This paper looks at some technical issues when using CDS data, and if these are incorporated, the analysis or regression results are likely to benefit. The paper endorses the use of stochastic recovery in CDS models when estimating probability of default (PD) and suggests that stochastic recovery may be a better harbinger of distress signals than fixed recovery. Similarly, PDs derived from CDS data are risk-neutral and may need to be adjusted when extrapolating to real world balance sheet and empirical data (e.g. estimating banks losses, etc). Another technical issue pertains to regressions trying to explain CDS spreads of sovereigns in peripheral Europe - the model specification should be cognizant of the under-collateralization aspects in the overall OTC derivatives market. One of the biggest drivers of CDS spreads in the region has been the CVA teams of the large banks that hedge their exposure stemming from derivative receivables due to non-posting of collateral by many sovereigns (and related entities).