Multi-Agent Financial Network (MAFN) Model of US Collateralized Debt Obligations (CDO): Regulatory Capital Arbitrage, Negative CDS Carry Trade and Systemic Risk Analysis

Abstract

A database driven multi-agent model has been developed with automated access to US bank level FDIC Call Reports which yield data on balance sheet and off balance sheet activity, respectively, in Residential Mortgage Backed Securities (RMBS) and Credit Default Swaps (CDS). The simultaneous accumulation of RMBS assets on US banks’ balance sheets and also large counterparty exposures from CDS positions characterized the $2 trillion Collateralized Debt Obligation (CDO) market. The latter imploded by end of 2007 with large scale systemic risk consequences. Based on US FDIC bank data, that could have been available to the regulator at the time, we investigate how a CDS negative carry trade combined with incentives provided by Basel II and its precursor in the US, the Joint Agencies Rule 66 Federal Regulation No. 56914 which became effective on January 1, 2002, on synthetic securitization and credit risk transfer (CRT), led to the unsustainable trends and systemic risk. The resultant market structure with heavy concentration in CDS activity involving 5 US banks can be shown to present too interconnected to fail systemic risk outcomes. The simulation package can generate the financial network of obligations of the US banks in the CDS market. We aim to show how such a multi-agent financial network (MAFN) model is well suited to monitor bank activity and to stress test policy for perverse incentives on an ongoing basis.

Keywords: Credit Risk Transfer, Synthetic Securitization, Perverse Incentives, Credit Default Swaps, Collateralized Debt Obligation, Agent Based Modelling

JEL Classification: G01, G21, G15, G17, G32