A New Test of Statistical Arbitrage with Applications to Credit Derivatives Markets

Abstract

This paper presents a new statistical arbitrage test which has lower Type I error and selects arbitrage opportunities with lower downside risk than existing alternatives. The test is applied to credit derivatives markets using strategies combining Credit Default Swaps (CDS) and Asset Swaps. Using four different databases (GFI, Reuters, CMA and JP Morgan) from 2005 to 2009, we find persistent mispricings between the CDS and Asset Swap spreads before and during the current financial crisis. These mispricings appear to offer arbitrage opportunities if a standard statistical arbitrage test is employed. However, our test shows that after considering funding and trading costs, these mispricings are unlikely to provide profitable arbitrage opportunities.