Archive for the ‘Correlation’ category

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
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Risk Portfolio Management

April 18, 2013

In 1952, Harry Markowitz wrote the article “Portfolio Selection” which became the seed for the theory called Modern Portfolio Theory. Modern Portfolio Theory (MPT) promises a path to follow to achieve the maximum return for a given level of risk for an investment portfolio.

It is not clear who first thought to apply the MPT ideas to a portfolio of risks in an insurer. In 1974, Gustav Hamilton of Sweden’s Statsforetag proposed the “risk management circle” to describe the interaction of all elements in the risk management process, including assessment, control, financing and communication. In 1979, Randell Brubaker wrote about “Profit Maximization for a multi line Property/Liability Company.” Since then, the idea of risk and reward optimization has become to many the actual definition of ERM.

Standard & Poor’s calls the process “Strategic Risk Management”.

“Strategic Risk Management is the Standard & Poor’s term for the part of ERM that focuses on both the risks and returns of the entire firm. Although other aspects of ERM mainly focus on limiting downside, SRM is the process that will produce the upside, which is where the real value added of ERM lies.“

The Risk Portfolio Management process is nothing more or less than looking at the expected reward and loss potential for each major profit making activity of an insurer and applying the Modern Portfolio Management ideas of portfolio optimization to that risk and reward information.

At the strategic level, insurers will leverage the risk and reward knowledge that comes from their years of experience in the insurance markets as well as from their enterprise risk management (ERM) systems to find the risks where their company’s ability to execute can produce better average risk-adjusted returns. They then seek to optimize the risk/reward mix of the entire portfolio of insurance and investment risks that they hold. There are two aspects of this optimization process. First is the identification of the opportunities of the insurer in terms of expected return for the amount of risk. The second aspect is the interdependence of the risks. A risk with low interdependency with other risks may produce a better portfolio result than another risk with a higher stand alone return on risk but higher interdependence.

Proposals to grow or shrink parts of the business and choices to offset or transfer different major portions of the total risk positions can be viewed in terms of risk-adjusted return. This can be done as part of a capital budgeting/strategic resource allocation exercise and can be incorporated into regular decision-making. Some firms bring this approach into consideration only for major ad hoc decisions on acquisitions or divestitures and some use it all the time.

There are several common activities that may support the macro- level risk exploitation.

Economic Capital
Economic capital (EC) flows from the Provisioning principle. EC is often calculated with a comprehensive risk model consistently for all of the actual risks of the company. Adjustments are made for the imperfect correlation of the risks. Identification of the highest-concentration risks as well as the risks with lower correlation to the highest-concentration risks is risk information that can be exploited. Insurers may find that they have an advantage when adding risks to those areas with lower correlation to their largest risks if they have the expertise to manage those risks as well as they manage their largest risks.

Risk-adjusted product pricing
Another part of the process to manage risk portfolio risk reward involves the Consideration principle. Product pricing is “risk-adjusted” using one of several methods. One such method is to look at expected profits as a percentage of EC resulting in an expected return-to-risk capital ratio. Another method reflects the cost of capital associated with the economic capital of the product as well as volatility of expected income. The cost of capital is determined as the difference between the price to obtain capital and the rate of investment earnings on capital held by the insurer. Product profit projections then will show the pure profit as well as the return for risk of the product. Risk-adjusted value added is another way of approaching risk-adjusted pricing.

Capital budgeting
The capital needed to fulfill proposed business plans is projected based on the economic capital associated with the plans. Acceptance of strategic plans includes consideration of these capital needs and the returns associated with the capital that will be used. Risk exploitation as described above is one of the ways to optimize the use of capital over the planning period. The allocation of risk capital is a key step in this process.

Risk-adjusted performance measurement (RAPM)
Financial results of business plans are measured on a risk-adjusted basis. This includes recognition of the cost of holding the economic capital that is necessary to support each business as reflected in risk-adjusted pricing as well as the risk premiums and loss reserves for multi-period risks such as credit losses or casualty coverages. This should tie directly to the expectations of risk- adjusted profits that are used for product pricing and capital budgeting. Product pricing and capital budgeting form the expectations of performance. Risk-adjusted performance measurement means actually creating a system that reports on the degree to which those expectations are or are not met.

For non-life insurers, Risk Portfolio Management involves making strategic trade-offs between insurance, credit (on reinsurance ceded) and all aspects of investment risk based on a long-term view of risk-adjusted return for all of their choices.

Insurers that do not practice Portfolio Risk Management usually fail to do so because they do not have a common measurement basis across all of their risks. The recent move of many insurers to develop economic capital models provides a powerful tool that can be used as the common risk measure for this process. Economic capital is most often the metric used to define risk in the risk/reward equation of insurers.

Some insurers choose not to develop an EC model and instead rely upon rating agency or regulatory capital formulas. The regulatory and rating agency capital formulas are by their nature broad market estimates of the risk capital of the insurer. These formulae will over-state the capital needs for some of the insurer’s activity and understate the needs for others. The insurer has the specific data about their own risks and can do a better job of assessing their risks than any outsider could ever do. In some cases, insurers took high amounts of catastrophe exposure or embedded guarantee and option risks, which were not penalized in the generic capital formulas. In the end, some insurers found that they had taken much more risk than their actual loss tolerance or capacity.

Risk Portfolio management provides insurers with the framework to take full advantage of the power of diversification in their risk selection. They will look at their insurance and investment choices based on the impact, after diversification, on their total risk/reward profile. These insurers will also react to the cycles in risk premium that exist for all of their different insurance risks and for all of their investment risks in the context of their total portfolio.

Sales of most insurance company products result in an increase in the amount of capital needed by the business due to low or negative initial profits and the need to support the new business with Economic Capital. After the year of issue, most insurance company products will show annual releases of capital both due to the earnings of the product as well as the release of supporting capital that is no longer needed due to terminations of prior coverages. The net capital needs of a business arise when growth (new sales less terminations) is high and/or profits are low and capital is released when growth is low and/or profits are high.

The definition of the capital needs for a product is the same as the definition of distributable earnings for an entire business: projected earnings less the increase in Economic Capital. The capital budgeting process will then focus on obtaining the right mix of short and long term returns for the capital that is needed for each set of business plans.

Both new and existing products can be subjected to this capital budgeting discipline. A forecast of capital usage by a new product can be developed and used as a factor in deciding which of several new products to develop. In considering new and existing products, capital budgeting may involve examining historic and projected financial returns.

Pitfalls of Risk Portfolio Management

In theory, optimization processes can be shown to produce the best results for practitioners. And for periods of time when fluctuations of experience are moderate and fall comfortably within the model parameters, continual fine tuning and higher reliance on the modeled optimization recommendations produce ever growing rewards for the expert practitioner. However, model errors and uncertainties are magnified when management relies upon the risk model to lever up the business. And at some point, the user of complex risk models will see that levering up their business seems to be a safe and profitable way to operate. When volatility shifts into a less predictable and/or higher level, the highly levered company can find it self quickly in major trouble.

Even without major deviations of experience, the Risk Portfolio Management principles can lead to major business disruptions. When an insurer makes a major change in its risk profile through an acquisition or divestiture of a large part of their business, the capital allocation of all other activities may shift drastically. Strict adherence to theory can whipsaw businesses as the insurer makes large changes in business.

Insurers need to be careful to use the risk model information to inform strategic decisions without overreliance and abdication of management judgment. Management should also push usage of risk and reward thinking throughout the organization. The one assumption that seems to cause the most trouble is correlation. The saying goes that “in a crisis, all correlations go to one”. If the justification for a major strategic decision is that correlations are far from one, management should take note of the above saying and prepare accordingly. In addition management should study the variability of correlations over time. They will find that correlations are often highly unreliable and this should have a major impact on the way that they are used in the Risk Portfolio Management process.

Risk Portfolio Management 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.

 

Ford does some Real ERM Thinking

February 28, 2012

Ford shifted their pension fund investment strategy to overweight in bonds.  See Business Insider Story 

This is a clear example of real ERM thinking. 

For at least 40 years, pension plans have been investing in equities and they have claimes that since they have a long investment horizon, that they were immune to concerns about the fluctuations. 

But what has happened instead is that company after company has built up a very large equity exposure.  If they figured their real corporate risk profile, management would see how exposed that they are to stock market risk. 

Ford did some real ERM thinking when they realized that their business risk was fairly highly correlated to the stock market.  So by investing their pension plan assets in the stock market, they were assuring that investors would see their pension plan funding levels faulter just when their business was sputtering. 

There are two aspects of real ERM thinking here.  First, Ford looked past the fiction of the separate pension fund to realize that the company was really exposed to the risk of equity fluctuations.  Second, they realized the true correlations that face their business and its risks. 

Risk managers need to think outside the lines that we draw just like Ford did.   The banks did not do that when they lent money to hedge funds to purchase Mortgage CDOs. 

Risk managers need to look for risks that are likely to hit together and prepare to reduce the likely impact of the combined risk exposure by whatever means makes the msot sense.

Echo Chamber Risk Models

June 12, 2011

The dilemma is a classic – in order for a risk model to be credible, it must be an Echo Chamber – it must reflect the starting prejudices of management. But to be useful – and worth the time and effort of building it – it must provide some insights that management did not have before building the model.

The first thing that may be needed is to realize that the big risk model cannot be the only tool for risk management.  The Big Risk Model, also known as the Economic Capital Model, is NOT the Swiss Army Knife of risk management.  This Echo Chamber issue is only one reason why.

It is actually a good thing that the risk model reflects the beliefs of management and therefore gets credibility.  The model can then perform the one function that it is actually suited for.  That is to facilitate the process of looking at all of the risks of the firm on the same basis and to provide information about how those risks add up to make up the total risk of the firm.

That is very, very valuable to a risk management program that strives to be Enterprise-wide in scope.  The various risks of the firm can then be compared one to another.  The aggregation of risk can be explored.

All based on the views of management about the underlying characteristics of the risks. That functionality allows a quantum leap in the ability to understand and consistently manage the risks of the firm.

Before creating this capability, the risks of each firm were managed totally separately.  Some risks were highly restricted and others were allowed to grow in a mostly uncontrolled fashion.  With a credible risk model, management needs to face their inconsistencies embedded in the historical risk management of the firm.

Some firms look into this mirror and see their problems and immediately make plans to rationalize their risk profile.  Others lash out at the model in a shoot the messenger fashion.  A few will claim that they are running an ERM program, but the new information about risk will result in absolutely no change in risk profile.

It is difficult to imagine that a firm that had no clear idea of aggregate risk and the relative size of the components thereof would find absolutely nothing that needs adjustment.  Often it is a lack of political will within the firm to act upon the new risk knowledge.

For example, when major insurers started to create the economic capital models in the early part of this century, many found that their equity risk exposure was very large compared to their other risks and to their business strategy of being an insurer rather than an equity mutual fund.  Some firms used this new information to help guide a divestiture of equity risk.  Others delayed and delayed even while saying that they had too much equity risk.  Those firms were politically unable to use the new risk information to reduce the equity position of the group.  More than one major business segment had heavy equity positions and they could not choose which to tell to reduce.  They also rejected the idea of reducing exposure through hedging, perhaps because there was a belief at the top of the firm that the extra return of equities was worth the extra risk.

This situation is not at all unique to equity risk.   Other firms had the same experience with Catastrophe risks, interest rate risks and Casualty risk concentrations.

A risk model that was not an Echo Chamber model would be any use at all in these situation above. The differences between management beliefs and the model assumptions of a non Echo Chamber model would result in it being left out of the discussion entirely.

Other methods, such as stress tests can be used to bring in alternate views of the risks.

So an Echo Chamber is useful, but only if you are willing to listen to what you are saying.

A Wealth of Risk Management Research

December 15, 2010
The US actuarial profession has produced and/or sponsored quite a number of risk management research projects.  Here are links to the reports: 

It’s Usually the Second Truck

July 8, 2010

In many cases, companies survive the first bout of adversity.

It is the second bout that kills.

And more often than not, we are totally unprepared for that second hit.

Totally unprepared because of how we misunderstand statistics.

First of all, we believe that large loss events are unlikely and two large loss events are extremely unlikely.  So we decide not to prepare for the extremely unlikely event that we get hit by two large losses at the same time.  And in this case, “at the same time” may mean in subsequent years.  Some who look at correlation, only use an arbitrary calendar year split out of experience data.  So that they would consider losses in the third and fourth quarter to be happening at the same time but fourth quarter and first quarter of the next year would be considered different periods and therefore might show low correlations!

Second, we fail to deal with our reduced capacity immediately after a major loss event.  We still think of our capacity as it was before the first hit.  A part of our risk management plans for a major loss event should have been to immediately initiate a process to rationalize our risk exposures with our newly reduced capacity.  This may in part be due to the third issue.

Third, we misunderstand that the fact of the first event does not reduce the likelihood of the other risk events.  Those joint probabilities that made the dual event, no longer apply.  In fact, with the reduced capacity, the type of even that would incapacitate the firm has suddenly become much more likely.

Most companies that experience one large loss event do not experience a second shortly thereafter, but many companies that fail do.

So if your interest is to reduce the likelihood of failure, you should consider the two loss event situation as a scenario that you prepare for.

But those preparations will present a troubling alternative.  If, after the first major loss event, the actions needed include a sharp reduction in retained risk position, that will severely reduce the likelihood of growing back capacity.

Management is faced with a dilemma – that is two choices, neither of which are desirable.   But as with most issues in risk management, better to face those issues in advance and to make a reasoned plan, rather than looking away and hoping for the best.

But on further reflection, this issue can be seen to be one of over concentration in a single risk.  Some firms have reacted to this whole idea by setting their risk tolerance such that any one loss event will be limited to their excess capital.  Their primary strategy for this type of concentration risk is in effect a diversification strategy.

Comprehensive Actuarial Risk Evaluation

May 11, 2010

The new CARE report has been posted to the IAA website this week.

It raises a point that must be fairly obvious to everyone that you just cannot manage risks without looking at them from multiple angles.

Or at least it should now be obvious. Here are 8 different angles on risk that are discussed in the report and my quick take on each:

  1. MARKET CONSISTENT VALUE VS. FUNDAMENTAL VALUE   –  Well, maybe the market has it wrong.  Do your own homework in addition to looking at what the market thinks.  If the folks buying exposure to US mortgages had done fundamental evaluation, they might have noticed that there were a significant amount of sub prime mortgages where the Gross mortgage payments were higher than the Gross income of the mortgagee.
  2. ACCOUNTING BASIS VS. ECONOMIC BASIS  –  Some firms did all of their analysis on an economic basis and kept saying that they were fine as their reported financials showed them dying.  They should have known in advance of the risk of accounting that was different from their analysis.
  3. REGULATORY MEASURE OF RISK  –  vs. any of the above.  The same logic applies as with the accounting.  Even if you have done your analysis “right” you need to know how important others, including your regulator will be seeing things.  Better to have a discussion with the regulator long before a problem arises.  You are just not as credible in the middle of what seems to be a crisis to the regulator saying that the regulatory view is off target.
  4. SHORT TERM VS. LONG TERM RISKS  –  While it is really nice that everyone has agreed to focus in on a one year view of risks, for situations that may well extend beyond one year, it can be vitally important to know how the risk might impact the firm over a multi year period.
  5. KNOWN RISK AND EMERGING RISKS  –  the fact that your risk model did not include anything for volcano risk, is no help when the volcano messes up your business plans.
  6. EARNINGS VOLATILITY VS. RUIN  –  Again, an agreement on a 1 in 200 loss focus is convenient, it does not in any way exempt an organization from risks that could have a major impact at some other return period.
  7. VIEWED STAND-ALONE VS. FULL RISK PORTFOLIO  –  Remember, diversification does not reduce absolute risk.
  8. CASH VS. ACCRUAL  –  This is another way of saying to focus on the economic vs the accounting.

Read the report to get the more measured and complete view prepared by the 15 actuaries from US, UK, Australia and China who participated in the working group to prepare the report.

Comprehensive Actuarial Risk Evaluation

Take CARE in evaluating your Risks

February 12, 2010

Risk management is sometimes summarized as a short set of simply stated steps:

  1. Identify Risks
  2. Evaluate Risks
  3. Treat Risks

There are much more complicated expositions of risk management.  For example, the AS/NZ Risk Management Standard makes 8 steps out of that. 

But I would contend that those three steps are the really key steps. 

The middle step “Evaluate Risks” sounds easy.  However, there can be many pitfalls.  A new report [CARE] from a working party of the Enterprise and Financial Risks Committee of the International Actuarial Association gives an extensive discussion of the conceptual pitfalls that might arise from an overly narrow approach to Risk Evaluation.

The heart of that report is a discussion of eight different either or choices that are often made in evaluating risks:

  1. MARKET CONSISTENT VALUE VS. FUNDAMENTAL VALUE 
  2. ACCOUNTING BASIS VS. ECONOMIC BASIS         
  3. REGULATORY MEASURE OF RISK    
  4. SHORT TERM VS. LONG TERM RISKS          
  5. KNOWN RISK AND EMERGING RISKS        
  6. EARNINGS VOLATILITY VS. RUIN    
  7. VIEWED STAND-ALONE VS. FULL RISK PORTFOLIO       
  8. CASH VS. ACCRUAL 

The main point of the report is that for a comprehensive evaluation of risk, these are not choices.  Both paths must be explored.

All Things Being Equal

January 26, 2010

is a phrase that is left out more often than left in when it is actually a key and seldom true assumption behind an argument.

If you are talking about risk and risk models, that phrase should be a red flag.  If the phrase is actually stated, the risk manager should immediately challenge it.  Because when a major risk becomes a loss or threatens to become a loss, very rarely are all things equal.

Most, and possibly all, major loss situations have ripple effects.  These ripple effects may be direct or they may be because they affect people who then in turn take actions that cause other unusual things to happen.

Here is a map of how the World Economic Forum thinks that the major risks of the world are interconnected:

Another example of a problem with the “All things Being Equal” assumption is the discussion of inflation.  Few people remember to say it but when they worry that addional money in the system due to direct Fed actions or Stimulus spending will cause inflation – that would be true – ALL THINGS BEING EQUAL.  But in fact, they are not equal, or even close to equal.

What is different is the amount of money that was in the system prior to the crisis other than the money from the Fed and the Stimulus.  The losses suffered by the banks and the shrinkage of loans and the inability of consumers and businesses to get loans – each of those things REDUCES the amount of money in the economy.  So in no stretch of the imagination are all things equal.

So the old rule about government spending being inflationary is only true ALL THINGS BEING EQUAL.

That does not, however, mean that there is not a difficult task ahead for the Fed to try to discern how fast the total money supply catches up with the economy so that they can reel back the money that they have put in.  But the problem with that idea is that because of the amount of economic activity that has been totally privatized, the Fed does not necessarily have the information to do that directly.

So ALL THINGS BEING EQUAL, they will have to try anyway by looking at the pick up in activity from the parts of the economy that they do have information about.

Meanwhile, folks like the NIF are looking to help to improve the information flow so that proper management of the money supply is possible from direct information.

Best Risk Management Quotes

January 12, 2010

The Risk Management Quotes page of Riskviews has consistently been the most popular part of the site.  Since its inception, the page has received almost 2300 hits, more than twice the next most popular part of the site.

The quotes are sometimes actually about risk management, but more often they are statements or questions that risk managers should keep in mind.

They have been gathered from a wide range of sources, and most of the authors of the quotes were not talking about risk management, at least they were not intending to talk about risk management.

The list of quotes has recently hit its 100th posting (with something more than 100 quotes, since a number of the posts have multiple quotes.)  So on that auspicous occasion, here are my favotites:

  1. Human beings, who are almost unique in having the ability to learn from the experience of others, are also remarkable for their apparent disinclination to do so.  Douglas Adams
  2. “when the map and the territory don’t agree, always believe the territory” Gause and Weinberg – describing Swedish Army Training
  3. When you find yourself in a hole, stop digging.-Will Rogers
  4. “The major difference between a thing that might go wrong and a thing that cannot possibly go wrong is that when a thing that cannot possibly go wrong goes wrong it usually turns out to be impossible to get at or repair” Douglas Adams
  5. “A foreign policy aimed at the achievement of total security is the one thing I can think of that is entirely capable of bringing this country to a point where it will have no security at all.”– George F. Kennan, (1954)
  6. “THERE ARE IDIOTS. Look around.” Larry Summers
  7. the only virtue of being an aging risk manager is that you have a large collection of your own mistakes that you know not to repeat  Donald Van Deventer
  8. Philip K. Dick “Reality is that which, when you stop believing in it, doesn’t go away.”
  9. Everything that can be counted does not necessarily count; everything that counts cannot necessarily be counted.  Albert Einstein
  10. “Perhaps when a man has special knowledge and special powers like my own, it rather encourages him to seek a complex explanation when a simpler one is at hand.”  Sherlock Holmes (A. Conan Doyle)
  11. The fact that people are full of greed, fear, or folly is predictable. The sequence is not predictable. Warren Buffett
  12. “A good rule of thumb is to assume that “everything matters.” Richard Thaler
  13. “The technical explanation is that the market-sensitive risk models used by thousands of market participants work on the assumption that each user is the only person using them.”  Avinash Persaud
  14. There are more things in heaven and earth, Horatio,
    Than are dreamt of in your philosophy.
    W Shakespeare Hamlet, scene v
  15. When Models turn on, Brains turn off  Til Schuermann

You might have other favorites.  Please let us know about them.

The Future of Risk Management – Conference at NYU November 2009

November 14, 2009

Some good and not so good parts to this conference.  Hosted by Courant Institute of Mathematical Sciences, it was surprisingly non-quant.  In fact several of the speakers, obviously with no idea of what the other speakers were doing said that they were going to give some relief from the quant stuff.

Sad to say, the only suggestion that anyone had to do anything “different” was to do more stress testing.  Not exactly, or even slightly, a new idea.  So if this is the future of risk management, no one should expect any significant future contributions from the field.

There was much good discussion, but almost all of it was about the past of risk management, primarily the very recent past.

Here are some comments from the presenters:

  • Banks need regulator to require Stress tests so that they will be taken seriously.
  • Most banks did stress tests that were far from extreme risk scenarios, extreme risk scenarios would not have been given any credibility by bank management.
  • VAR calculations for illiquid securities are meaningless
  • Very large positions can be illiquid because of their size, even though the underlying security is traded in a liquid market.
  • Counterparty risk should be stress tested
  • Securities that are too illiquid to be exchange traded should have higher capital charges
  • Internal risk disclosure by traders should be a key to bonus treatment.  Losses that were disclosed and that are within tolerances should be treated one way and losses from risks that were not disclosed and/or that fall outside of tolerances should be treated much more harshly for bonus calculation purposes.
  • Banks did not accurately respond to the Spring 2009 stress tests
  • Banks did not accurately self assess their own risk management practices for the SSG report.  Usually gave themselves full credit for things that they had just started or were doing in a formalistic, non-committed manner.
  • Most banks are unable or unwilling to state a risk appetite and ADHERE to it.
  • Not all risks taken are disclosed to boards.
  • For the most part, losses of banks were < Economic Capital
  • Banks made no plans for what they would do to recapitalize after a large loss.  Assumed that fresh capital would be readily available if they thought of it at all.  Did not consider that in an extreme situation that results in the losses of magnitude similar to Economic Capital, that capital might not be available at all.
  • Prior to Basel reliance on VAR for capital requirements, banks had a multitude of methods and often used more than one to assess risks.  With the advent of Basel specifications of methodology, most banks stopped doing anything other than the required calculation.
  • Stress tests were usually at 1 or at most 2 standard deviation scenarios.
  • Risk appetites need to be adjusted as markets change and need to reflect the input of various stakeholders.
  • Risk management is seen as not needed in good times and gets some of the first budget cuts in tough times.
  • After doing Stress tests need to establish a matrix of actions that are things that will be DONE if this stress happens, things to sell, changes in capital, changes in business activities, etc.
  • Market consists of three types of risk takers, Innovators, Me Too Followers and Risk Avoiders.  Innovators find good businesses through real trial and error and make good gains from new businesses, Me Too follow innovators, getting less of gains because of slower, gradual adoption of innovations, and risk avoiders are usually into these businesses too late.  All experience losses eventually.  Innovators losses are a small fraction of gains, Me Too losses are a sizable fraction and Risk Avoiders often lose money.  Innovators have all left the banks.  Banks are just the Me Too and Avoiders.
  • T-Shirt – In my models, the markets work
  • Most of the reform suggestions will have the effect of eliminating alternatives, concentrating risk and risk oversight.  Would be much safer to diversify and allow multiple options.  Two exchanges are better than one, getting rid of all the largest banks will lead to lack of diversity of size.
  • Problem with compensation is that (a) pays for trades that have not closed as if they had closed and (b) pay for luck without adjustment for possibility of failure (risk).
  • Counter-cyclical capital rules will mean that banks will have much more capital going into the next crisis, so will be able to afford to lose much more.  Why is that good?
  • Systemic risk is when market reaches equilibrium at below full production capacity.  (Isn’t that a Depression – Funny how the words change)
  • Need to pay attention to who has cash when the crisis happens.  They are the potential white knights.
  • Correlations are caused by cross holdings of market participants – Hunts held cattle and silver in 1908’s causing correlations in those otherwise unrelated markets.  Such correlations are totally unpredictable in advance.
  • National Institute of Financa proposal for a new body to capture and analyze ALL financial market data to identify interconnectedness and future systemic risks.
  • If there is better information about systemic risk, then firms will manage their own systemic risk (Wanna Bet?)
  • Proposal to tax firms based on their contribution to gross systemic risk.
  • Stress testing should focus on changes to correlations
  • Treatment of the GSE Preferred stock holders was the actual start of the panic.  Leahman a week later was actually the second shoe to drop.
  • Banks need to include variability of Vol in their VAR models.  Models that allowed Vol to vary were faster to pick up on problems of the financial markets.  (So the stampede starts a few weeks earlier.)
  • Models turn on, Brains turn off.

Diversification Causes Correlations

November 3, 2009

The Bond insurers diversified out of their niche of municpal bonds into real estate backed securities and suddenly these two markets that previously seemed to have low correlation were highly correlated as the sub prime crisis brought down the Bond Insurers and their problems rippled into the Muni market.

(I say seemed uncorrelated, but of course they are highly dependent since a high fraction of municipal incomes comes from taxes relating to real estate values.  That is a major problem with the statistical idea of correlation – statistical approaches must never be used uncritically.)

But the point of the first paragraph above is that interdependencies do not have to come from the fundamentals of two markets – that is to come from common drivers of risk.  Interdependencies especially of market prices can and often do come from common ownership of securities from different markets.  The practice of holding risks from seemingly unrelated risks or markets is generally thought to create better risk adjusted results because of diversification.

But the perverse truth is that like many things in real economics (not book economics) the more people use this rule, the less likely it is that it will work.

There are several reasons for this:

  • When a particularly large organization diversifies, their positions in every market will be large.  For anyone to get the most benefit from diversification, they need to have positions in each diversifying risk that are similar in size.  Since even the largest firms had to have started somewhere, they will have a primary business that is very large and so will seek to take very large positions in the diversifying markets to get that diversifying benefit.  So there ends up being some very significant specific risk of a sudden change in correlation if that large firm runs into trouble.  These events only ever happen once to a firm so there is never, ever any historical correlations to be found.  But if you want to avoid this diversification pitfall, it pays to pay attention to where the largest firms operate and be cautious in assuming diversification benefits where THEY are the correlating factor.
  • When large numbers of firms use the same correlation factors (think Solvency II), then they will tend to all try to get into the same diversifying lines of business where they can get the best diversification benefits.  This results in both the specific risk factor mentioned above and to a pricing pressure on those markets.  Those risks with “good” diversification will tend to price down to their marginal cost, which will be net of the diversification benefit.  The customers will end up getting the advantage of diversification.
  • Diversification is commonly believed to eliminate risk.  THis is decidedly NOT TRUE.  No risk is destroyed via diversification.  All of the losses that were going to happen do happen, unaffected by diversification.  What diversification hopes to accomplish is to make this losses relatively less important and more affordable because some risk taking activity is likely to be showing gains while others is showing losses.  So people who thought that because they were diversified, that they had less risk, were willing to go out and take more risk.  This effect causes more of the stampede for the exits behaviors when times get tough and the losses that were NOT destroyed by diversification occur.
  • The theory of a free lunch with diversification encourages firms who are inexperienced with managing a risk to take on that risk because their diversification analysis says that it is “free”.  These firms will often help to drive down prices for everyon, sometimes to the point that they do not make money from their “diversification play” even in good years.  Guess what?  All that fancy correlation math does not work as advertised if the expected earnings from a “diversifying risk” is negative.  These is no diversification from a losing operation because it has no gains to offset the losses of other risks.

Coverage and Collateral

October 22, 2009

I thought that I must be just woefully old fashioned. 

In my mind the real reason for the financial crisis was that bankers lost sight of what it takes to operating a lending business. 

There are really only two simple factors that MUST be the first level of screen of borrowers:

1.  Coverage

2.  Collateral

And banks stopped looking at both.  No surprise that their loan books are going sour.  There is no theory on earth that will change those two fundamentals of lending. 

The amount of coverage, which means the amount of income available to make the loan payments, is the primary factor in creditworthiness.  Someone must have the ability to make the loan payments. 

The amount of collateral, which means the assets that the lender can take to offset any loan loss upon failure to repay, is a risk management technique that insulates the lender from “expected” losses. 

Thinking has changed over the last 10 – 15  years with the idea that there was no need for collateral, instead the lender could securitize the loan, atomize the risk, thereby spreading the specific risk to many, many parties, thereby making it inconsequential to each party.  Instead of collateral, the borrower would be charged for the cost of that securitization process. 

Funny thing about accounting.  If the lender does something very conservative (in terms of current standards) and requires collateral that would take up the first layer of loss then there will be no impact on P&L of this prudence. 

If the lender does not require collateral, then this charge that the borrower pays will be reported as profits!  The Banks has taken on more risk and therefore can show more profit! 

EXCEPT, in the year(s) when the losses hit! 

What this shows is that there is a HUGE problem with how accounting systems treat risks that have a frequency that is longer than the accounting period!  In all cases of such risks, the accounting system allows this up and down accounting.  Profits are recorded for all periods except when the loss actually hits.  This account treatment actually STRONGLY ENCOURAGES taking on risks with a longer frequency. 

What I mean by longer frequency risks, is risks that expect to show a loss, say once every 5 years.  These risks will all show profits in four years and a loss in the others.  Let’s say that the loss every 5 years is expected to be 10% of the loan, then the charge might be 3% per year in place of collateral.  So the banks collect the 3% and show results of 3%, 3%, 3%, 3%, (7%).  The bank pays out bonuses of about 50% of gains, so they pay 1.5%, 1.5%, 1.5%, 1.5%, 0.  The net result to the bank is 1.5%, 1.5%, 1.5%, 1.5%, (7%) for a cumulative result of (1%).  And that is when everything goes exactly as planned! 

Who is looking out for the shareholders here?  Clearly the deck is stacked very well in favor of the employees! 

What it took to make this look o.k. was an assumption of independence for the loans.  If the losses are atomized and spread around eliminating specific risk, then there would be a small amount of these losses every year, the negative net result that is shown above would NOT happen because every year, the losses would be netted against the gains and the cumulative result would be positive. 

Note however, that twice above it says that the SPECIFIC risk is eliminated.  That leaves the systematic risk.  And the systematic risk has exactly the characteristic shown by the example above.  Systematic risk is the underlying correlation of the loans in an adverse economy. 

So at the very least, collateral should be resurected and required to the tune of the systematic losses. 

Coverage… well that seems so obvious it doed not need discussion.  But if you need some, try this.

Black Swan Free World (5)

October 9, 2009

On April 7 2009, the Financial Times published an article written by Nassim Taleb called Ten Principles for a Black Swan Free World. Let’s look at them one at a time…

5. Counter-balance complexity with simplicity. Complexity from globalisation and highly networked economic life needs to be countered by simplicity in financial products. The complex economy is already a form of leverage: the leverage of efficiency. Such systems survive thanks to slack and redundancy; adding debt produces wild and dangerous gyrations and leaves no room for error. Capitalism cannot avoid fads and bubbles: equity bubbles (as in 2000) have proved to be mild; debt bubbles are vicious.

Complexity gets away from us very, very quickly.  And at the same time, we may spend so much time worrying about the complexity, building very complex models to deal with the complexity, that we lose sight of the basics.  So Complexity can hurt us both coming and going.

So why do we insist on Complexity?  That at least is simple.  Most complexity exists to provide differentiation between financial products that otherwise would be pure commodities.  The excuse is that the Complex products are needed to match up with the risks of a complex world.  Another, even less admirable reason for the complexity is to create something that sounds like a simple risk relief product but that costs the seller much less to provide, by carving out the parts of the risk relief that are more expensive but less desirable or less well understood by the customer.

Generally, customers who are buying risk relief products like insurance or hedges have a simple objective.  If they have a loss they want something that will make a payment that will offset the loss.  Complexity comes in when the risk relief products are customized to potentially better meet customer needs. (according to the sales literature).

Taleb suggests that complexity also hides leverage.  That is ver definitely the case.  For example, a CDS can be replicated by a long position in a credit and a short position in a treasury.  A short position in a treasury is finance speak for a loan at a better rate than you can actually get.  And a loan is leverage.  THe amount of the leverage is the full notional amount of the CDS.  Fans of derivatives will scoff at the idea that the notional amount if of any interest to anyone, but in this case at least, anyone who wants to know how much leverage the buyer of a CDS has, needs to add in the full notional amount of all of the CDS.

Debt bubbles are vicious because of the feedback loop in debt.  If one borrows money to purchase an asset and the asset increases in value, then you can use that increased value as collateral to increase the debt and purchase more of the asset.  The increase in demand for the asset causes prices to rise and so it goes.

But ultimately the reason that may economists have a hard time identifying bubbles (other than they do not believe that bubbles really ever exist) is that they do not know the capacity of any asset market to absorb additional investment.  Clearly in the example above, if there is a fixed amount of the asset that becomes subject to a debt bubble, it will very, very quickly run into a bubble situation.  But if the asset is a business or more likely a sector, it is not so easy to know exactly when the capacity of that sector to efficiently use additional capital is reached.

Black Swan Free World (10)

Black Swan Free World (9)

Black Swan Free World (8)

Black Swan Free World (7)

Black Swan Free World (6)

Black Swan Free World (5)

Black Swan Free World (4)

Black Swan Free World (3)

Black Swan Free World (2)

Black Swan Free World (1)

Unrisk – Part 3

October 6, 2009

From Jawwad Farid

Transition Matrix

Here is another way of looking at it. It is called a transition matrix. All it does is track how something rated/scored in a given class moves across classes over time

t1

How do you link to profitability?

t2

This is how profitability is calculated generally. Take the amount you have lent, multiply it by your expected adjusted return and voila, you have expected earnings. But that is not the true picture.

t3

What you are missing is the impact of two more elements. Your cost of funds (the money you have lent is actually not yours. You have borrowed it at a cost and that cost needs to be repaid) and your best and worst case provisions. So true profitability would look something like this.

t4

That is a pretty picture if I ever saw one. Especially when you compare the swing from the original projected number. Back to the question clients ask. Where do projected provisions come from? From transition matrices. And where do transition matrices come from. From applying your understanding of your distribution to your portfolio.

Remember these are not my ideas. They are hardly even original. The Goldman trader who first asked me about moment generating functions wanted to understand how well I understood the distributions that were going to rule my life on Fleet street?

Full credit for posing the distribution problem goes to our friend NNT (Nicholas Nassim Taleb) who first posed this as getting comfortable with the generating function problem. He wrote all of three books on the subject and then some. Rumor has it that he also made an obscene amount of money in the process (not with book writing, but with understanding the distribution). All he suggested was that before you took a punt, try and understand how much trouble could you possibly land in based on how what you are punting on is likely to behave in the future. Don’t just look at the past and the present, look the range, likely, unlikely, expected, unexpected.

UNRISK Part 1

UNRISK Part 2

How Many Dependencies did you Declare?

September 12, 2009

Correlation is a statement of historical fact.  The measurement of correlation does not necessarily give any indication of future tendencies unless there is a clear interdependency or lack thereof.  That is especially true when we seek to calculate losses at probability levels that are far outside the size of the historical data set.  (If you want to calculate a 1/200 loss and have 50 years of data, you have 25% of 1 observation)

Using historical correlations in the absence of understand the actual interdependencies could possibly result in drastic problems.

An example is the sub primes.  One of the key differences between what actually happened and the models used prior to the collapse of these markets is that historical correlations were used to drive the models for sub primes.  The correlations were between regions.  Historically, there had been low correlations between mortgage default rates in different regions of the US.  Unfortunately, those correlations were an artifact of regional unemployment driven defaults and unemployment is not the only factor that affects defaults.   The mortgage market had changed drastically from the period over which the defaults were measured.  Mortgage lending practices changed in most of the larger markets.  The prevalence of modified payment mortgages meant that the relationship between mortgages and income was changing as the payments shifted.  In addition, the amount of mortgage granted compared to income also shifted drastically.

So the long term low regional correlations were no longer applicable to the new mortgage market, because the market had changed.  The historical correlation was still a true fact, but is did not have much predictive power.

And it makes some sense to talk about interdependency rising in extreme events.  Just like in the subprime situation, there are drivers of risks that shift into new patterns because systems exceed their carrying capacity.

Everything that is dependent on confidence in the market may not correlate in most times, but that interdependency will show through when confidence is shaken.  In addition to confidence, financial market instruments may also be dependent on the level of liquidity in the markets.  Is confidence in the market a stochastic variable in the risk models?  It should be – it is one of the main drivers of levels of correlation of otherwise unrelated activities.

So before jumping to using correlations, we must seek to understand dependencies.

Multi dimensional Risk Management

August 28, 2009

Many ERM programs are one dimensional. They look at VaR or they look at Economic Capital. The Multi-dimensional Risk manager consider volatility, ruin, and everything in between. They consider not only types of risk that are readily quantifiable, but also those that may be extremely difficult to measure. The following is a partial listing of the risks that a multidimensional risk manager might examine:
o Type A Risk – Short-term volatility of cash flows in one year
o Type B Risk – Short-term tail risk of cash flows in one year
o Type C Risk – Uncertainty risk (also known as parameter risk)
o Type D Risk – Inexperience risk relative to full multiple market cycles
o Type E Risk – Correlation to a top 10
o Type F Risk – Market value volatility in one year
o Type G Risk – Execution risk regarding difficulty of controlling operational losses
o Type H Risk – Long-term volatility of cash flows over five or more years
o Type J Risk – Long-term tail risk of cash flows over 5 five years or more
o Type K Risk – Pricing risk (cycle risk)
o Type L Risk – Market liquidity risk
o Type M Risk – Instability risk regarding the degree that the risk parameters are stable

Many of these types of risk can be measured using a comprehensive risk model, but several are not necessarily directly measurable. But the muilti dimensional risk manager realizes that you can get hurt by a risk even if you cannot measure it.

VaR is not a Bad Risk Measure

August 24, 2009

VaR has taken a lot of heat in the current financial crisis. Some go so far as to blame the financial crisis on VaR.

But VaR is a good risk measure. The problem is with the word RISK. You see, VaR has a precise definition, RISK does not. There is no way that you could possible measure an ill defined idea as RISK with a precise measure.

VaR is a good measure of one aspect of RISK. Is measures volatility of value under the assumption that the future will be like the recent past. If everyone understands that is what VaR does, then there is no problem.

Unfortunately, some people thought that VaR measured RISK period. What I mean is that they were led to believe that VaR was the same as RISK. In that context VaR (and any other single metric) is a failure. VaR is not the same as RISK.

That is because RISK has many aspects. Here is one partial list of the aspects of risk:

Type A Risk – Short Term Volatility of cash flows in 1 year
Type B Risk – Short Term Tail Risk of cash flows in 1 year
Type C Risk – Uncertainty Risk (also known as parameter risk)
Type D Risk – Inexperience Risk relative to full multiple market cycles
Type E Risk – Correlation to a top 10
Type F Risk – Market value volatility in 1 year
Type G Risk – Execution Risk regarding difficulty of controlling operational losses
Type H Risk – Long Term Volatility of cash flows over 5 or more years
Type J Risk – Long Term Tail Risk of cash flows over 5 years or more
Type K Risk – Pricing Risk (cycle risk)
Type L Risk – Market Liquidity Risk
Type M Risk – Instability Risk regarding the degree that the risk parameters are stable
(excerpted from Risk & Light)

VaR measures Type F risk only.


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