"Barry Gorton, a 57-year old finance professor and jazz buff, is emerging as an unlikely central figure in the near-collapse of American International Group Inc. ... But he also has a lucrative part-time gig: devising computer models used by the giant insurer to gauge risk in more than $400 billion of devilishly complicated deals called credit-default swaps. AIG relied on those models to help figure out which swap deals were safe. But AIG didn't anticipate how market forces and contract terms not weighed by the models would turn the swaps, over the short term, into huge financial liabilities. ... In the case of AIG, as with many other firms, the financial horrors were hidden in the enormous market for credit-default swaps, which are a form of insurance against defaults on all sorts of debts. ... Had the sheer complexity of the financial products made it all but impossible to fully calculate the risk? And did the firms put too much faith in computer models to assess dangers? ... Warren Buffett ... [r]ecently told PBS interviewer Charlie Rose: 'All I can say is, beware of geeks ... bearing formulas.' ... In essence, AIG sold insurance of billions of dollars of debt securities backed by everything from corporate loans to subprime mortgages to auto loans to credit-card receivables. It promised buyers of the swaps that if the debt securities defaulted, AIG would make good on them. ... In addition, AIG is obliged to account for the contracts on its own books based on their market values. If those values fall, AIG has to take write-downs. ... But as AIG was aware, [Gordon's] models didn't attempt to measure the risk of future collateral calls or write-downs, which have devastated AIG's finances. Goldman Sachs Group Inc. [GSG], for instance, has pried from AIG $8 billion to $9 billion, covering virtually all its exposure to AIG--most of it before the U.S. stepped in. ... Eventually, [Gorton] collected multiple degrees, including a Ph.D. in economics, and joined the faculty of the Wharton School. ... One of his academic interests was how banks could unload risk and sell loans to investors. ... Gorton collected vast amounts of data and built models to forecast losses on pools of assets such as home loans and corporate bonds. ... Gorton's work 'helped convince [Joseph] Cassano [of AIG] that these things were only gold, that if anybody paid you to take on these risks, it was free money' because AIG would never have to make payments to cover actual defaults. ... For years, the business was extremely lucrative. ... AIG's trading partners were worried, [GSG] held swaps from AIG that insured about $20 billion of securities. In August 2007, [GSG] demanded $1.5 billion in collateral, arguing that the assets backing the securities were falling in value. ... Late last October, [GSG] asked for even more collateral, $3 billion. [GSG] hedged its exposure by making a bearish bet on AIG, buying credit-default swaps on AIG's own debt, according to one person knowledgeable about this move. ... Gorton [said] 'The models are all extremely simple.' ... 'They're highly data intensive'," my emphasis, WSJ, 3 November 2008.
"Today's economic turmoil, it seems, is an implicit indictment of the arcane field of financial engineering--a blend of mathematics, statistics and computing. Its practitioners devised not only the exotic, mortgage-backed securities that proved so troublesome, but also the mathematical models of risk that suggested these securities were safe. ... 'Innovation can be a dangerous game,' said Andrew W. Lo, an economist and proefssor of finance at the Sloan School of Management of the Massachusetts Institute of Technology. 'The technology got ahead of our ability to use it in responsible ways.' ... Credit-default swaps, though intended to spread risk, have magnified the financial crisis because the market is unregulated, obscure and brimming with counterparty risk (that is, the risk that one embattled bank or firm will not be able to meet its payment obligations, and that trading with it will seize up). The market for [CDSs] has been at the center of the recent Wall Street banking failures and rescues, and these instruments embody the kinds of risks not easily captured in math formulas. ... Math, statistics and computer modeling, it seems, also fell short in calibrating the lending risk on individual mortgage loans. 'If the incentives and the systems change, the hard data can mean less that it did or something else than it did,' said Raghuram G. Rajan, a professor at the University of Chicago. The danger is that the modeling becomes too mechanical.' ... [Four Fed] economists ... surveyed the published research reports by Wall Street analysts and economists, and asked why the Wall Street experts failed to foresee the surge in subprime foreclosures in 2007 and 2008. The Fed economists concluded that the risk models used by Wall Street analysts correctly predicted a drop in real estate prices of 10 or 20 percent would imperil the market for subprime mortgage-backed sucurities. But the analysts themselves assigned a very low probablility to that happening. The miss by Wall Street analysts shows how models can be precise out to several decimal places, and yet be totally off base. ... The quantitative models typically have their origins in academia and often in the physical sciences. In academia, the focus is on problems than can be solved, proved and published--not messy, intractible challenges. In science, the models derive from particle flows in a liquid or a gas, which conform to the neat, crisp laws of physics. ... Emanuel Derman is a physicist who became a managing director at Goldman Sachs, a quant whose name is on a few financial models and authorof 'My Life as a Quant--Reflections on Physics and Finance' (Wiley, 2004). In a paper that will be published next year in a professional journal, Mr. Derman writes, '
To confuse the model with the world is to embrace a future disaster driven by the belief that humans obey mathematical rules'," my emphasis, Steve Lohr at
http://www.nytimes.com/, 5 November 2008.
Michael Panzner at Financial Armageddon read this article too and on 3 November noted, "One failing of at least some of those who inhabit the academic world is a relentlessly popular and hopelessly arrogant delusion that human behavior can be reduced to formulas that others can or should rely on. Economists and finance experts seem especially guilty in this respect, having dreamed up models that regularly fail to predict anything that might be of value to those who must make decisions about what the future holds", well said Mike. Here's a link: http://www.financialarmageddon.com/2008/11/poisoned-math.html?cid=137572728.
Professor Siegel, apparently Gorton was once one of your "boys". Could you take him aside and in an avuncular way tell him about technical stock market analysis? Please. How do I see CDSs? First, they violate Uncle Miltie's TANSTAAFL principle. In the capital markets you pay. As I've written before, these products, unlike life insurance, can't be effectively modeled. GSG got paid before Uncle Sam stepped in. Did GSG benefit from a preference payment? Is the push to end mark-to-market accounting to conceal AIG's insolvency which may have predated GSG's payments? Will Dudley Do-right save Nell Fenwick from the oncoming train? Models "to forecast losses on pools of assets"? You're kidding? The ghost of Wassily Leontief haunts Wall Street. Gold, or fool's gold?
Let's return to "Fama-Miller" finance. Initial conditions:
Company A: market cap of stock, $10, of debt $8, total = $18.
Company B: market cap of stock, $20, of debt $10, total = $30.
Total combined value = $48.
Company A's debt has an "A" S&P credit rating, Company B, "AAA".
Now B issues a CDS on $4 of A's debt for a fee. How can the total value change? If it was $48 before, it will be $48 after. Neither A's nor B's operating cash flows change. If the value of A's debt went up because it is now rated "AAA", B's should fall. What am I missing? How does financial engineering turn lead into gold?
See my posts on financial alchemy:
1 comment:
CDS was kinda like the universe... expanding outward at a steady rate...
It's interesting how it took a year after the credit crisis started for the synthetic CDOs to really start imploding... (maybe it was before?)
SF modeling is for girlie men... (++)
GS... I don't want to get started on them... skunks...
Money quote = "The quantitative models typically have their origins in academia and often in the physical sciences. In academia, the focus is on problems than can be solved, proved and published--not messy, intractible challenges...."
Right "messy, intractible challenges" ... maybe like fraud and market manipulation? Just wondering...
Post a Comment