Princeton University researchers report that sellers of financial derivatives could intentionally include pieces of bad risk that buyers couldn't detect with even the most powerful computers. The research focused on collateralized debt obligations (CDOs), an investment tool that combines multiple mortgages with the promise of spreading out and lowering the risk of default. The researchers explored what would happen if a seller knew some mortgages were bad and structured a package of CDOs that benefited the seller. They found that the manipulation could be impossible for buyers to detect either at the time of sale or when the derivative loses money.
The study was conducted by Sanjeev Arora, director of Princeton's Center for Computational Intractability; his colleague Boaz Barak; economics professor Markus Brunnermeier; and computer science graduate student Rong Ge.
The researchers say their study indicates that mathematical models used for risk analysis at financial firms may be problematic. "We are cautioning that even if you have the right model it's not easy to price derivatives," Arora says. "Making the models more complicated will not make these effects go away, even for computationally sophisticated."
Arora says the problem comes from asymmetric information between buyers and sellers, and goes against conventional wisdom of economic theory, which states that derivatives reduce the negative effects of unequal information. "We stress that certain derivative securities introduce additional complexity and thus a new layer of asymmetric information that can be so severe it overturns the initial advantage," Brunnermeier says.
From Princeton Engineering News
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