Myths of Market Consistent Valuation

Guest Post from Elliot Varnell

Myth 1: An arbitrage free model will by itself give a market consistent valuation.

An arbitrage-free model which is calibrated to deep and liquid market data will give a market consistent valuation. An arbitrage-free model which ignores available deep and liquid market data does not give a market consistent valuation. Having said this there is not a tight definition of what constitutes deep and liquid market data, therefore there is no tight definition of what constitutes market consistent valuation. For example a very relevant question is whether calibrating to historic volatility can be considered market consistent if there is a marginally liquid market in options. CEIOPs CP39 published in July 2009 appears to leave open the questions of which volatility could be used, while CP41 requires that a market is deep and liquid, transparent and that these properties are permanent.

Myth 2: A model calibrated to deep and liquid market data will give a Market Consistent Valuation.

A model calibrated to deep and liquid market data will only give a market consistent valuation if the model is also arbitrage free. If a model ignores arbitrage free dynamics then it could still be calibrated to replicate certain prices. However this would not be a sensible framework marking to model the prices of other assets and liabilities as is required for the valuation of many participating life insurance contracts Having said this the implementation of some theoretically arbitrage free models are not always fully arbitrage free themselves, due to issues such as discretisation, although they can be designed to not be noticeably arbitrage free within the level of materiality of the overall technical provision calculation.

Myth 3: Market Consistent Valuation gives the right answer.

Market consistent valuation does not give the right answer, per se, but an answer conditional on the model and the calibration parameters. The valuation is only as good as these underlying assumptions. One thing we can be sure of is that the model will be wrong in some way. This is why understanding and documenting the weakness of an ESG model and its calibration is as important as the actual model design and calibration itself.

Myth 4: Market Consistent Valuation gives the amount that a 3^rd party will pay for the business.

Market Consistent Valuation (as calculated using an ESG) gives a value based on pricing at the margin. As with many financial economic models the model is designed to provide a price based on a small scale transaction, ignoring trading costs, and market illiquidity. The assumption is made that the marginal price of the liability can be applied to the entire balance sheet. Separate economic models are typically required to account for micro-market features; for example the illiquidity of markets or the trading and frictional costs inherent from following an (internal) dynamic hedge strategy. Micro-market features can be most significant in the most extreme market conditions; for example a 1-in-200 stress event.

Even allowing for the micro-market features a transaction price will account (most likely in much less quantitative manner than using an ESG) the hard to value assets (e.g. franchise value) or hard to value liabilities (e.g. contingent liabilities).

Myth 5: Market Consistent Valuation is no more accurate than Discounted Cash Flow techniques using long term subjective rates of return.

The previous myths could have suggested that market consistent valuation is in some way devalued or not useful. This is certainly the viewpoint of some actuaries especially in the light of the recent financial crisis. However it could be argued that market consistent valuation, if done properly, gives a more economically meaningful value than traditional DCF techniques and provides better disclosure than traditional DCF. It does this by breaking down the problem into clear assumptions about what economic theory is being applied and clear assumption regarding what assumptions are being made. By breaking down the models and assumptions weaknesses are more readily identified and economic theory can be applied.

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RISK USA Conference – October 2009

Many, many good questions and good ideas at the RISK USA conference in New York.  Here is a brief sampling:

• Risk managers are spending more time showing different constituencies that they really are managing risk.
• May want to change the name to “Enterprise Uncertainty Management”
• Two risk managers explained how their firms did withdraw from the mortgage market prior to the crisis and what sort of thinking by their top management supported that strategy
• Now is the moment for risk management – we are being asked for our opinion on a wide range of things – we need to have good answers
• Availability of risk management talent is an issue.  At both the operational level and the board level. 
• Risk managers need to move to doing more explaining after better automating the calculating
• Group think is one of the major barriers of good risk management
• Regulators tend to want to save too many firms.  Need to have a middle path that allows a different sort of resolution of a troubled firm than bankrupcy.
• Collateral will not be a sufficient solution to risks of derivatives.  Collateral covers only 30 – 50% of risk
• No one has ever come up with a theory for the level of capital for financial firms.  Basel II is based upon the idea of keeping capital at about the same level as Basel I. 
• Disclosure of Stress tests of major banks last Spring was a new level of transparency. 
• Banking is risky. 
• Systemic Risk Regulation is impossibly complicated and doomed to failure. 
• Systemic Risk Regulation can be done.  (Two different speakers)
• In Q2 2007, the Fed said that the sub-prime crisis is contained.  (let’s put them in charge)
• Having a very good system for communicating was key to surviving the crisis.  Risk committees met 3 times per day 7 days per week in fall 2008. 
• Should have worked out in advance what do do after environmental changes shifted exposures over limits
• One firm used ratings plus 8 additional metrics to model their credit risk
• Need to look through holdings in financial firms to their underlying risk exposures – one firm got red of all direct exposure to sub prime but retained a large exposure to banks with large sub prime exposure
• Active management of counterparties and information flow to decision makers of the interactions with counter parties provided early warning to problems
• Several speakers said that largest risk right now is regulatory changes
• One speaker said that the largest Black Swan was another major terrorist attack
• Next major systemic risk problem will be driven primarily by regulators/exchanges
• Some of structured markets will never come back (CDO squareds)
• Regret is needed to learn from mistakes
• No one from major firms actually went physically to the hottest real estate markets to get an on the ground sense of what was happening there – it would have made a big difference – Instead of relying solely on models. 

Discussions of these and other ideas from the conference will appear here in the near future.

Understanding and Balance

Everything needs to balance.  A requirement that management understand the model creates and equal and opposite obligation on the part of the modelers to really explain the assumptions that are embedded in the model and the characteristics that the model will exhibit over time.

This means that the modelers themselves have to actually understand the assumptions of the model – not just the mechanical assumptions that support the mechanical calculations of the model.  But the fundamental underlying assumptions about why the sort of model chosen is a reliable way to represent the world.

For example, one of the aspects of models that is often disturbing to senior management is the degree to which the models require recalibration.  That need for recalibration is an aspect of the fundamental nature of the model.  And I would be willing to guess that few modelers have in their explanation of their model fully described that aspect of their model and explained why it exists and why it is a necessary aspect of the model.

That is just an example.  We modelers need to understand all of these fundamental points where models are simply baffling to senior management users and work to overcome the gap between what is being explained and what needs to be explain.

We are focused on the process.  Getting the process right.  If we choose the right process and follow it correctly, then the result should be correct.

But the explanations that we need are about why the choice of the process made sense in the first place.  And more importantly, how, now that we have followed the process for so long that we barely remember why we chose it, do we NOW believe that the result is correct.

What is needed is a validation process that gets to the heart of the fundamental questions about the model that are not yet known!  Sound frustrating enough?

The process of using risk models appropriately is an intellectual journey.  There is a need to step past the long ingrained approach to projections and models that put models in the place of fortune tellers.  The next step is to begin to find value in a what-if exercise.  Then there is the giant leap of the stochastic scenario generator.  Many major conceptual and practical leaps are needed to move from (a) getting a result that is not reams and reams of complete nonsense to (b) getting a result that gives some insight into the shape of the future to (c) realizing that once you actually have the model right, it starts to work like all of the other models you have ever worked with with vast amount of confirmation of what you already know (now that you have been doing this for a couple of years) along with an occasional insight that was totally unavailable without the model.

But while you have been taking this journey of increasing insight, you cross over and become one of those who you previously thought to talk mostly in riddles and dense jargon.

But to be fully effective, you need to be able to explain all of this to someone who has not taken the journey.

The first step is to understand that in almost all cases they do not give a flip about your model and the journey you went throughto get it to work.

The next step is to realize that they are often grounded in an understanding of the business.  For each person in your management team, you need to understand which part of the business that they are grounded in and convince them that the model captures what they understand about the part of the business that they know.

Then you need to satisfy those whse grounding is in the financials.  For those folks, we usually do a process called static validation – show that if we set the assumptions of the model to the actual experience of last year, that the model actually reproduces last year’s financial results.

Then you can start to work on an understanding of the variability of the results.  Where on the probability spectrum was last year – both for each element and for the aggregate result.

That one is usually troublesome.  For 2008, it was particularly troublesome for any firms that owned any equities.  Most models would have placed 2008 stock market losses almost totally off the charts.

But in the end, it is better to have the discussion.  It will give the management users a healthy skepticism for the model and more of an appreciation for the uses and limitations of the entire modeling methodology.

These discussions should lead to understanding and balance.  Enough understanding that there is a balanced view of the model.  Not total reliance and not total skepticism.

Black Swan Free World (8)

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…

8. Do not give an addict more drugs if he has withdrawal pains. Using leverage to cure the problems of too much leverage is not homeopathy, it is denial. The debt crisis is not a temporary problem, it is a structural one. We need rehab.

George Soros has said that he believes that the GFC is the beginning of the unwinding of a fifty year credit buildup.  Clearly there was too much leverage.  But does anyone know what the right amount of leverage for a smoothly functioning capitalist system should be?

There is always a problem after a bubble.  Many people keep comparing things to how they were at the very height of the bubble.  Stock valuations are compared to the height of the market.  Employment is compared to the point where the most people had jobs.  But these are often not the right comparisons.  If in the month of May, for 30 days, I had an outstanding offer for my house of $300,000 and on one day a person flew in from far away and offered $3 million, and if I never made that sale, do I forever after compare the offering price for selling the house to $3 Million?

People talk about a “New Normal”.  Possibly, the new normal means nothing more than returning to the long term trend line.  Going back to where things would now be if everything had stayed rational.

That may seem sensible, but this new normal may be a very different economy than the overheated and overleveraged one that we had.

Taleb suggests that the only possible transition from excessive debt is cold turkey.  If Soros is right and we are going to transition to a new normal that is more like 50 years ago than 5 years ago, there that will be a long bout of DTs.

What we are seeing in the way of debt is the substitution of government debt for private debt.  While Taleb is probably too harsh, the Fed does need to be careful.   Careful not to go too far with the government debt.  The Fed should be acting like the football player who passes ahead of the teammate, not to where they are standing right now.  The amount of debt that they should be shooting for is a level that will make sense when the banks fully recover and again take up lending “like normal”.  That will keep enough money flowing in the economy to soften the slowdown to the economy from the contraction of bank lending.

However, if the Fed is shooting to put us back where we were at the peak, then we are in trouble and Taleb’s warning holds.  I would restate his warning as “Using too much leverage to combat the problem of too much leverage…” But using the right amount of leverage is just what is needed.

But that does mean learning to live with much less leverage.  It means that we need to better understand how much leverage is the right amount.  And we need to stop blaming the Chinese because they hold so much dollars and want to lend them to us.  We need to develop a structural solution to the global imbalance that the Chinese balances are a symptom of.

Like some of our other problems, the purely market based solutions will not work.  China is not playing by the market based rule book.  They are a mercantilist economy that is taking advantage of the global market economy systems.  We need to stop whining about that and develop strategies that work for everyone.

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)

Cultural Theory of Risk

Back in 1984 an anthropologist, Mary Douglas, wrote about her theory for why people chose to form and continue to associate with groups.  She postulated that the way that people thought about RISK was a primary driver.

Cultural Theory describes four views of RISK:

Individualists see the world as mean reverting.  Any risk that they take will be offset by later gains.

Egalitarians see the world in a delicate balance where any risky behaviors might throw off that balance and result in major problems.

Authoritarians see the world as dangerous by manageable.  Some risk can be taken but must be tightly controlled.

Fatalists see the world as unpredictable.  No telling what the result might be from risk taking.

The dynamics of human behavior are influenced by these four groups.  People shift between the four groups because they find the environment either validating their belief or failing to validate their belief.

Cultural Theory also see that there are broadly four different risk regimes in the world.  The four groups exist because the risk regime that validates their view of risk will exist some of the time.

These four regimes are:

Normal Risk – when the ups and downs of the world fall within the expected ranges.

Low Risk – when everything seems to be working out well for the risk takers and the dips are quickly followed by jumps.

High Risk – when the world is on the edge of disaster and hard choices must be made very carefully.

High Loss – when the risks have all turned to losses and survival does not seem certain.

There are huge implications of these ideas for risk managers.  Risk management, as currently practiced, is process that is designed by Authoritarians for the Normal Risk regime.  The Global Financial Crisis has shown that current risk management fails when faced with the other regimes.

One solution would be to redesign risk management to be a broader idea that can both use the skills of those other three views of risk, adapting to the other three regimes of risk.

This idea is discussed in more detail here and in a forthcoming series of articles in Wilmott Magazine.

Which ERM are you talking about?

If you ask managers, and if they give an honest answer, the large majority of them will say that they do not really know what Enterprise Risk Management really means.

One major reason for that confusion is that there really are three different and largely separable ideas of ERM that are being performed in organizations and discussed by experts.  Much confusion results because of these highly mixed messages.  The three types of ERM are:

Loss Controlling – practiced in most non-financial firms and also the traditional risk management of financial firms.  This type of ERM has the objective of minimizing losses.

Risk Trading – practiced in firms like banks and insurers who see their business as risk taking.  The ERM of risk trading focuses primarily on pricing of those risks.  Modern ERM grew up in banks out of the trading desks of banks.

Risk Steering – is an ideal that exists much more prevalently in books about ERM and in articles by consultants than in reality.  Risk steering concentrates on using risk and reward information for strategic decision making.

Some firms seek to do all three.  Most are looking to do just one of the three.  Writers on ERM usually do not clearly distinguish between the very different activities that are needed to support the three different types of ERM or they might exclude one of the three completely from their discussion.

So some of the confusion about ERM arises from this confusing discussion.  Most confusing to everyone else is the Bankers.  They are focused almost solely on risks that can be traded in a real time basis.  Their risk trading.  They are so in love with that idea, that people like Alan Greenspan have suggested that all risks would be better managed by turning them into traded risks.

Unfortunately, what we have seen is almost the opposite of that.  Many risks can only be managed by a Loss Controlling process and the way that banks have abandoned Loss Controlling in favor of Risk Trading has proven disastrous for all of us.

For a discussion of how this idea impacts on actuaries seeking to practice in ERM see this post.

Coverage and Collateral

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.

Whose Loss is it?

As we look at the financial system and contemplate what makes sense going forward, it should be important to think through what we plan to do with losses going forward.

There are at least seven possibilities.  As a matter of public policy, we should be discussing where the attachment should be for each layer of losses.  Basel 2 tries to set the attachment for the fourth layer from the bottom, without directly addressing the three layers below.

So for major loss scenarios, we should have a broad idea of how we expect the losses to be distributed.  Recent practices have focused on just a few of these layers, especially the counterparty layer.  The “skin in the game” idea suggests that the counterparties, when they are intermediaries, should have some portion of the losses. Other counterparties are the folks who are taking the risks via securitizations and hedging transactions.

However, we do not seem to be discussing a public policy about the degree to which the first layer, the borrowers, needs to absorb some of the losses.  In all cases, absorbing some of the losses means that that layer really needs to have the capacity to absorb those losses.  Assigning losses to a layer with no resources is not an useful game.  Having resources means having valuable collateral or dependable income that can be used to absorb the loss.  It could also mean having access to credit to pay the loss, though hopefully we have learned that access to credit today is not the same as access to credit when the loss comes due.

+    +    +   +

This picture might be a useful one for risk managers to use as well to clarify things about how losses will be borne that are being taken on by their firm.  The bottom layer does not have to be a borrower, it can also be an insured.

This might be a good way to talk about losses with a board.  Let them know for different frequency/severity pairs who pays what.  This discussion could be a good part of a discussion on Risk Appetite and Risk Limits as well as a discussion of the significance of each different layer to the risk management program of the firm.

The “skin in the game” applies at the corporate level as well.  If you are the reinsurer or another counterparty, you might want to look at this diagram for each of your customers to make sure that they each have enough “skin” where it counts.

The Glass Box Risk Model

I learned a new term today “The Glass Box Risk Model” from a post by Donald R. van Deventer,

Glass Boxes, Black Boxes, CDOs and Grocery Lists

You can read what he has to say about it.  I just wanted to pass along the term “Glass Box.”

A Glass Box Risk Model is one that is exactly the opposit of a Black Box.  With a Black Box Model, you have no idea what is going on inside.  WIth a Glass Box, you can see everything inside.

Something is needed, however, in addition to transparency, and that is clarity.  To use the physical metaphor further, the glass box could easily be crammed with so, so much complicated stuff that it is only transparent in name.  The complexity acts as a shroud that keeps real transparency from happening.

I would suggest that argues for separability of parts of the risk model.  The more different things that one tries to cram into a single model, the less likely that it is separable or truely transparent.

That probably argues against any of the elegance that modelers sometimes prize.  More code is probably preferable to less if that makes things easier to understand.

For example, I give away my age, but I stopped being a programmer about the time when actuaries took up APL.  But I heard from everyone who ever tried to assign maintenance of an APL program to someone other than the developer, that APL was a totally elegant but totally opaque programming language.

But I would suggest that the Glass Box should be the ideal for which we strive with our models.

Toward a New Theory of the Cost of Equity Capital

From David Merkel, Aleph Blog

I have never liked using MPT [Modern Portfolio Theory] for calculating the cost of equity capital for two reasons:

• Beta is not a stable parameter; also, it does not measure risk well.
• Company-specific risk is significant, and varies a great deal.  The effects on a company with a large amount of debt financing is significant.

What did they do in the old days?  They added a few percent on to where the company’s long debt traded, less for financially stable companies, more for those that took significant risks.  If less scientific, it was probably more accurate than MPT.  Science is often ill-applied to what may be an art.  Neoclassical economics is a beautiful shining edifice of mathematical complexity and practical uselessness.

I’ve also never been a fan of the Modigliani-Miller irrelevance theorems.  They are true in fair weather, but not in foul weather.  The costs of getting in financial stress are high, much less when a firm is teetering on the edge of insolvency.  The cost of financing assets goes up dramatically when a company needs financing in bad times.

But the fair weather use of the M-M theorems is still useful, in my opinion.  The cost of the combination of debt, equity and other instruments used to finance depends on the assets involved, and not the composition of the financing.  If one finances with equity only, the equityholders will demand less of a return, because the stock is less risky.  If there is a significant, but not prohibitively large slug of debt, the equity will be more risky, and will sell at a higher prospective return, or, a lower P/E or P/Free Cash Flow.

Securitization is another example of this.  I will use a securitization of commercial mortgages [CMBS], to serve as my example here.  There are often tranches rated AAA, AA+, AA, AA-, A+, A, A-, BBB+, BBB, BBB-, and junk-rated tranches, before ending with the residual tranche, which has the equity interest.

That is what the equity interest is – the party that gets the leftovers after all of the more senior capital interests get paid.  In many securitizations, that equity tranche is small, because the underlying assets are high quality.  The smaller the equity tranche, the greater percentage reward for success, and the greater possibility of a total wipeout if things go wrong.  That is the same calculus that lies behind highly levered corporations, and private equity.

All of this follows the contingent claims model that Merton posited regarding how debt should be priced, since the equityholders have the put option of giving the debtholders the firm if things go bad, but the equityholders have all of the upside if things go well.

So, using the M-M model, Merton’s model, and securitization, which are really all the same model, I can potentially develop estimates for where equities and debts should trade.  But for average investors, what does that mean?  How does that instruct us in how to value stock and bonds of the same company against each other?

There is a hierarchy of yields across the instruments that finance a corporation.  The driving rule should be that riskier instruments deserve higher yields.  Senior bonds trade with low yields, junior bonds at higher yields, and preferred stock at higher yields yet.  As for common stocks, they should trade at an earnings or FCF yield greater than that of the highest after-tax yield on debts and other instruments.

Thus, and application of contingent claims theory to the firm, much as Merton did it, should serve as a replacement for MPT in order to estimate the cost of capital for a firm, and for the equity itself.  Now, there are quantitative debt raters like Egan-Jones and the quantitative side of Moody’s – the part that bought KMV).  If they are not doing this already, this is another use for the model, to be able to consult with corporations over the cost of capital for a firm, and for the equity itself.  This can replace the use of beta in calculations of the cost of equity, and lead to a more sane measure of the weighted average cost of capital.

Values could then be used by private equity for a more accurate measurement of the cost of capital, and estimates of where a portfolio company could do and IPO.  The answer varies with the assets financed, and the degree of leverage already employed.  Beyond that, CFOs could use the data to see whether Wall Street was giving them fair financing options, and take advantage of finance when it is favorable.

Black Swan Free World (7)

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…

7. Only Ponzi schemes should depend on confidence. Governments should never need to “restore confidence”. Cascading rumours are a product of complex systems. Governments cannot stop the rumours. Simply, we need to be in a position to shrug off rumours, be robust in the face of them.

Hyman Minsky’s Financial Instability Hypothesis talks about the financial markets working in three regimes, Hedge, Speculative and Ponzi.   Under Hedge financing, investments generally have sufficient cashflow to pay both principle and interest.  Under Speculative financing, investments generally have cashflows sufficient to pay interest, but depend upon rolling over financing to continue.  Ponzi financing does not have sufficient cashflows to pay either interest or principle.  Ponzi financing requires that values will increase enough to pay both principle and interest to repay financing.

Speculative financing requires a belief that the value of the collateral will be stable to justify future refinancing or rolling over of the financing.  That belief could be called confidence.

Ponzi financing requires a belief that the value of collateral will grow faster than the interest rate charged.  That belief requires a significantly higher amount of confidence.

There are several other levels that a financial business could operate.  For example, the value of the collateral could be viewed in terms, not of its current value, but of its value in an adverse scenario.  A very conservative lender could then make sure that each investment used that adverse value as the actual amount of collateral granted.  In that situation, the investor does not want to rely upon the belief that the asset value will be stable.  A significantly more aggressive investor will want to make sure that their portfolio in total adjusts the value of collateral for the possible loss in an adverse situation, allowing for the effects of diversification in the portfolio.

Credit practices in the US have drifted against the path of having the borrower put up cash for that difference between adverse value and current value.  Instead, practice has changed so that the lender will hold capital against that adverse scenario and charge the borrowed the cost of holding that capital.

What has changed with that drift, is who will bare the losses in the adverse scenario.  That has shifted from the borrower to the lender.  So the loan transaction has changed from a simple credit transaction to a combined credit and asset value insurance transaction.  (Which makes me wonder if the geniuses who thought of this thought to charge appropriately for the insurance or if they just believed that if the market bought it when they securitized it, then the price must be right.)

This will look different from the former loan business where the borrowed bore the asset value risk because the lender will have fluctuations in their balance sheet when the adverse scenarios hit and the collateral value falls below the loan value.  And that is exactly what we are seeing right now.

In addition, as we are seeing now, when there is a extremely severe drop in the value of collateral, having the banks hold the risk of the decline in collateral value, then a drop in the collateral will have a significant impact on bank capital.  The impact on bank capital may have a major impact on the bank’s ability to lend which will impact on all of the rest of the economy that had no connection to the impaired asset class.

So to Taleb’s point about confidence,  it seems that he is stating that lending practices should revert to their prior level where collateral was valued under an adverse scenario.  Then there will be little if any confidence involved in the lending business.  And less chance that a steep drop in any one asset class will spill over to the rest of the economy.

So the dividing line would be that the financial firms that could be subject to future government bailouts would need to value collateral pessimistically and to avoid loans that are not fully collateralized.

Sounds SAFE.

But here is the problem with that proposal…

If any other firms, outside of that restriction are permitted to lend in the same markets, business will ultimately shift to those institutions.  They will be able to offer better loan terms and larger loans for the same collateral AND in most years, they will show much higher profits.

Bad risk management will drive out good.  The institutions that take the most optimistic view of risk, those who have the most confidence, will drive the firms with the more pessimistic view (whether that is their own view or the view imposed by the regulators) out of the market.

And then when the next crisis hits, regulators will find that the business has shifted to the non-regulated firms and they they will instead need to bail them out, unless they make it illegal for non-regulated firms to do any of the kinds of finance that is related to a government’s need to bailout.

Then the bank would almost always have real collateral and any drop in confidence could be resolved by assigning that collateral over to someone with cash and settling any needs for cash that the lack of confidence creates.

Taleb is not clear however whether he is referring to banks or the financial system in general or to the government with his statement.  The discussion above is about banks.

Trying to think about this idea in the context of the entire financial system, I wonder if he was suggesting a return to the gold standard.  When there was a gold standard, there was no need for confidence in the currency.  If you stay with the current currency regime, then the confidence idea, I suppose, relates to the question of inflating the currency.  If the government does seem to consistently hold the money supply at a reasonable level in proportion to the economy, then there will not be a problem.  However, I cannot think of any way of looking at the floating currency system that does not REQUIRE confidence that the government will hold inflation in check.

Applying the idea to the government, I would also say that confidence is required there as well.  A government that could be counted on to fund fully for spending programs would instill confidence, but there could be no surity, especially under the US system where the next congress could immediately trample on the good record of a all preceding governments.

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)

Gresham’s Law of Risk Management

Those who do not see a risk will drive those who see the risk out of the market.

Gresham’s law is of course “bad money will drive out good.” Its application to risk can be stated as the above and is well known to many market participants even though they might not have named it. Many business managers will blame their lack of success in a market to fools who are inappropriately undercutting their price and losing money doing so. For the most part, in most markets, participants are price takers, not price makers.
If someone comes into a market and wants to take a risk at half the going rate, then there is a new going rate. Market participants who do see the risk can take the new going price or withdraw.

From this you can infer that there is no benefit to better modeling of risk if it results in a significantly higher value for the risk.  Simple techniques should be used to broadly size a risk to see if your view of the risk puts you near the market or not.  Then if you are near to the market, you can spend the time and money to more carefully evaluate the risk.

It makes no sense to spend lots of time an money carefully evaluating a risk that you will not be seeing because someone who is more optimistic, or someone who does not see that risk at all will be writing all of that business.

Optimizing ERM & Economic Capital

The above was the title of a conference in London that I attended this week.  Here are some random take-aways:

• Sometimes it makes sense to think of risk indicators instead of risk limits.

• Should MVM reflect diversification?  But who’s diversification?

• Using a Risk and Control Self Assessment as the central pillar to an Operational Risk program

• Types of Operational Losses:  Financial, Reputation, Opportunity, Inefficiency

• Setting low thresholods for risk indicators/KRIs provides an early warning of the development of possible problems

• Is your risk profile stable?  Important question to consider.

• Number of employees correlates to size of operational risk losses.  May be a simple way to start thinking about how to assign different operational risk capital to different operations.  Next variable might be experience level of employees – might be total experience or task specific experience.  If a company goes into a completely new business, there are likely to be operational issues if they do not hire folks with experience from other firms.

• Instead of three color indicators, use four – Red, Orange(Amber), Yellow, Green.  Allows for elevating situations out of green without raising alarm.

• Should look at CP33

• Controls can encourage more risk taking.  (See John Adams work on seatbelts)

• Disclosures of safety margin in capital held might create market expectations that would make it impossible to actually use those margins as a buffer without market repercussions.

• Serious discussions about a number of ways that firms want to deviate from using pure market values.  Quite a shift from the discussions I heard 2 -3 years ago when strict adherence to market values was a cornerstone of good financial and risk management.  As Solvency 2 is getting closer to reality, firms are discovering some ways that the MTM regime would fundamentally change the insurance business.  People are starting to wonder how important it is to adhere to MTM for situations where liquidity needs are very low, for example.

All in all a very good conference.

Emerging Risk Scenario (1)

The British dominance of the world scene was largely seen to have ended with WWI.  However, that decline was not really an absolute decline in wealth, it was really mostly just a relative decline.  Other countries, especially the US rose in wealth faster than the UK.

That story begins to hint at the ELEPHANT in the room.  That elephant is the relative per capita wealth of the people in China, India, and the other emerging economies.

We have entered a period of equalization of personal wealth between the have-nots and the haves.  That will be a very disruptive process in the Have countries.  It may go gradually with small slow changes or it may go rapidly through a series of big jumps.

But what we will see will be a series of shocks like the dot com bubble and the current financial crisis.  At the end of each shock, the PPP per capita wealth of the rising economies will be the same as at the start or more likely higher and the PPP per capital wealth of the Have economies will be lower.

This will happen largely via shocks because there is extreme amounts of resistance to the process on the part of the Have economies.  This resistance took the form of excessive leverage in recent times.  People were unwilling to accept the fact that their PPP income was dropping, so that they borrowed to keep their lifestyle at the level that they felt that they are entitled to.

So discussions about deficits are really about how the US will handle the coming change in distribution of the wealth of the world.  If we simply choose to resist the change and try to bring things back to “normal” by government or personal deficit spending, then eventually we will have to pay through devaluation of our currency and if we persist, those funding our debt will cut us off.

It is hard to imagine our political process coming to the conclusion that we need to rethink our financial strategies in the light of the changing world financial order. That thinking has to come from outside the political process and eventually find its way in.

So the Emerging Risks scenario is for the long term decline of the income of the Have economies accomplished through a long series of financial system shocks accompanies by growing government deficits and declining credit quality for the government debt of the developed nations.  At the same time, the successful “emerging market” economies become the dominant economic players and their people gradually risk in PPP income to match up with the PPP income of the “developed” nations for people who still do the same or comparable work.  That income equalization will include some significant increase in overall wealth, but not enough to maintain the incomes of the developed countries during this process.

So if this is the emerging risk scenario. the questions are:

1.  How would your firm fare in this scenario if no specific advance planning or anticipation is done?

2.  Are there any things that your firm might do differently if you thought that this scenario was somewhat likely?

3.  Assuming that this scenario occurs, what is the cost benefit of those actions?  i.e. do they make sense in that scenario?

4.  Are there any ways to track secondary signs that this scenario might be coming to be?

From time to time, different Emerging Risk scenarios will be posted here and in the INARM LinkedIn Emerging Risks group for discussion.

Readers can post scenarios also – directly on LinkedIn or as a comment here (that I will “promote” to a posting.)

Global ERM Best Practices Webinar III

Date
December 1, 2009

Time

Times vary by location.  Program runs for 18 hours to allow for daytime viewing in all locations.

Location:
This webcast takes place via the Internet.  At your location.

Speakers from Europe, Americas and Asia-Pacific areas.

ERM is a unique field that is developing in all parts of the world at more or less the same time; therefore it is a new practice area where a global actuarial community of practitioners is developing. The webcast includes speakers from Europe and Asia/Pacific, as well as the Americas, and allows risk officers to share emerging risk management practices across different geographical regions.

The objective of this webcast is to provide the global actuarial community with new and emerging enterprise risk management (ERM) practices from different geographical regions. This webcast will include speakers from Asia/Pacific, Europe and the Americas offering insight into ERM best practices.

The webcast objectives

• Disseminating and promoting global ERM best practices to the actuarial community
• Offering accessible information about ERM to actuaries
• Facilitating the discussion of practical and theoretical ERM issue and possible solutions
• Promoting global standards of best practices in ERM

Who Should Attend

• Actuaries who are currently practicing in the ERM area within Insurers or consultancies and
• Actuaries and actuarial students who wish to get exposed to ERM practices so they can participate in ERM programs at insurers in the future
• Other nonactuarial risk officer

MORE INFORMATION

REGISTER HERE

Session Description in Comment to this post.

Speakers will be posted when available.

Black Swan Free World (6)

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…

6. Do not give children sticks of dynamite, even if they come with a warning . Complex derivatives need to be banned because nobody understands them and few are rational enough to know it. Citizens must be protected from themselves, from bankers selling them “hedging” products, and from gullible regulators who listen to economic theorists.

It is my opinion that many bubbles come about after a completely incorrect valuation model or approach becomes widely adopted.  Today, we have the advantage over observers from prior decades.  In this decade we have experienced two bubbles.  In the case of the internet bubble, the valuation model was attributing value to clicks or eyeballs.  It had drifted away from there being any connection between free cashflow and value.  As valuations soared, people who had internet investments had more to invest in the next sensation driving that part of the bubble. The internet stocks became more and more like Ponzi schemes.  In fact, Hyman Minsky described bubbles as Ponzi finance.

In the home real estate bubble, valuation again drifted away from traditional metrics, the archaic and boring loan to value and coverage ratio pair.  It was much more sophisticated and modern to use copulas and instead of evaluating the quality of the credit to use credit ratings of a structured securities of loans.

Goerge Soros has said that the current financial crisis might just be the final end of a fifty year mega credit bubble.  If he is right, then we will have quite a long slow ride out of the crisis.

There are two aspects of derivatives that I think were ignored in the run up to the crisis.  The first is the leverage aspect of derivatives.  A CDS is equivalent to a long position in a corporate bond and a short position in a risk free bond.  But few observers and even fewer principals considered CDS as containing additional leverage equal to the full notional amount of the bond covered.  And leverage magnifies risk.  Worse than that.

Leverage takes the cashflows and divides them between reliable cashflows and unreliably cashflows and sells the reliable cashflows to someone else so that more unreliable cashflows can be obtained.

The second misunderstood aspect of the derivatives is the amount of money that can be lost and the speed at which it can be lost.  This misunderstanding has caused many including most market participants to believe that posting collateral is a sufficient risk provision.  In fact, 999 days out of 1000 the collateral will be sufficient.  However, that other day, the collateral is only a small fraction of the money needed.  For the institutions that hold large derivative positions, there needs to be a large reserve against that odd really bad day.

So when you look at the two really big, really bad things about derivatives that were ignored by the users, Taleb’s description of children with dynamite seems apt.

But how should we be dealing with the dynamite?  Taleb suggests keeping the public away from derivatives.  I am not sure I understand how or where the public was exposed directly to derivatives, even in the current crisis.

Indirectly the exposure was through the banks.  And I strongly believe that we should be making drastic changes in what different banks are allowed to do and what different capital must be held against derivatives.  The capital should reflect the real leverage as well as the real risk.  The myth that has been built up that the notional amount of a derivative is not an important statistic and that the market value and movements in market value is the dangerous story that must be eliminated.  Derivatives that can be replicated by very large positions in securities must carry the exact same capital as the direct security holdings.  Risks that can change overnight to large losses must carry reserves against those losses that are a function of the loss potential, not just a function of benign changes in market values and collateral.

In insurance regulatory accounting, there is a concept called a non-admitted asset.  That is something that accountants might call an asset but that is not permitted to be counted by the regulators.  Dealings that banks have with unregulated financial operations should be considered non-admitted assets.  Transferring something off to the books to an unregulated entity just will not count.

So i would make it extremely expensive for banks to get anywhere near the dynamite.  Or to deal with anyone who has any dynamite.

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)

What is RISK?

I have started to get bothered by the way that the word RISK is used to mean almost anything – noun verb adjective.

It makes it almost impossible to understand what someone is trying to say about a risk or risk management topic.  I am probably even more guilty than most.  I was once told by an editor that I used the word over 100 times in an article.

One way that people misuse the word is in place of the word loss.  For the most part, people are interested in minimizing losses, not risks.  For some reason, risk seems to be a more professional word to use than loss.  But we should be honest with ourselves and be clear about when we really mean losses.  Looking forward, something can be a risk.  Looking backwards, something can no longer be a risk, it is a loss or not a loss.

In addition, many folks want to define risk to have both upside and downside.

I think that they are  being sloppy with words.

I think that they may trying to say that the concerns of risk managers are related to both the upside and downside.

Or they are trying to say that the upside part of Risk is the risk of foregone opportunities?  That at least makes a little sense to me.

But if you really mean upside and downside, then that definition of Risk seems to me to be Orwellian.  Like defining “hot” to include the temperature of ice. And your heating system to include your air conditioner.

It also seems that if you follow that line of reasoning to its logical conclusion, the only possible candidate for the CRO job is the CEO.

It seems that risk management is unhappy with only dealing with preventing bad things (losses) – it is so hard to get headlines if you are a defensive player on a sports team.  The things that do not happen do not lead to bonuses.

But making sure that bad things do not happen (with greater frequency or severity than the risk appetite) IS the job of the risk manager.

So I would define risk as “exposure to the potential for a future uncertain adverse event”.

This definition does not follow Knight, who separates Risk and Uncertainty.  Knight divides the two terms based upon the degree to which we know the distribution of outcomes.  I combine them because I do not believe that there is a set of future events with known distributions and another set with unknown distributions (putting aside dice).  I believe that there is a continuum of degrees to which we suspect that we know distributions of outcomes of future events.

So with this definition, I would suggest that there is no risk in an unknown future event where there are only positive outcomes possible.

I say this because there is more than enough to worry about on the downside regarding the management of potential losses.

Risk Limits always mean a limit in the amount of potential losses.  I have never heard of any organization anywhere ever that has put a limit on favorable deviations.

A Model Defense

From Chris Mandel

Risk modeling is the key to successful risk management. Not quite. Not even close. It has been headline news for most of this year, though. “Risk models got it wrong,” the headlines said. Billions were written off or lost. Chief Risk Officers were fired and some scape-goated.

By quick, yet unfounded extension, enterprise risk management has failed, just like so many pundits predicted.

Wrong again. Like every other component of risk frameworks, no one part is key to the whole. In fact, each part is important to a successful approach to understanding and successfully managing risk.

But what about risk modeling? No one model can be expected to give just the “right” answer.

More often, multiple and varied data points are more useful to an effective analysis. Think traditional actuarial work in casualty insurance. Most good actuaries use multiple methods or models to get to their range of predicted values.

So it is in modeling all kinds of risks. More than one model gets you to a better answer most of the time. But a better analysis doesn’t stop there. Supplemental approaches can often add a lot. One such approach is the use of expert opinion.

Continued in Risk & Insurance

What to get a Risk Manager for Christmas

From the Riskczar

This Christmas season, when you don’t know what to get the one you love because they already have a Nintendo Wii, iPod Touch or Beatles Rock Band, why not give them the gift of voluntary risk management guidelines, the ISO 31000 Risk Management – Principles and Guidelines.

Imagine the joy Christmas morning when your loved one unwraps the guidelines (even though it is branded ISO it is not a certifiable standard) and looks at the table of contents, unsure which chapter to read first: 1) Scope; 2) Terms and definitions; 3) Principles; 4) Framework; and 5) Process. Oh, I would go straight to the Process chapter myself.

And ISO 31000 does not require batteries or recharging either. It will not break and does not contain any small, dangerous parts or toxic paints. It is way friendlier than COSO ERM (well so is a pit bull actually) and unlike other fun toys you might get his season, ISO 31000 will harmonize principles, framework and processes. Oh Joy!

For more information, check out this article at Strategic Risk

Risks, Not Risk

From David Merkel in Aleph Blog

There is no generic risk.  There are many risks.  Are you getting fair compensation for the risks that you are taking?  If not, invest in other risks, or if there are few risks worth taking, invest in cash, TIPS, or foreign fixed income.

To this end, it is better to think in terms of risk factors rather than some generic formulation of risk.  Ask yourself, am I getting paid to bear this risk?  Look to the risks that offer the best compensation, and avoid those that offer little or negative compensation.

Modern Portfolio Theory has done everyone a gross disservice.  It is not as if we can predict the future, but the use of historical values for average returns, standard deviations, and correlations lead us astray.  These figures are not stable in the intermediate term.  The past is not prologue, and unlike what Sallie Krawcheck said in Barron’s, asset allocation is not a free lunch.  With so many people following strategic asset allocation, assets have separated into two groups, safe and risky.

Any risk reward strategy that is developed by looking backward at historical performance will no longer work well when everyone knows and uses it.  See the Law of Risk and Light Riskviews

Black Swan Free World (5)

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)

An Al-Chet for Risk Managers:

From James McCallum

I was not strong enough to stand up to my boss

I put selfish gain ahead of ethical considerations

I falsified or hid data to conceal results

I failed to be objective

My risk model was too subjective

I ignored warning signs

I was in over my head

I did not understand all the risk factors

I failed to get an outside opinion

I was beholden to monetary gain

I was victim to group think

I placed institutional interest before ethical considerations

I failed to admit I was wrong

I was not honest with regulators

I was not honest with shareholders

I looked the other way

I failed to act

I conveniently overlooked infractions

I turned a blind eye to irregularities

I made exemptions

I did not understand the depth of the problem

I know there are many more.

Please help me to uncover, understand, make right and overcome.

Shalom

From

Audit, Risk & Controls Community Blog

ERM Role in Implementing a Winning Acquisition Strategy (2)

From Mike Cohen

Part 2

(Part 1)

Execution of an Acquisition Strategy Goes Through Several Stages and Involves Many and Varied Complex, Interrelated Business Issues (they must be performed well, and there are numerous junctures where things can go awry … suggesting that many potential risks need to be addressed, and more effectively than they typically are)

– Defining the business case

– Considering the corporate strategy and the resulting (ideally enhanced) business model

* Fit vs. conflict

* Synergies; potential synergies are frequently overstated

* Diversification

– Assessing market opportunities and competitive dynamics

* Products

* Distribution

* Markets/segments

* Brand/reputation

– Financial impact

* Earnings

* Capital

* Economic value

* Assessment of an appropriate price

– Investments

* Asset classes

* Loss positions

* Liquidity

– Operational fit (or problematically, the need to ‘fix’ the target’s operations)

* Technology

* Administration

* Core competencies

– Integrating the target: melding the two organizations so that they can perform effectively together, while mitigating risk, volatility and confusion to the greatest extent possible

Q: Is an acquisition strategy a core competency of your company … can you execute such a transaction successfully?

Due Diligence Performed on any Acquisition Target: A Critical Activity on the Strategic and Tactical Levels

– Valuation, impact on future financial results

– Management/staff

– Profitability of new (potential), existing business

– Competitive market position; product management, distribution capabilities

– Synergies: strategic, operational, financial, market/product/distribution

– Investments

– Expense structure (opportunities for increasing efficiency and/or cost reduction)

– Technological capabilities or possible lack of fit

– Contractual obligations

– Areas of risk or uncertainty

Many acquisitions are viewed retrospectively as failures. A lack of accurate evaluation of/objectivity about prospective acquisition targets (using ‘rose-colored glasses’ leads many (most?) acquirers to have unrealizable goals for their transactions, and as a consequence the end results (strategic, financial or otherwise) do not meet expectations.  There is a considerable level of risk to the acquirer if the due diligence process is not conducted with sufficient accuracy and objectivity.

Evaluating the Capabilities of an Organization to Execute Successful Acquirer: Being a successful acquirer requires a number of skills and mind-sets:

– Knowing one’s own corporate vision, mission, strategy and operating model, and how  acquisitions complement them

– Having a disciplined approach: evaluating fit, paying an appropriate price based on economic value, both current and future

– Performing careful, accurate and objective due diligence on the target company and management counterparts … caveat emptor!

– Executing timely, well planned and orchestrated integration activities focus on achieving a favorable operational model and attaining a satisfactory level of cost savings; a number of  companies that acquired positive reputations as acquirers were in fact poor at integrating their acquisition(s), causing their organizations to implode

– Managing the staffs and corporate cultures sensitively. There is considerable amount of research that identifies human resource related issues as the most prevalent causes for acquisition failure; personalities (egos), conflicting management styles and cultures, and different compensation structures are all too common. Proactive conflict resolution is critical to steer the resulting entity past these pratfalls. Open and continuous communication is critical.

The General Lack of Success from Acquisitions is Attributed to Mismanaging One or More Critical Aspects of the Transaction with Material Risk

Strategy

– Incompatible cultures

– Incompatible business models

– Synergy non-existent or overestimated

Due Diligence

– Acquirer overpaid

– Foreseeable problems overlooked

– Acquired firm too unhealthy

– Overlooking aspects of the target where excessive divestiture or liquidation might be required

Implementation

– Inability to manage target

– Inability to implement change

– Clash of management styles/egos

Conclusion

An acquisition is arguably the most difficult business endeavor a company can undertake. This report discussed a considerable number of elements involved in acquisition activity; they are all complex, and there are many junctures in the process where a number of these elements can go awry or reach adverse conclusions, either derailing transactions that could have otherwise been successful or ‘proving’ the efficacy of transactions that upon closer scrutiny could not have succeeded and should have been avoided.

Studies of acquisition activity across all industries (not just insurance) have consistently  found that approximately two-thirds of these transactions yielded unsatisfactory results. One could observe that this is not surprising, as there are so many steps along the way that can turn into insurmountable roadblocks. Considering the myriad of factors that must be performed well, it is clear than sound, pragmatic risk management throughout the process and beyond is critical in order for acquisition activity to succeed

Law of Risk & Light

Risk management is all about making conscious decisions about risk taking.  Fully recognizing the potential losses that could result from a risky undertaking.  But in many camps, risk management is being simplified and simplified to a point where it may well mislead CEOs and Boards about the potential effectiveness of an oversimplified risk management regime.

These simplified risk management regimes are often in violation of the Law.  The Law of Risk and Light…

Risks in the light shrink, Risks in the dark grow
Return for Risks in the light shrinks faster than risk
Return for Risks in the dark does not grow as fast as risk

What this means is that risks that are visible to the market (in the light) will be managed by the market. The degree of uncertainty around the risk will shrink. With decreased uncertainty, the risk premium will shrink. With broad comfort, demand will rise; with increased demand, risk premium will shrink further.

Risks in the dark are risks that are not visible or known to the market. If the market charges little or nothing for a risk, then those who are aware of the risk will bring more and more of that risk to market. And if the market continues to be unaware of a risk, then more and more extreme versions of the risk will be brought to market, the risk will grow.
As the risks grow and grow, that growth might be noticed faintly by the market as a shadow of a risk. Some market participants are canny enough to know that if someone really wants to do a transaction, then a higher price for that transaction is probably in order, even if they do not fully understand the underlying reasons.

This law is as fundamental to risk management as supply and demand is fundamental to micro economics.  Any risk management actions that are taken or planned without recognition of the risks that may be in the dark initially could end up to be as flawed as management without consideration of risk.

Risk & Light was the winner of the Practical Paper Award at the 2009 Enterprise Risk Management Symposium

Unrisk – Part 3

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

How do you link to profitability?

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.

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.

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

Visions of Risk

How do you see risk?

One of the most difficult issues for many risk managers is the fact that people do not all see risk the same way.  No matter how hard they try, they cannot get some people to take risk management seriously.  On the other hand some people are eager to eliminate all risk.  Why cannot people just see risk the way that Enterprise Risk Managers have learned to see it?

1.  Do you see risk as something that could lead to severe problems, but if treated properly using well developed risk management techniques, then it can be controlled?

2.  Do you see risk as something that we have almost too much of – if we take any more risk then we will suffer dire consequences?  We need to work to lessen the risk that we are taking at all costs.

3.  Do you think that risk comes and goes, but in the end it all works out?  That periods of risk and loss are always followed by periods of low risk and large gains, so that over the cycle, it all works out.

4.  Or do you think that risk is unpredictable, that it is almost impossible to tell whether risks will turn into losses, so it is best not to bother with risk management?

Those are four views of risk that you probably have seen in your life and work.  As a risk manager, you need to figure out how to work with all four views, because there is little likelihood that you will convert everyone over to your view of risk.

ERM Role in Implementing a Winning Acquisition Strategy

From Mike Cohen

Part 1 (of 2)

“Winning bids are made by winning bidders”
Author Unknown

“Is there such a dynamic as The Winners’ Curse?”
Richard H. Thaler

Is an acquisition strategy a positive endeavor for an insurance company? Is it a strategy necessary for the survival of some companies? In these difficult times, even for companies that have a track record of success in this arena, is an acquisition the answer? This report explores the various thought processes that companies go through when they consider an acquisition strategy, explores what activities need to take place in order for an acquisition to be seen as successful, and reflects on the role of enterprise risk management in improving the likelihood of success.

Success: According to Whom?

A property isn’t valued on the same terms by a buyer and a seller. Buyers and sellers are trying to accomplish different things relative to their particular situations:                                                                   – The buyer is trying to enhance his business (ideally strategically, not just financially … although improving one’s financial position at this point time looks very appealing!); on what criteria will the buyer’s acquisition be viewed a success?                                                                                                        – The seller is trying to either raise capital or increase focus; on what terms will the seller’s divestiture be viewed a success?

What can buyers and sellers do to increase their respective chances of success? What role can/should ERM play in these transactions?

Acquisitions as an Element of Corporate Strategy: Various Perspectives

What is the mind–set companies have as they consider acquisition activity?

“We see the opportunity to make suitable acquisitions at the right price as just another way of meeting our corporate objectives”

“We see acquisitions as crucial to achieving our objectives”

“We are an acquisition specialist”

“Our strategy is to make acquisitions and then integrate them effectively”

Which is of these approaches is right for you, if any … and, if so, under what circumstances? Given that acquisition activity in the aggregate has an uneven track record of success, how can acquirers improve their likelihood of success? Have the myriad of risks involved in such complicate endeavors not been understood and dealt with effectively, causing the majority of acquisitions to fall short of expectations?

Companies’ conversations with rating agencies have often revealed ‘curious’ expectations of acquisition activity:

“The deal is ‘fully priced,’ but we did not overpay”

“The deal will work because there is overlap”

“The deal will work because there is no overlap”

“Cultures are similar despite apparent differences”

“Although not accretive, it’s non-dilutive”

“Growth & profit objectives will be met through synergies”

Enhancing an Organization’s Business Model, in General and via Acquisition, to Better Meet Goals and Objectives

Can an Acquisition Be a Driver of Positive Change?

Existing business model   Clear business case for an acquisition  Enhanced business model

A well respected expert on business strategy and planning, Russell L. Ackoff, presented the concept of ‘idealized design” …  the best conceived business model a company can put into place. Does an acquisition help a company make its business model more effective? For this to happen, it must be supportive of the following:

– Mission, Vision: Is the acquisition consistent with the company’s strategic direction?
– Profitability: EPS, ROE, EVA; is the acquisition accretive to financial results, and if not when will it be? Are there dynamics/risks that could prevent attainment of the stated financial objectives?
– Competitive dynamics: Will additional market share provide the ability to dictate competitive terms? Given how fragmented the life insurance industry is, can the largest companies (as large as they are) alter competitive dynamics more in their favor? Does the acquisition enable the company to compete more strongly against powerful competitors?
– Market share: Are economics of scale gained? Is less desirable (unfavorably priced) business being acquired? As said, since most insurance business segments are so fragmented, even after decades of consolidation activity, does market share even matter?
– Is a company’s business profile materially enhanced?
– Is favorable diversification gained? Is focus lost?

Does an Acquisition Make a Company a More Successful Competitor?

– Expanding distribution
– Expanding geographic coverage
– Achieving business growth, scale
– Acquiring/enhancing functional capabilities
– Increasing profits and capital

To be continued …

Black Swan Free World (4)

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…

4. Do not let someone making an “incentive” bonus manage a nuclear plant – or your financial risks. Odds are he would cut every corner on safety to show “profits” while claiming to be “conservative”. Bonuses do not accommodate the hidden risks of blow-ups. It is the asymmetry of the bonus system that got us here. No incentives without disincentives: capitalism is about rewards and punishments, not just rewards.

For many years, money managers were paid out of the revenue from a small management fee charged on assets.  The good performing funds attracted more funds and therefore had more gross revenue.  Retail mutual funds usually charged a flat rate.  Institutional funds charged a sliding scale that went down as a percentage of assets as the amount of assets went up.  Since mutual fund expenses were relatively flat, that meant that the larger funds could generate quite substantial profits.

Then hedge funds came along fifty years ago and established the pattern of incentive compensation of 20% of profits fairly early.  In addition, the idea of the fund using leverage was an early innovation of hedge funds.

Another innovation was the custom that the hedge fund manager’s gains would stay in the fund so that the incentives were aligned.  But think about how that works.  The investor puts up $1 million.  The fund gains 20%, the manager gets $400k and the investor gets $160k.  Then the fund drops 50%, the investor’s account is now worth $580k – he is down $420k.  The manager is down to $80k, but still up by that $80k.  The investor is creamed but the manager is well ahead.  Seems like that incentives need realignment.

Taleb may be thinking of a major issue with hedge funds – valuation of illiquid investments.  Hedge funds often make purchases of totally illiquid investments.  Each quarter, the manager makes an estimate of what they are worth.  The manager gets paid based upon those estimates.  However, with the recent downturn, even in funds that have not shown significant losses have had significant redemptions.  When these funds have redemptions, the liquid assets are sold to pay off the departing investors.  Their shares are determined using the estimated values of the illiquid assets and the remaining fund becomes more and more concentrated in illiquid assets.

If the fund manager had been optimistic about the value of the illiquid assets or simply did not anticipate the shift in demand that has ocurred with the financial crisis, there may well be a major problem brewing for the last investors out the door.  The double whammy of depressed prices for the illiquid assets as well as the distribution based upon values for those assets that are now known to be optimistic.

And over payment of the one sided performance bonuses to the manager were supported by the optimistic valuations.

Black Swan Free World (3)

Black Swan Free World (2)

Black Swan Free World (1)

The Yin and Yang of Risk

Guest Post By Chris Mandel

One thing I’ve discovered in the last year is that extremes seem to be the rule of thumb these days.

The obvious example is that which represents the more significant aspects of the current financial crisis; huge amounts of mortgage defaults; unfathomable aggregations of loss in credit default swaps; inordinate quantums of market confidence destruction and the resulting 50 percent portfolio reductions in the wake, etc, etc.

In recent years it has been reflected in the more traditional insurable risk realm with record-setting natural catastrophe seasons and increasingly severe terrorism events. The fundamental insurance concept of pooling and sharing risk for profitable diversification is threatened. Even the expected level of loss is growing increasingly unexpected in actual results.

Examining the risk discipline and its evolving practice, I see management by extremes beginning to subsume the norm. So here are some examples of how this looks.

Reams of Data–Little Data Intelligence: We have tons of “risk” related data but limited ability to interpret it and use it in order to head off losses that were ostensibly preventable or at least reducible.

Continued at Risk and Insurance

Need to Shift the Defense . . . and the ERM

Sports analogies are so easy.

ERM is like the defense in football.  You would no more think of fielding a football team without a defensive squad then you would think of running a financial firm without ERM.  On the football field, if a team went out without any defensive players, they would doubtless be scored upon over and over again.

A financial firm without an ERM program would experience losses that were higher than what they wanted.

The ERM program can learn something from the football defenders.  The defenders, even when they do show up,  cannot get by doing the exact same thing over and over again.  The offensive of the other team would quickly figure out that they were entirely predictable and take them apart.  The defenders need to shift and compensate for the changes in the environment and in the play of the other team.

Banks with compliance oriented static ERM programs found this out in the financial crisis.  Their ERM program consisted of the required calculation of VaR using the required methods.  If you look at what happened in the crisis, many banks did not show any increase in VaR almost right up until the markets froze.  That is because the clever people at the origination end of the banks knew exactly how the ERM folks were going to calculate the VaR and they waltzed their fancy new CDO products right around the static defense of the ERM crew at the bank.

They knew that the ERM squad would not look into the quality of the underlying credit that went into the CDOs as long as those CDOs had the AAA stamp of approval from the rating agencies.  The ERM models worked very well off of the ratings and the banks had drastically cut back on their staff of credit analysts anyway.

They also knew that the spot on the gain and loss curve where the VaR would be calculated was fixed in advance.  As long as their new creation passed the VaR test at that one point, nobody was going to look any further.

So what would the football coach do if their defense kept doing the same thing over and over while the other team ran around them all game?  Would the coach decide to play the next season without a defense?  Or would he retrain and restaff his defense with new players who would move around and adapt and shift to different strategies as the game went along.

And that is what ERM needs to do.  ERM needs to make sure that it does not get stuck in a rut.  Because any predictable rut will not work for long.  The marketplace and perhaps some within their own companies will  find a way around them and defeat their purpose.