I first encountered Andrew Redleaf, founder and CEO of Whitebox Advisors, when he was a guest lecturer in Robert Shiller’s Yale economics course, available online. Even though he was somewhat ill at ease in the classroom, he came across as an intriguing thinker.
Panic: The Betrayal of Capitalism by Wall Street and Washington (Richard Vigilante Books, 2010) co-authored by Redleaf and Richard Vigilante, the communications director of Redleaf’s hedge fund, is a compelling work. It is for the most part an intellectual history of the financial meltdown, demonstrating how Wall Street became the victim of its own faulty paradigms. Unfortunately, the book could not be written in the past tense because most of these paradigms are still secure atop their pedestals. Until there is a paradigm shift we will continue to experience recurring economic havoc.
The overarching paradigm is that efficient markets are superior to free markets, that human judgment is inferior to structures and systems, and that, by extension, “public securities markets—computerized, blazingly fast, effusively liquid—are as close as mankind has ever come to realizing the perfectly efficient market of classical economic theory.” (p. 7) Even Thursday’s tape action has not called this model into question; rather, the solutions being bandied about focus simply on coordinating the existing structures and systems.
The authors proceed to dissect the notion of efficiency and some of its equally flawed ideological relatives. Among them: that investors are paid for taking risk, that if the so-called smart money (mutual fund managers are singled out because their performance is a matter of public record) can’t beat the market no one can, that technical analysis does not work because scientifically rigorous studies demonstrate that it provides at best only a minimal edge often erased by commissions, and that the primary skill of finance is diversification.
The book’s arguments are carefully developed. They are often nuanced, so summary will not do them justice. With that caveat I’m going to look briefly at the flawed idea that can most easily be separated out from the main argument of the book—that technical analysis doesn’t work.
The weak form of the efficient market hypothesis claims that technical analysis is bunk because “the very next price change in a publicly traded stock will be statistically indistinguishable from a random change.” Wrong, claim the authors. “In an efficient market, prices are fully ‘determined’ by the flow of information that the market is processing.” (p. 81) If a market is efficient we are, in the words of yesterday’s blog post, dealing with epistemic uncertainty, not stochastic uncertainty.
Critics of technical analysis would not be moved by this argument. Instead, they would press on, citing the numerous studies that have shown the limited value of technical analysis. The authors don’t fault the studies; they simply note that the academics were necessarily constrained by the rigors of scientific methodology. They couldn’t do what “adroit market practitioners do.” They couldn’t pick and choose, highlighting time periods when past prices predicted future prices and ignoring those blocks of time when they didn’t, or pointing to the handful of stocks where technical analysis worked and excluding evidence from the overwhelming majority. Savvy investors don’t have the scientific scruples of academicians. Here let me quote at length: “We assume that potentially profitable anomalies appear and disappear as market conditions change. We assume that such anomalies are almost certain to be more powerful and profitable for some sets of securities than for others. . . . When we build quantitative tools, our goal is not to find algorithms that work for all eternity across any arbitrarily defined class of securities. We look for tools that deliver very strong results over time periods biased to the near term. And in building the universe of securities to which to apply the algorithm, we do not choose some neutrally defined class that would please an academic such as every stock in the S&P or every large cap. We select a subset of securities with favorable characteristics that make them good candidates for the algorithm. . . . Once we go live, we monitor the universe, tossing securities whose behavior no longer seems to be well predicted by the algorithm and adding others that seem promising.” (p. 85)
In this review I’ve barely touched the surface of this book. For instance, I’ve not said a word about the role of Washington in the whole mess. Well, that’s the problem with good books—just too many ideas in them! This one also has the added benefit of being well written, with a healthy dose of humor. There’s even a theoretical rationale for the good style: “If economics were about entrepreneurship [which the authors advocate], it would not look like physics. It would look a little like philosophy. Mostly it would look like literature." (p. 49)
Panic is one of the best books I’ve read in a long time and one of the very few I can wholeheartedly recommend to everyone—liberal or conservative, investor or trader—who appreciates contrarian thinking.
Tuesday, May 11, 2010
Monday, May 10, 2010
Stochastic and epistemic uncertainty
Are there two kinds of uncertainty, one a property of systems and the other a property of our knowledge of systems? The first, known alternatively as stochastic uncertainty, aleatory uncertainty, and randomness, resides in the real world and is irreducible. The second, epistemic uncertainty, is a function of our lack of knowledge about the world and is reducible by acquiring more or better information.
Terje Aven in Misconceptions of Risk takes an unabashedly idealist position, contending that all uncertainties are epistemic. He quotes R. L. Winkler: “Consider the tossing of a coin. If we all agree that the coin is fair, then we would agree that the probability that it lands heads the next time it is tossed is one-half. At first glance, our uncertainty about how it lands might be thought of as aleatory, or irreducible. Suppose, however, that the set of available information changes. In principle, if we knew all of the conditions surrounding the toss (the initial side facing up; the height, initial velocity, and angle of the coin; the wind; the nature of the surface on which the coin will land; and so on), we could use the laws of physics to predict with certainty or near certainty whether the coin will land heads or tails. Thus, in principle, the uncertainty is not irreducible, but is a function of the state of knowledge (and hence is epistemic).” (p. 146)
How should we understand market uncertainty? And how does the model that we choose inform our trading strategies?
If we assume that markets move randomly or at least with enough randomness that we cannot predict a single sequence or do better than 50-50 calling a series of sequences, we should abandon all attempts to gain an edge with our entries. No amount of work on our part will improve our entries over those of the dart thrower. Either we buy an index fund and trust that over time markets will rise or we become really savvy risk managers, protecting our assets while steering our trades toward gains and counting on that inevitable outlier somewhere down the pike.
If we assume that market uncertainty is epistemic, we can gain an edge by increasing our knowledge of market movements. Analysts churn out reports on individual companies, economists provide data and every kind of opinion you’d ever want to hear, chartists study how the past can portend the future. There are enough pockets of success for us to believe that market uncertainty is at least in part epistemic and that knowledge can make a real difference.
Beginners are true believers in epistemic uncertainty; professionals tend to have more respect for the randomness of markets. As Don Kaufman said in a recent Think or Swim chat on the Greeks and expiration (one that I highly recommend for anyone with even the most marginal interest in options), “Most retail traders are good at finding trades, bad at managing trades. Most professional traders are good at managing risk, less good at finding trades.”
Even though I believe that market uncertainty is at least in part epistemic, I think we would all be well served to work under the hypothesis that market uncertainty is stochastic. That hypothesis forces us to manage risk in ways that can be both imaginative and effective. Whatever we earn over and above that from our stock picking skills or whatever other means we use to enter a position is pure gravy!
Terje Aven in Misconceptions of Risk takes an unabashedly idealist position, contending that all uncertainties are epistemic. He quotes R. L. Winkler: “Consider the tossing of a coin. If we all agree that the coin is fair, then we would agree that the probability that it lands heads the next time it is tossed is one-half. At first glance, our uncertainty about how it lands might be thought of as aleatory, or irreducible. Suppose, however, that the set of available information changes. In principle, if we knew all of the conditions surrounding the toss (the initial side facing up; the height, initial velocity, and angle of the coin; the wind; the nature of the surface on which the coin will land; and so on), we could use the laws of physics to predict with certainty or near certainty whether the coin will land heads or tails. Thus, in principle, the uncertainty is not irreducible, but is a function of the state of knowledge (and hence is epistemic).” (p. 146)
How should we understand market uncertainty? And how does the model that we choose inform our trading strategies?
If we assume that markets move randomly or at least with enough randomness that we cannot predict a single sequence or do better than 50-50 calling a series of sequences, we should abandon all attempts to gain an edge with our entries. No amount of work on our part will improve our entries over those of the dart thrower. Either we buy an index fund and trust that over time markets will rise or we become really savvy risk managers, protecting our assets while steering our trades toward gains and counting on that inevitable outlier somewhere down the pike.
If we assume that market uncertainty is epistemic, we can gain an edge by increasing our knowledge of market movements. Analysts churn out reports on individual companies, economists provide data and every kind of opinion you’d ever want to hear, chartists study how the past can portend the future. There are enough pockets of success for us to believe that market uncertainty is at least in part epistemic and that knowledge can make a real difference.
Beginners are true believers in epistemic uncertainty; professionals tend to have more respect for the randomness of markets. As Don Kaufman said in a recent Think or Swim chat on the Greeks and expiration (one that I highly recommend for anyone with even the most marginal interest in options), “Most retail traders are good at finding trades, bad at managing trades. Most professional traders are good at managing risk, less good at finding trades.”
Even though I believe that market uncertainty is at least in part epistemic, I think we would all be well served to work under the hypothesis that market uncertainty is stochastic. That hypothesis forces us to manage risk in ways that can be both imaginative and effective. Whatever we earn over and above that from our stock picking skills or whatever other means we use to enter a position is pure gravy!
Saturday, May 8, 2010
Coming attractions
I had a post all set to publish on Friday, but after Thursday’s terrifying tape I decided that no one would be in the mood for a reflection on stochastic vs. epistemic uncertainty, even though I personally think it’s important. So, barring some further calamity, it will appear on Monday.
Next week I’ll also review Andrew Redleaf and Richard Vigilante’s book Panic, which mercifully is ever so much richer than its title. It’s a very thought-provoking read.
Next week I’ll also review Andrew Redleaf and Richard Vigilante’s book Panic, which mercifully is ever so much richer than its title. It’s a very thought-provoking read.
Thursday, May 6, 2010
What good are puzzles anyway?
Okay, all you geniuses who solved the puzzle and realized that the Norwegian drinks water and the Japanese owns the zebra, what have you accomplished? Do you just belong to the group of people who are, as someone once snidely described me, “good at taking tests”?
John Adair’s Decision Making and Problem Solving Strategies (first published in 1997, new edition reissued by Kogan Page in 2010) is addressed to business leaders. But it’s not a stretch to extend its audience to investors and traders.
As you might imagine, he doesn’t envisage a CEO spending his time figuring out who drinks water and who owns the zebra. But puzzle solving is not without its practical merits. For instance, it can distract the conscious mind so the “depth mind” that offers up educated intuitions can work. A case in point. In a psychological experiment volunteers were asked to decide which car out of a field of four to buy; one was clearly superior. They had a fixed amount of time to decide. Half of the group spent their time studying an abundance of information about the cars; the other half were given puzzles to solve to keep their minds busy. Guess who picked the best car? Well, of course, the puzzle solvers.
But solving puzzles has limited value. The reason is that puzzles, and many kinds of problems in general, are solutions in disguise. That is, to find a solution we only have to arrange or rearrange the elements we have been given in some clever way using skills we have acquired by solving many similar puzzles. Jigsaw puzzles are the most obvious example. But most math problems are also solutions in disguise; apply a rule or two, move a few letters or numbers around, and voilà!
Many system builders are puzzle solvers. They start with, let’s say, price, time, and volume and then try to find some way of expressing one or more of these elements with some indicator(s) that will expose market inefficiencies. They tweak here, optimize there, and more often than not start over again; they have, they admit, come up with an unsatisfactory solution. System design becomes addictive, most likely because for the most part it is a variety of puzzle solving, though one that never has a definitive answer.
To be truly creative we have to move beyond plain vanilla puzzle solving. We have to do more than perform some familiar operations to reach a conclusion or rearrange the parts to create a whole. Perhaps we could find real connections, however fleetingly applicable, that others have not found. (Our model here could be Renaissance Technologies, though most of us would be hard pressed to rise to their level of expertise.) Or we could devise a strategy (think of Ed Thorp’s convertible bond arbitrage, highly successful until everybody started copying it) that will profit from buying an undervalued asset and hedging risk. Of course, these tasks are ever so much more difficult than ordinary puzzle solving. But then whoever won a major math prize for solving an Algebra I problem?
In the meantime there’s still good money to be made by tapping into the “depth mind.” And here puzzles can distract the trader from making bad decisions stemming from information overload.
I enjoy puzzles far too much to proclaim them worthless wastes of time!
John Adair’s Decision Making and Problem Solving Strategies (first published in 1997, new edition reissued by Kogan Page in 2010) is addressed to business leaders. But it’s not a stretch to extend its audience to investors and traders.
As you might imagine, he doesn’t envisage a CEO spending his time figuring out who drinks water and who owns the zebra. But puzzle solving is not without its practical merits. For instance, it can distract the conscious mind so the “depth mind” that offers up educated intuitions can work. A case in point. In a psychological experiment volunteers were asked to decide which car out of a field of four to buy; one was clearly superior. They had a fixed amount of time to decide. Half of the group spent their time studying an abundance of information about the cars; the other half were given puzzles to solve to keep their minds busy. Guess who picked the best car? Well, of course, the puzzle solvers.
But solving puzzles has limited value. The reason is that puzzles, and many kinds of problems in general, are solutions in disguise. That is, to find a solution we only have to arrange or rearrange the elements we have been given in some clever way using skills we have acquired by solving many similar puzzles. Jigsaw puzzles are the most obvious example. But most math problems are also solutions in disguise; apply a rule or two, move a few letters or numbers around, and voilà!
Many system builders are puzzle solvers. They start with, let’s say, price, time, and volume and then try to find some way of expressing one or more of these elements with some indicator(s) that will expose market inefficiencies. They tweak here, optimize there, and more often than not start over again; they have, they admit, come up with an unsatisfactory solution. System design becomes addictive, most likely because for the most part it is a variety of puzzle solving, though one that never has a definitive answer.
To be truly creative we have to move beyond plain vanilla puzzle solving. We have to do more than perform some familiar operations to reach a conclusion or rearrange the parts to create a whole. Perhaps we could find real connections, however fleetingly applicable, that others have not found. (Our model here could be Renaissance Technologies, though most of us would be hard pressed to rise to their level of expertise.) Or we could devise a strategy (think of Ed Thorp’s convertible bond arbitrage, highly successful until everybody started copying it) that will profit from buying an undervalued asset and hedging risk. Of course, these tasks are ever so much more difficult than ordinary puzzle solving. But then whoever won a major math prize for solving an Algebra I problem?
In the meantime there’s still good money to be made by tapping into the “depth mind.” And here puzzles can distract the trader from making bad decisions stemming from information overload.
I enjoy puzzles far too much to proclaim them worthless wastes of time!
Wednesday, May 5, 2010
The paradox of diversification
Sometimes, writing this blog, I sense a woeful dearth of new ideas. I despair that I’ll come across as an oldster repeating the same story over and over, believing that I’m telling it for the first time. It’s true that I don’t remember every post I’ve written, but that’s not the problem. Rather, this blog occasionally becomes repetitive because there’s just as much herding in the world of financial literature as there is in the markets themselves.
In the wake of the financial collapse one of the “hot topics” is the failure of diversification to protect portfolios. I wrote about this briefly in my recent post on The Endowment Model of Investing. John Authers in The Fearful Rise of Markets: Global Bubbles, Synchronized Meltdowns, and How to Prevent Them in the Future (FT Press, 2010) joins in the conversation. He points to the new “paradox of diversification”—that “the more investors bought in to assets on the assumption that they were not correlated, the more they tended to become correlated.” (p. 166)
In fact, he writes, everyone was exposed to the same risks. Liquidity risk was the most serious; the second was that the run-up in commodity prices would end.
Echoing Mohamed El-Erian, he claims that asset allocation should be done according to type of risk. Instead of balancing asset classes, he suggests that it might be more sensible to balance, for instance, the risks of inflation and deflation. Admittedly, his prose is much clearer than El-Erian’s, but that may be because his suggestion is simpler. (I wrote about El-Erian’s idea early in the life of this blog and offered a few thoughts about how traders could flesh it out.) For those who don’t recall El-Erian’s words in When Markets Collide, here they are:
“The ideal situation is to come up with a small set (three to five) of distinct (and ideally orthogonal) risk factors that command a risk premium. The next step is to assess the stability of the factors and how they can be best captured through the use of tradable instruments. This provides for a portfolio optimization process whereby the factors are combined in a manner that speaks directly to the investors’ return objective and risk tolerance. The end product is a more robust and time-consistent combination of asset classes that map clearly to the underlying factors.” (p. 233)
In an unleveraged or modestly leveraged world this style of portfolio building makes eminent sense and is theoretically elegant to boot. But as leverage increases and, in a crisis, funds sell whatever they can to meet margin calls, it doesn’t matter how carefully constructed a long-only portfolio is and on what principles it is diversified; it will get whacked. (I specifically use the example of a long-only portfolio because it was for this kind of portfolio that the traditional asset allocation model was devised. A hedged portfolio is a different kettle of fish altogether.)
Personally I prefer the notion of a portfolio with many moving parts rather than one that is fixed for a certain period of time—let’s say rebalanced once a year. Indeed, why not make a very difficult task a herculean one?
In the wake of the financial collapse one of the “hot topics” is the failure of diversification to protect portfolios. I wrote about this briefly in my recent post on The Endowment Model of Investing. John Authers in The Fearful Rise of Markets: Global Bubbles, Synchronized Meltdowns, and How to Prevent Them in the Future (FT Press, 2010) joins in the conversation. He points to the new “paradox of diversification”—that “the more investors bought in to assets on the assumption that they were not correlated, the more they tended to become correlated.” (p. 166)
In fact, he writes, everyone was exposed to the same risks. Liquidity risk was the most serious; the second was that the run-up in commodity prices would end.
Echoing Mohamed El-Erian, he claims that asset allocation should be done according to type of risk. Instead of balancing asset classes, he suggests that it might be more sensible to balance, for instance, the risks of inflation and deflation. Admittedly, his prose is much clearer than El-Erian’s, but that may be because his suggestion is simpler. (I wrote about El-Erian’s idea early in the life of this blog and offered a few thoughts about how traders could flesh it out.) For those who don’t recall El-Erian’s words in When Markets Collide, here they are:
“The ideal situation is to come up with a small set (three to five) of distinct (and ideally orthogonal) risk factors that command a risk premium. The next step is to assess the stability of the factors and how they can be best captured through the use of tradable instruments. This provides for a portfolio optimization process whereby the factors are combined in a manner that speaks directly to the investors’ return objective and risk tolerance. The end product is a more robust and time-consistent combination of asset classes that map clearly to the underlying factors.” (p. 233)
In an unleveraged or modestly leveraged world this style of portfolio building makes eminent sense and is theoretically elegant to boot. But as leverage increases and, in a crisis, funds sell whatever they can to meet margin calls, it doesn’t matter how carefully constructed a long-only portfolio is and on what principles it is diversified; it will get whacked. (I specifically use the example of a long-only portfolio because it was for this kind of portfolio that the traditional asset allocation model was devised. A hedged portfolio is a different kettle of fish altogether.)
Personally I prefer the notion of a portfolio with many moving parts rather than one that is fixed for a certain period of time—let’s say rebalanced once a year. Indeed, why not make a very difficult task a herculean one?
Tuesday, May 4, 2010
A puzzle to fritter away some time
I’ve started reading John Adair’s Decision Making and Problem Solving Strategies, about which you will undoubtedly hear more later. But today let me share a puzzle that you can work on when the markets are quiet. Adair gives his readers 30 minutes to solve it.
1. There are five houses, each with a front door of a different color, and inhabited by people of different nationalities, with different pets and drinks. Each person eats a different kind of food.
2. The Australian lives in the house with the red door.
3. The Italian owns the dog.
4. Coffee is drunk in the house with the green door.
5. The Ukrainian drinks tea.
6. The house with the green door is immediately to the right (your right) of the house with the ivory door.
7. The mushroom-eater owns snails.
8. Apples are eaten in the house with the yellow door.
9. Milk is drunk in the middle house.
10. The Norwegian lives in the first house on the left.
11. The person who eats onions lives in the house next to the person with the fox.
12. Apples are eaten in the house next to the house where the horse is kept.
13. The cake-eater drinks orange juice.
14. The Japanese eats bananas.
15. The Norwegian lives next to the house with the blue door.
Who drinks water and who owns the zebra?
Please wait until tomorrow to post your answers.
1. There are five houses, each with a front door of a different color, and inhabited by people of different nationalities, with different pets and drinks. Each person eats a different kind of food.
2. The Australian lives in the house with the red door.
3. The Italian owns the dog.
4. Coffee is drunk in the house with the green door.
5. The Ukrainian drinks tea.
6. The house with the green door is immediately to the right (your right) of the house with the ivory door.
7. The mushroom-eater owns snails.
8. Apples are eaten in the house with the yellow door.
9. Milk is drunk in the middle house.
10. The Norwegian lives in the first house on the left.
11. The person who eats onions lives in the house next to the person with the fox.
12. Apples are eaten in the house next to the house where the horse is kept.
13. The cake-eater drinks orange juice.
14. The Japanese eats bananas.
15. The Norwegian lives next to the house with the blue door.
Who drinks water and who owns the zebra?
Please wait until tomorrow to post your answers.
Monday, May 3, 2010
Ward, The Devil's Casino
Over the weekend I read Vicky Ward’s The Devil’s Casino: Friendship, Betrayal, and the High-Stakes Games Played Inside Lehman Brothers (Wiley, 2010). Ward, who started off her career in England as a gossip columnist and is now a contributing editor for Vanity Fair, focuses on the people who ran Lehman and the culture they instilled. It’s harder to mourn the demise of the firm after reading this book.
Take, for instance, the chapter entitled “Lehman’s Desperate Housewives.” The wives of the top brass at Lehman were expected to attend countless corporate and social events, they were told what charities they were expected to donate to and how much they were expected to give, they were expected to dress appropriately for every occasion, and they were expected to attend the annual summer get-together at the Fulds’ ranch in Sun Valley, Idaho, where (among other things) they were expected to hike. One wife hated the rigorous hike up Bald Mountain so much that she arrived in Sun Valley with a fake cast on her leg. Unfortunately her scheme failed because another wife, higher up in the pecking order, arrived with a real broken leg and announced that, broken leg or not, she planned to climb.
The Lehman dress code was taken seriously. Dick Fuld’s motto was “Sloppy dress, sloppy thinking.” The dress code extended beyond the office. For instance, on the golf course men were expected to wear either a golf or a button-down shirt and khaki pants. And when the co-head of global equities appeared at an off-site meeting dressed business casual, Fuld announced “Off-site, yes. Out of mind, no.”
To meet these expectations and to indulge themselves some Lehman executives and their wives relied on outsized personal staffs. Niki Gregory had a staff of about 30 who seemed to do everything except shop for shoes; that she did herself, filling a closet “twice the size of the Jimmy Choo store in New York.” Joe Gregory had his own domestic staff of 30, presumably to take care of his fleet of boats, multiple houses, and private planes. And Erin Callan, named CFO in 2007 despite no finance background, saw nothing wrong with talking to the Wall Street Journal about her personal shopper at Bergdorf Goodman even as Lehman was fighting for its life.
To those who know Wall Street culture these stories may seem typical, not unique to Lehman. Worse, they may seem irrelevant to the financial crisis. I have no first-hand knowledge, but throughout Ward’s book one could see ways in which corporate expectations led to group-think. Just as no one in the upper echelons could challenge the dress code, so no one seemed prepared to challenge Lehman’s appetite for risk. The firm rewarded loyalty and discouraged dissent. In 2007 Hank Paulson warned securities firms to recapitalize, but Lehman kept growing its leveraged businesses and piling on billions of debt. The head of risk management was demoted and subsequently left; “she says she couldn’t believe the stupidity of what she was seeing—and she had seen a lot.”
Joe Gregory introduced a diversity program at Lehman, which received much praise. But diversity is useful to a firm only if it brings with it a diversity of opinions, not just a diversity of sex, skin color, or sexual orientation. And this diversity of opinions must have a voice. It’s hard to run a business effectively in an echo chamber. The demise of Lehman Brothers bears sad witness to this fact.
Take, for instance, the chapter entitled “Lehman’s Desperate Housewives.” The wives of the top brass at Lehman were expected to attend countless corporate and social events, they were told what charities they were expected to donate to and how much they were expected to give, they were expected to dress appropriately for every occasion, and they were expected to attend the annual summer get-together at the Fulds’ ranch in Sun Valley, Idaho, where (among other things) they were expected to hike. One wife hated the rigorous hike up Bald Mountain so much that she arrived in Sun Valley with a fake cast on her leg. Unfortunately her scheme failed because another wife, higher up in the pecking order, arrived with a real broken leg and announced that, broken leg or not, she planned to climb.
The Lehman dress code was taken seriously. Dick Fuld’s motto was “Sloppy dress, sloppy thinking.” The dress code extended beyond the office. For instance, on the golf course men were expected to wear either a golf or a button-down shirt and khaki pants. And when the co-head of global equities appeared at an off-site meeting dressed business casual, Fuld announced “Off-site, yes. Out of mind, no.”
To meet these expectations and to indulge themselves some Lehman executives and their wives relied on outsized personal staffs. Niki Gregory had a staff of about 30 who seemed to do everything except shop for shoes; that she did herself, filling a closet “twice the size of the Jimmy Choo store in New York.” Joe Gregory had his own domestic staff of 30, presumably to take care of his fleet of boats, multiple houses, and private planes. And Erin Callan, named CFO in 2007 despite no finance background, saw nothing wrong with talking to the Wall Street Journal about her personal shopper at Bergdorf Goodman even as Lehman was fighting for its life.
To those who know Wall Street culture these stories may seem typical, not unique to Lehman. Worse, they may seem irrelevant to the financial crisis. I have no first-hand knowledge, but throughout Ward’s book one could see ways in which corporate expectations led to group-think. Just as no one in the upper echelons could challenge the dress code, so no one seemed prepared to challenge Lehman’s appetite for risk. The firm rewarded loyalty and discouraged dissent. In 2007 Hank Paulson warned securities firms to recapitalize, but Lehman kept growing its leveraged businesses and piling on billions of debt. The head of risk management was demoted and subsequently left; “she says she couldn’t believe the stupidity of what she was seeing—and she had seen a lot.”
Joe Gregory introduced a diversity program at Lehman, which received much praise. But diversity is useful to a firm only if it brings with it a diversity of opinions, not just a diversity of sex, skin color, or sexual orientation. And this diversity of opinions must have a voice. It’s hard to run a business effectively in an echo chamber. The demise of Lehman Brothers bears sad witness to this fact.
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