One of the problems in trying to stay topical with this BLOG is that often interesting articles get "lost" because I try to deal with events as they break. Moreover, there is only so much that I can give you to read in a day.
Here is a case in point and a break from the Tunnel, border, arena etc.
This is a fascinating article in the Globe and Mail about business models going bad since they have no relationship to reality and the role of "grey hair."
I experienced something similar when I worked in the oil industry and the Bureaucrats under the Government of Prime Minister Pierre Trudeau enacted the National Energy Program. That program which was anti-foreign oil companies just about destroyed the Canadian oil industry and a bank or two at the time. That result obviously was totally unexpected and not contemplated by the geniuses who drafted the program.
My own view is that the Government bureaucracies are doing the same thing today with the border as I have related. What looks good on paper bears no relationship to the real world. Look at how Bill C-3 can hurt Windsor as an example. Brian Masse should take the full blame for that if he also demands credit for its passing!
I experienced something similar when I worked in the oil industry and the Bureaucrats under the Government of Prime Minister Pierre Trudeau enacted the National Energy Program. That program which was anti-foreign oil companies just about destroyed the Canadian oil industry and a bank or two at the time. That result obviously was totally unexpected and not contemplated by the geniuses who drafted the program.
My own view is that the Government bureaucracies are doing the same thing today with the border as I have related. What looks good on paper bears no relationship to the real world. Look at how Bill C-3 can hurt Windsor as an example. Brian Masse should take the full blame for that if he also demands credit for its passing!
All that will happen is economic devastation since these people have no real world experience. The mess at the Blue Water Bridge plaza is just one example of what I mean. Same thing with Eddie's multi-million Horseshoe Road and now the billion dollar plus Greenlink extravaganza. What the Bridge Co. spends a few million on and makes work, Governments would spend billions and see fail!
Here is part of the Globe story. As well here is one involving Borealis that scared me since as taxpayers, dear reader, you and I have to pay for their mistakes through increased pension plan contributions. We have gone through that once already after huge write-downs there that impacted just about every municipality in Ontario. The story is about their network but I note their reliance on models as well. I hope that their systems are a lot better now and that there is more grey hair in their shop too.
- Miscalculating the risks
Statistical geniuses of finance at the banks and hedge funds got it wrong. They were lulled into a false sense of security by their spreadsheets and risk models. Meanwhile, the old-fashioned wisdom of contrarians like Prem Watsa saw trouble. And profited.
BOYD ERMAN AND DEREK DECLOET
...Fairfax this week disclosed an annual profit of $1.1-billion (U.S.) for 2007, nearly four times what the insurance and investment company had earned in its best year the year before. Much of that was the result of a single, contrarian bet the firm made that the world had got it wrong about risk.
Starting in 2003, and continuing through early 2007, Fairfax began to buy credit default swaps on U.S. companies. The buyer of such a derivative is essentially betting that the company's debt is overpriced – that the market has underestimated the odds of a financial failure.
Some of Fairfax's swaps were against the debt of so-called monoline insurers, companies like MBIA Inc. and Ambac Financial Group Inc., that guaranteed U.S. municipal bonds but had massive exposure to subprime mortgages and other risky debt.
“All you had to do was take a prospectus or you take their 10-K and you open it up and you say, ‘Let me look at the risk factors,'” Mr. Watsa said. “It's all there. And what's amazing is that when you read it, you can't believe that these guys did what they did.
“They never worried about risk.”
Neither did a lot of other people, until the credit crunch exposed tens of billions in toxic consumer debt, high-risk business loans, and complex, structured investment products. Some have called the U.S. mortgage crisis the biggest risk-management failure in financial history. Soothed by triple-A credit ratings, a strong economy and intricate risk-management plans, financial institutions and investors took on far more risk, and paid a much higher price, than they realized at the time.
The cause of their complacency, Mr. Watsa said, was the low volatility that prevailed between 2003 and 2006. “The only way that that could happen is we have to have a long period of stability – a long period where there wasn't any accidents. You'd never take that risk otherwise.”
It also happened because too many banks, insurers, hedge funds and rating agencies were given a false sense of security by statistical models that told them the probability of a financial “accident” was low. Where they used spreadsheets and algebra, aging investors like Mr. Watsa, 57, relied on their instincts and decades of experience to tell them something was amiss. And the grey-hairs won.
“We were shocked at how low the risk premiums went,” Mr. Watsa said...
Until last summer, as the economy and credit markets boomed, investors were clamouring for risk, taking on more and more for less in return. Optimism ruled.
The most tangible result was that market interest rates dove to record lows relative to government bonds, with even risky products such as junk bonds earning investors a scant premium to “risk-free” debt such as Treasury bills.
Fairfax won its bet when that trend reversed, starting last summer, as investors spooked by U.S. mortgage defaults once again demanded more compensation for taking chances...
Many of the answers lie in the uncertain science of risk management, which banks depend on to avoid pitfalls.
As markets flourished, financial institutions poured vast intellectual and electronic resources into creating fancy new products such as collateralized debt obligations (CDOs). At the same time, in a parallel universe also populated by PhDs and supercomputers, risk managers used statistical models in hopes of simulating what sudden market moves would do to the value of those securities and derivatives.
In all financial institutions, there is a daily battle between the risk takers and the risk managers. The takers push for bigger positions to make bigger profits, while the managers push for prudence and caution.
But as their warnings of potential loss were proved false each day by the soaring financial markets, many risk managers lost the ear of management teams focused on the vast profits generated by the people in the business of creating the structures. That led banks to take bigger and bigger bets.
“In a lot of these organizations that have had difficulties, the chief risk officer's role wasn't that meaningful or the business lines had more power and authority than the risk function did,” said Brian Porter, 50, chief risk officer at Bank of Nova Scotia, which has largely avoided the financial mess.
But some of the fault also lies with risk managers who relied too much on their tools, the statistical models, which were rapidly eclipsed by the rapid innovation in financial markets that begat complicated structures such as CDOs, so-called CDO squareds and structured investment vehicles (SIVs).
“Risk management tools are blunt instruments, which calls for prudence,” said Louis Gagnon, a former Royal Bank of Canada risk-management executive who now teaches business at Queen's University. “If you know you are driving your car on a foggy evening, you are supposed to go easy on the gas, but it's not necessarily what happens.”
Banks reeling from the massive losses are coming to realize that two of their key tenets of risk management – diversification and dependence on the so-called “normal distribution of events” – have been weighed in the balance of the credit crisis and found wanting.
Diversification has proved illusory because of a greater degree of correlation between asset classes and world markets than almost anybody expected.
The concept of avoiding correlation through diversification stems from the world of insurance. If you're going to insure homes, you have a greater chance of a big loss if all the houses you protect are on one street, or even in one town. There's too much risk of correlation, because a single hurricane or big fire could wipe them all out. One answer is to seek wider geographic diversification to cut correlation. Another is to insure in different markets, perhaps adding life or auto coverage to reduce the chance that all your customers will make claims at once.
In investing, money managers and risk officers seek to spread their risks over different geographies and markets for precisely the same reason.
The problem is, what works in insurance doesn't necessarily work in financial markets, because markets are prone to contagion.
A house fire in Saskatoon won't spark a conflagration in Tokyo, or any reaction at all, for that matter. But faced with something that shocks the financial world, such as falling U.S. home prices, investors on all continents and in all markets tend to react in a similar manner. Stocks, bonds, fancy CDOs and credit default swaps – the knee-jerk reaction is to sell them all, whether they trade in Toronto or New York or Tokyo.
In statistical terms, markets that don't show much correlation on good days can be very correlated in bad times, and there are no current models that reflect that fact.
“Historically, you see correlation between markets is not that high,” said John Hull, a risk-management specialist who teaches at the University of Toronto's Rotman School of Management. “But it's dangerous to base your risk management on those correlations because when things start to go wrong, the correlations start to go up.”
Along with correlation, another term has come to haunt risk managers: “tail risk.”
It's an odd name for the statistical chance that returns on any given investment will fall outside the normal probability of events. (When plotted on a graph, the statistically probable events are grouped in a bell curve, but there's a long tail of improbable events that trails off to one side, hence the name.)
In other words, most of the times markets behave normally. But every so often they don't. Those abnormal events fall in the “tail” of the risk curve.
Many risk managers, especially those at banks, use the normal probability concept to develop a yardstick called Value-at-Risk (VaR), which measures the amount a position taken by traders could lose on any statistically “normal” day. Normal is defined as a move of less than three standard deviations from the mean, and the assumption is that normalcy will reign for all but one day in a hundred, or even a thousand. That's when the tail comes into play.
Most banks look back three or four years to determine the likelihood of loss – meaning that just before last summer's blowup they were looking only at years of unnatural calm. Markets fooled the models.
“The tail events happen far more often than we would predict,” Mr. Gagnon said. “But what are the predictions based upon? The normal distribution of events.”
As a result, VaR failed investors. For example, CIBC had a daily VaR in the third quarter of 2007 that averaged $9.9-million, according to the bank's quarterly investor presentations. Yet three times in that quarter, as the credit crunch picked up steam and the bank booked writedowns, it lost more than that in a single day, including one loss of $120-million.
“The tails are always fatter than you think and the correlations are always higher than you expected,” Mr. Hull said.
Financial institutions augment VaR with stress tests, in which a range of possible outcomes are run through the models to see what happens. What if interest rates rose three percentage points in two months and the price of oil doubled?
Scotiabank, for example, can run 75 stress tests a day on its balance sheet. In fact, if Mr. Porter, the chief risk officer, thinks of a potential situation that worries him, he can have a test turned around by his team in as little as 24 hours.
But even stress testing fell short at many institutions during the credit crisis.
“VaR, stress tests and other risk measures significantly underestimated the magnitude of actual loss from the unprecedented credit market environment,” Merrill Lynch said in its third-quarter earnings filing, which revealed a writedown $8.4-billion of CDOs, mortgages and loans.
The problem, risk managers now say, is that there were no models that could accurately predict how the products would react because of the way that innovation had outpaced risk controls. In such a situation, there was no hope of coming up with an accurate estimate of the losses.
“When you're dealing with an opaque structure, there's no amount of stress scenarios that will reveal the true exposures you're putting on the balance sheet,” Mr. Gagnon said. “It all becomes a theoretical exercise. There's just no model.”
The problem, however, is not just with the models. It's also with the human brain. Because of the way humans think, they are unlikely to dream up the kinds of havoc that markets can wreak. People are just too programmed to think within the box, Mr. Hull said.
“The unfortunate thing is that human beings have this tendency to latch on to the most likely scenario, and as soon as they start thinking about that scenario they convince themselves that's what's actually going to happen,” Mr. Hull said. “That's the danger, that you become complacent, and you don't think about the range of alternative outcomes.”
The answer, then, may be a renewed deference to grey hair. The same experience that helped Mr. Watsa make his winning bet may help keep financial institutions on the right side of the risk curve.
The result is a renaissance for the credit officers who came of age in an era when banks largely only needed to focus on the risk of a client skipping out on a loan, only to be eclipsed by youngsters versed in the markets and slicing, dicing and repackaging loans for trading.
Those experienced managers were around to see the crash of 1987, the Russian debt crisis and, in many cases, the sky-high interest rates of the early 1980s. In other words, they have been around long enough to have seen markets move irrationally. That makes them invaluable for their ability to dream up scenarios to test the balance sheet, because they are unlikely to say: “That could never happen.”
“We have about a dozen PhDs in mathematics,” says Scotiabank chief executive officer Rick Waugh, 60. “We probably need about another dozen PhDs in human behaviour. And we probably need at least 12 risk officers with grey hair, because you need this balance.”
The result of the newfound respect for grey hair is that risk managers are starting to win the fight on at least one front – the cultural battle. Headhunters report that top risk managers have become one of the hottest commodities in the financial world.
Merrill Lynch CEO John Thain reached out to a veteran of Goldman Sachs Group Inc., home to perhaps the top risk culture, making him co-chief risk officer. The new risk czar, a 20-year veteran of markets named Noel Donohoe, will report directly to Mr. Thain, giving him the clout that risk managers need.
The pendulum is swinging back from the risk takers to the risk managers.
“If we eliminate risk, we eliminate the bank,” Mr. Waugh said. “We have to make money. But they [risk managers] have to have an independent voice. They have to call it the way they see it.”
Starting in 2003, and continuing through early 2007, Fairfax began to buy credit default swaps on U.S. companies. The buyer of such a derivative is essentially betting that the company's debt is overpriced – that the market has underestimated the odds of a financial failure.
Some of Fairfax's swaps were against the debt of so-called monoline insurers, companies like MBIA Inc. and Ambac Financial Group Inc., that guaranteed U.S. municipal bonds but had massive exposure to subprime mortgages and other risky debt.
“All you had to do was take a prospectus or you take their 10-K and you open it up and you say, ‘Let me look at the risk factors,'” Mr. Watsa said. “It's all there. And what's amazing is that when you read it, you can't believe that these guys did what they did.
“They never worried about risk.”
Neither did a lot of other people, until the credit crunch exposed tens of billions in toxic consumer debt, high-risk business loans, and complex, structured investment products. Some have called the U.S. mortgage crisis the biggest risk-management failure in financial history. Soothed by triple-A credit ratings, a strong economy and intricate risk-management plans, financial institutions and investors took on far more risk, and paid a much higher price, than they realized at the time.
The cause of their complacency, Mr. Watsa said, was the low volatility that prevailed between 2003 and 2006. “The only way that that could happen is we have to have a long period of stability – a long period where there wasn't any accidents. You'd never take that risk otherwise.”
It also happened because too many banks, insurers, hedge funds and rating agencies were given a false sense of security by statistical models that told them the probability of a financial “accident” was low. Where they used spreadsheets and algebra, aging investors like Mr. Watsa, 57, relied on their instincts and decades of experience to tell them something was amiss. And the grey-hairs won.
“We were shocked at how low the risk premiums went,” Mr. Watsa said...
Until last summer, as the economy and credit markets boomed, investors were clamouring for risk, taking on more and more for less in return. Optimism ruled.
The most tangible result was that market interest rates dove to record lows relative to government bonds, with even risky products such as junk bonds earning investors a scant premium to “risk-free” debt such as Treasury bills.
Fairfax won its bet when that trend reversed, starting last summer, as investors spooked by U.S. mortgage defaults once again demanded more compensation for taking chances...
Many of the answers lie in the uncertain science of risk management, which banks depend on to avoid pitfalls.
As markets flourished, financial institutions poured vast intellectual and electronic resources into creating fancy new products such as collateralized debt obligations (CDOs). At the same time, in a parallel universe also populated by PhDs and supercomputers, risk managers used statistical models in hopes of simulating what sudden market moves would do to the value of those securities and derivatives.
In all financial institutions, there is a daily battle between the risk takers and the risk managers. The takers push for bigger positions to make bigger profits, while the managers push for prudence and caution.
But as their warnings of potential loss were proved false each day by the soaring financial markets, many risk managers lost the ear of management teams focused on the vast profits generated by the people in the business of creating the structures. That led banks to take bigger and bigger bets.
“In a lot of these organizations that have had difficulties, the chief risk officer's role wasn't that meaningful or the business lines had more power and authority than the risk function did,” said Brian Porter, 50, chief risk officer at Bank of Nova Scotia, which has largely avoided the financial mess.
But some of the fault also lies with risk managers who relied too much on their tools, the statistical models, which were rapidly eclipsed by the rapid innovation in financial markets that begat complicated structures such as CDOs, so-called CDO squareds and structured investment vehicles (SIVs).
“Risk management tools are blunt instruments, which calls for prudence,” said Louis Gagnon, a former Royal Bank of Canada risk-management executive who now teaches business at Queen's University. “If you know you are driving your car on a foggy evening, you are supposed to go easy on the gas, but it's not necessarily what happens.”
Banks reeling from the massive losses are coming to realize that two of their key tenets of risk management – diversification and dependence on the so-called “normal distribution of events” – have been weighed in the balance of the credit crisis and found wanting.
Diversification has proved illusory because of a greater degree of correlation between asset classes and world markets than almost anybody expected.
The concept of avoiding correlation through diversification stems from the world of insurance. If you're going to insure homes, you have a greater chance of a big loss if all the houses you protect are on one street, or even in one town. There's too much risk of correlation, because a single hurricane or big fire could wipe them all out. One answer is to seek wider geographic diversification to cut correlation. Another is to insure in different markets, perhaps adding life or auto coverage to reduce the chance that all your customers will make claims at once.
In investing, money managers and risk officers seek to spread their risks over different geographies and markets for precisely the same reason.
The problem is, what works in insurance doesn't necessarily work in financial markets, because markets are prone to contagion.
A house fire in Saskatoon won't spark a conflagration in Tokyo, or any reaction at all, for that matter. But faced with something that shocks the financial world, such as falling U.S. home prices, investors on all continents and in all markets tend to react in a similar manner. Stocks, bonds, fancy CDOs and credit default swaps – the knee-jerk reaction is to sell them all, whether they trade in Toronto or New York or Tokyo.
In statistical terms, markets that don't show much correlation on good days can be very correlated in bad times, and there are no current models that reflect that fact.
“Historically, you see correlation between markets is not that high,” said John Hull, a risk-management specialist who teaches at the University of Toronto's Rotman School of Management. “But it's dangerous to base your risk management on those correlations because when things start to go wrong, the correlations start to go up.”
Along with correlation, another term has come to haunt risk managers: “tail risk.”
It's an odd name for the statistical chance that returns on any given investment will fall outside the normal probability of events. (When plotted on a graph, the statistically probable events are grouped in a bell curve, but there's a long tail of improbable events that trails off to one side, hence the name.)
In other words, most of the times markets behave normally. But every so often they don't. Those abnormal events fall in the “tail” of the risk curve.
Many risk managers, especially those at banks, use the normal probability concept to develop a yardstick called Value-at-Risk (VaR), which measures the amount a position taken by traders could lose on any statistically “normal” day. Normal is defined as a move of less than three standard deviations from the mean, and the assumption is that normalcy will reign for all but one day in a hundred, or even a thousand. That's when the tail comes into play.
Most banks look back three or four years to determine the likelihood of loss – meaning that just before last summer's blowup they were looking only at years of unnatural calm. Markets fooled the models.
“The tail events happen far more often than we would predict,” Mr. Gagnon said. “But what are the predictions based upon? The normal distribution of events.”
As a result, VaR failed investors. For example, CIBC had a daily VaR in the third quarter of 2007 that averaged $9.9-million, according to the bank's quarterly investor presentations. Yet three times in that quarter, as the credit crunch picked up steam and the bank booked writedowns, it lost more than that in a single day, including one loss of $120-million.
“The tails are always fatter than you think and the correlations are always higher than you expected,” Mr. Hull said.
Financial institutions augment VaR with stress tests, in which a range of possible outcomes are run through the models to see what happens. What if interest rates rose three percentage points in two months and the price of oil doubled?
Scotiabank, for example, can run 75 stress tests a day on its balance sheet. In fact, if Mr. Porter, the chief risk officer, thinks of a potential situation that worries him, he can have a test turned around by his team in as little as 24 hours.
But even stress testing fell short at many institutions during the credit crisis.
“VaR, stress tests and other risk measures significantly underestimated the magnitude of actual loss from the unprecedented credit market environment,” Merrill Lynch said in its third-quarter earnings filing, which revealed a writedown $8.4-billion of CDOs, mortgages and loans.
The problem, risk managers now say, is that there were no models that could accurately predict how the products would react because of the way that innovation had outpaced risk controls. In such a situation, there was no hope of coming up with an accurate estimate of the losses.
“When you're dealing with an opaque structure, there's no amount of stress scenarios that will reveal the true exposures you're putting on the balance sheet,” Mr. Gagnon said. “It all becomes a theoretical exercise. There's just no model.”
The problem, however, is not just with the models. It's also with the human brain. Because of the way humans think, they are unlikely to dream up the kinds of havoc that markets can wreak. People are just too programmed to think within the box, Mr. Hull said.
“The unfortunate thing is that human beings have this tendency to latch on to the most likely scenario, and as soon as they start thinking about that scenario they convince themselves that's what's actually going to happen,” Mr. Hull said. “That's the danger, that you become complacent, and you don't think about the range of alternative outcomes.”
The answer, then, may be a renewed deference to grey hair. The same experience that helped Mr. Watsa make his winning bet may help keep financial institutions on the right side of the risk curve.
The result is a renaissance for the credit officers who came of age in an era when banks largely only needed to focus on the risk of a client skipping out on a loan, only to be eclipsed by youngsters versed in the markets and slicing, dicing and repackaging loans for trading.
Those experienced managers were around to see the crash of 1987, the Russian debt crisis and, in many cases, the sky-high interest rates of the early 1980s. In other words, they have been around long enough to have seen markets move irrationally. That makes them invaluable for their ability to dream up scenarios to test the balance sheet, because they are unlikely to say: “That could never happen.”
“We have about a dozen PhDs in mathematics,” says Scotiabank chief executive officer Rick Waugh, 60. “We probably need about another dozen PhDs in human behaviour. And we probably need at least 12 risk officers with grey hair, because you need this balance.”
The result of the newfound respect for grey hair is that risk managers are starting to win the fight on at least one front – the cultural battle. Headhunters report that top risk managers have become one of the hottest commodities in the financial world.
Merrill Lynch CEO John Thain reached out to a veteran of Goldman Sachs Group Inc., home to perhaps the top risk culture, making him co-chief risk officer. The new risk czar, a 20-year veteran of markets named Noel Donohoe, will report directly to Mr. Thain, giving him the clout that risk managers need.
The pendulum is swinging back from the risk takers to the risk managers.
“If we eliminate risk, we eliminate the bank,” Mr. Waugh said. “We have to make money. But they [risk managers] have to have an independent voice. They have to call it the way they see it.”
- BOREALIS CAPITAL
A Case Study In Growth and Efficiency –
And Big Numbers.
Borealis Capital Corporation, a Toronto-based private merchant bank, is managed by Michael Nobrega and Ian Collier, two prominent names in Canadian finance. Collectively, the group has completed over $110 billion of equity, debt and mezzanine financings worldwide.
From Zero To 100 In No Time Flat
When Borealis was established two years ago, there were only six workstations. Today, there are nearly 100.
“In a financial service firm, downtime is lost time and lost money,”
[DESCRIPTION OF THEIR COMPUTER NETWORK]
“Our user base is demanding but not necessarily high tech in nature,” said Darren Soanes, an associate with Borealis Capital. “There is a great deal of information sharing, including rather sophisticated financial analyses and models, which are often sent back and forth internally and externally. The virtual private network that the LAN Shoppe installed accomplishes this quite well.”
Borealis’ Divisional Controller Jenny Hay explains, “Because the number of transactions we handle are small and yet the amounts are so high, the reliability of the system and the relationship with the network architect is critical.”
In addition, Borealis partners travel widely to the worlds’ capital markets and to their clients’ projects. So, high on their wish list was secure, reliable remote access to analyze multi million-dollar financing deals from other locations.
“You don’t want to reconstruct data. The information is too crucial. Cost-cutting in this area is not advised.”
Ms. Hay estimated the cost of downtime to the firm as reaching $200 per hour per user in productivity alone – and far more than that if it affects a major financing. “Our return on IT investment is in the continued functioning of the firm in case of a problem – and in the rapidity of response time from our network supplier.”
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