Over-the-counter (OTC) derivatives are believed to have played a significant role in the 2008 financial crisis. In an effort to prevent another crisis in the future, the US Government signed new regulations into law in 2010 that require OTC derivatives to be traded through Central Clearing Parties (CCPs). Theoretically, these regulations should induce more stability in the trading network. The model we propose uses probabilistic methods, including Gibbs Sampling, to sample different possible OTC derivative trading networks based on the small amount of data available to a regulator. Then, these networks are tested for the relative stability of each type of network: a bilateral trading network without a CCP, one with a single CCP, and one with multiple CCPs.
Worcester Polytechnic Institute
Major Qualifying Project
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