Making the Quantitative Models Work

By Michael Feldman

October 2, 2008

The ongoing financial turmoil in the U.S. continues to flog the stock market and the credit market. Not surprisingly, economists are in disarray, predicting everything from a mild recession to the end of capitalism. What is more widely agreed upon is the root cause: the bursting of the housing bubble and the related sub-prime and adjustable rate mortgages that banks and investment firms have been accumulating and trading like baseball cards.

As I wrote last week, the quantitative models used to value these mortgages (in the form of collateralized debt obligations or CDOs) were probably suspect or, at the very least, were being misused. Digging a little deeper, it appears that this was the case across the spectrum of buyers, sellers and rating agencies throughout the investment community.

The problems with the CDO models have been known for some time. In a Wall Street & Technology article from September 2007, Penny Crosman begins thusly: “Why didn’t the sophisticated, computerized pricing models that Wall Street firms use to predict returns and risk for complex derivatives save them from the sub-prime mortgage mess? The short answer is: Fund and portfolio managers rarely use them.” Crosman goes on to reveal some problems with the algorithms themselves, noting that “some models for analyzing mortgage-backed securities don’t include house prices, which are a fairly important piece of the puzzle.” In other cases, the models were simplified for the sake of expediency. One quant noted that “[t]raders will like a light model because they don’t need heavy routines that will take forever to run on their machines.”

A lot of the problem started with the rating agencies at places like Standard and Poor’s (S&P), Moody’s and Fitch. In a recent article by Elliot Blair Smith in Bloomberg News, the author makes the case that the agencies mismanaged the models. Frank Raiter, a former director of S&P’s business unit that rated residential mortgages, tried to urge management to “develop more sophisticated financial models and buy more detailed loan data for monitoring securities the company graded.”

But as long as real estate prices kept rising, there was little incentive for either the rating agencies or their customers to make the ratings more robust. Everyone profited by keeping the party going.

Smith lays some of blame on the quantitative models themselves, noting: “AAA ratings on sub-prime mortgage investments can be traced to the rise on Wall Street of quantitative analysts, or quants, with advanced degrees in math, physics and statistics. They developed computer-driven models that didn’t rely on historical performance data, according to Raiter and others. If the old rating methods were like Rembrandt’s portraiture, with details painted in, the new ones were Monet impressionism, with only a suggestion of the full picture.”

In truth, though, compared to corporate-backed securities, there wasn’t a long record for the mortgage-backed version, which came into vogue relatively recently. This lack of historical context hid a lot of risk in the CDOs, and since these types of securities weren’t being priced on the open market, extra risk was already built in.

The way those mortgage-backed securities are valued may soon become everyone’s problem. As I write this, the Senate has passed the $700 billion economic bailout package and the House is getting ready to vote on the measure. If it becomes law — and this is by no means assured — the U.S. government will have to figure out how to value all these mortgage-based CDOs as well as other stressed assets like their corporate-backed counterparts.

Julius Finance, a firm that specializes in CDO valuation using HPC technology, has called for the use of standardized house price appreciation scenarios in the valuation of complex financial products. In a press release on Tuesday, Joseph Cotton, the company’s CEO, stated: “For years, banks have been able to tranche up CDOs and sell the slices for more than the cost of the pie — with inconsistent valuation and ratings models not exactly standing in the way. Now, there is the possibility of the entire financial community playing that game on a vast scale with the taxpayer on the other end of the deal.”

I spoke with Cotton earlier in the week and asked him how he thinks the government should proceed. According to him, there needs to be a standard set of assumptions and scenarios used to value homes. This, he says, is one of the greatest sources of uncertainty in these products for investors, which allows sellers to game the system. “What you don’t want to see is a number of independent valuations of these products being done by different parties with very different assumptions,” says Cotton.

At this point no plan has been put forth by either the Treasury of the Fed to bring any rigorous technology to bear on the problem. According to Cotton, if the government is not careful, taxpayers will end up paying very high prices for these securities relative to what any other investor would be prepared to spend. But, he says, even though the financial instruments have become exceedingly complicated, these can be priced today with existing technology. Although some experts claim these products are impossible to value because of their complexity and lack of liquidity, Cotton believes that’s a fallacy.

He says all you really need is a significant sized cluster (1,000 nodes should be plenty), the loan database corresponding to the assets in question, and the software model that incorporates all the load attributes plus the structure of the deals. The model has to take into account home price appreciation/depreciation, prepayments, defaults, interest rates, and all cash flows as they get fed back into the various structured finance products associated with the mortgages. Software such as this exists today — it’s just not being applied at this scale. According to Cotton, the entire project could probably be accomplished for a few tens of millions of dollars — a small fraction of the $700 billion bailout.

Whether the Feds follow through with the rescue plan or not, it seems almost certain that the government is going to crack down on the rating services, either through regulation or by incorporating much of their function into the government itself. From my perspective, the latter path actually seems like the better way to go. Having the financial sector in charge of the asset ratings would be like analogous to the oil and gas industry controlling the global warming models. As one blog commentator put it: “The housing bubble was never about financing assets — it was all about financing financing.”

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