Analyzing the credit default swap market using cartesian genetic programming

Abstract

The credit default swap has become well-known as one of the causes of the 2007-2010 credit crisis but more research is vitally needed to analyze and define its impact more precisely and help the financial market transparency. This paper uses cartesian genetic programming as a discovery tool for finding the relationship between credit default swap spreads and debts and studying the arbitrage channel. (Arbitrage is the practice of taking advantage of a price difference between markets.) To our knowledge this work is the first attempt toward studying the credit default swap market via an evolutionary process and our results prove that cartesian genetic programming is human competitive and it has the potential to become a regression discovery tool in credit default swap market. © 2010 Springer-Verlag.