large companies are acting against the principle of diversification.

concentration

From a diversification point of view, the P&G folks above are mostly like the insurer above that writes the one $500k policy.  They may believe that P&G is less risky than a diversified portfolio of stocks.  Unlike the insurer, where the constraint on the amount of business that they can write is the 1/200 loss potential, the investor in this case is constrained by the amount of funds to be invested.  So if a $500k 401k account with P&G stock has a likelihood of losing 100% of value of 1/200, then a portfolio of 20 $25k positions in similarly risky companies would have a likelihood of losing 15% of value of 1/1000.  Larger losses would have much lower likelihood.

With that kind of math in its favor, it is hard to imagine that the holdings in employer stock in the 401ks represents a rational estimation of higher returns, especially not on a risk adjusted basis.

People must just not be at all aware of how diversification benefits them.

Or, there is another explanation, in the case of stock investments.  It can be most easily framed in terms of the Capital Asset Pricing Theory(CAPM) terms.  CAPM suggests that stock market returns can be represented by a market or systematic component (beta) and company specific component (alpha).  Most stocks have a significantly positive beta.  In work that RISKVIEWS has done replicating mutual find portfolios with market index portfolios, it is not uncommon for a mutual fund returns to be 90% explained by total market returns.  People may be of the opinion that since the index represents the fund, that everything is highly correlated to the index and therefore not really independent.

The simplest way to refute that thought is to show the variety of returns that can be found in the returns of the stocks in the major sectors:

Sectors

The S&P 500 return for 2012 was 16%.  Clearly, all sectors do not have returns that are closely related to the index, either in 2012 or for any other period shown here.

Both insurance companies and investors can have a large number of different risks but not be as well diversified as they would think.  That is because of the statement above that optimal diversification results when all risks are equal.  Investors like the 401k participants with half or more of their portfolio in one stock may have the other half of their money in a diversified mutual fund.  But the large size of the single position is difficult to overcome.  The same thing happens to insurers who are tempted to write just one, or a few risks that are much larger than their usual business.  The diversification benefit of their large portfolio of smaller risks disappears quickly when they add just a few much larger risks.

Diversification is the universal power tool of risk management.  But like any other tool, it must be used properly to be effective.

This is one of the seven ERM Principles for Insurers

Where is the Metric for Diversity?

June 18, 2012

“What gets measured, gets managed.” – Peter Drucker

By gaetanlee, via Wikimedia Commons

It seems that while diversification is widely touted as the fundamental principle behind insurance and behind risk management in general, there is no general measure of diversity. So based upon Drucker’s rule of thumb RISKVIEWS would say that we all fail to manage diversity.

A measure of diversity would tell us when we take more similar risks and when we are taking more distinct risks.  But we do not even look.

This may well be another part of good financial management that has been stolen by the presumptions of financial economics.  Financial economics PRESUMES that we all have full diversification.  It tells us that we cannot get paid for our lack of diversification.

But those presumptions are untested and untestable, at least as long as we fail to even measure diversity.

Correlation is the best measure that we have and it is barely used.  For the most part, correlation is used mainly to look at macro portfolio effects on Economic Capital Models.  And it is not a particularly good measure of diversity anyway.  It actually only measures a certain type of statistical comovement of data.  For example, below is a chart that shows that equity market comovement is increasing.

But have the activities of the largest companies in those markets been converging?  Or is this picture just an artifact of the continuing Euro crisis? In either case, if we were looking at a measure of diversity, rather than just comovement, we might have an idea whether this chart makes any sense or not.

Many believe that they are protected by indexing.  That an index is automatically diverse.  But there is little guarantee of that.  Particularly for a market-value weighted index.  In fact, a market-values weighted index is almost guaranteed to have less diversity just when it is needed most.

For a clear indication of that look at the TSX index during the internet bubble Nortel represented 35% of the index!  Concentration increases risk.  In this case, the results were disastrous for any indexers. While Nortel stock rose in the Dot Com mania, buyers of the TSX index were holding a larger and larger fraction of their investment in a single stock.

We badly need a metric for diversity.

 

The Danger of Optimization

November 21, 2011

RISKVIEWS was recently asked “How do insurers Optimize Risk and Reward?”

The response was “That is dangerous. Why do you want to know that?” You see, a guru must always answer a question with a question. And in this case, RISKVIEWS was being treated as a guru.

Optimizing risk and reward is dangerous because it is done with a model.  Not all things that use a model are dangerous.  But Optimizing is definitely dangerous.

One definition of optimizing is

“to make as perfect as possible.”

Most often, optimization means taking maximum possible advantage of the diversification effect.  You will often hear someone talking about the ability to add risk without adding capital.  Getting a free ride on risk.

There are two reasons that optimizing ends up being dangerous…

  1. The idea of adding risk without adding capital is a misunderstanding.  Adding risk always adds risk.  It may well not add to a specific measure of risk because of either size or correlation or both, but the risk is there.  The idea that adding a risk that is low correlation with the firm’s predominant risk is a free ride will sooner or later seep into the minds of the people who ultimately set the prices.  They will start to think that it is just fine to give away some or all of the risk premium and eventually to give up most of the risk margin because there is thought to be no added risk.  This free risk idea will also lead to possibly taking on too much of that uncorrelated risk.  More than one insurer has looked at an acquisition of a large amount of the uncorrelated risk where the price for the acquisition only makes sense with a diminished risk charge.  But with the acquisition, the risk becomes a major concentration of loss potential and suddenly, the risk charge is substantial.
  2. In almost all cases, the best looking opportunities, based on the information that you are getting out of the model are the places where the model is in error, where the model is missing one or more of the real risks.  Those opportunities will look to have unusually fat risk premiums. To the insurer with the incorrect model, those look like extra margin.  This is exactly what happened with the super senior tranches of sub prime mortgage securities.  If you believed the standard assumption that house prices would never go down, there was no risk in the super senior, but they paid 5 – 10 bps more than a risk free bond.

The reliance on a model for optimization is dangerous.

That does not mean that the model is always dangerous.  The model only becomes dangerous when there is undue reliance is placed upon the exact accuracy of the model, without regard for model error and/or parameter uncertainty.

The proper use of the model is Risk Steering.  The model helps to determine the risks that should be held steady, which risks would be good to grow (as long as the environment stays the same as what the model assumes) and which risk to reduce.

Diversity and Resilience

September 19, 2011

Can’t we all just learn to “Get it Right”?

Just picture a ship with a large flat deck and thousands of passengers on the deck. The boat lists to one side and the passengers scurry to the other side to avoid going over the edge in the side that is dipping. Guess what happens? The boat now lists to the other side. Stabilizing the boat requires that everyone is spread about the entire deck. But since we do not necessarily know the exact spots where everyone needs to stand, some moving around makes sense. Just as long as everyone does not start moving together.

The world we live in is a much more complex and dynamic system than a ship at sea. We definitely do not know what is the safest course of action for everyone to take. We do know what hasn’t worked. We suspect that some of the things that we thought did work in the past were actually not good ideas. We do not know how to get the world to go backwards in time to when things were working best. In fact, they weren’t working best for someone then anyway.

Diversity is the most sensible approach when we do not know what will work. With a diversified approach it is quite possible that some will be doing the exact wrong thing, but at the same time, some will be doing the best thing for what comes next.

Only if we are certain of what will come next can we be sure to pick the best course. When too many people pick any single course of action, however, there often are unintended consequences.
Never before had mortgage loans in the US all gone down together, but when everyone started to increase the amount of leverage in the mortgage system, the leverage itself became the cause of massive correlation.

Ecological systems that are more diverse are more resilient. Human systems are the same.


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