In this article we address risk characteristics and rating of Collateralized Commodity Obligations (CCO), which are recently devised structured products similar to the Collateralized Debt Obligation (CDO). Commodities as an asset class have been in the spotlight of investors’ attention for the last decade. CCOs, which are fixed income instruments, provide fixed income investors an exposure to commodity markets. The underlying assets of a CCO are Commodity Trigger Swaps (CTS), similar to a Credit Default Swap, but instead of a default, a “trigger” occurs when a commodity price reaches a certain pre-set level. Rating agencies have used their CDO evaluators to rate CCOs; however, particular characteristics of commodity prices and an abundance of historical price data for commodities render such an approach questionable. Recently, S&P has withdrawn their ratings for CCOs, which may be linked to some concerns regarding their rating approach. We examine the historical performance of CCOs and propose two novel approaches to their rating. The first is a flexible multivariate parametric model for commodity prices: a mean-reversion model with correlated trends. The second approach is close in spirit to the historical simulation method for risk management and is based on the block bootstrap technique. We apply both approaches to an example of a CCO and compare the results to the ratings provided by the rating agencies. We find that: * Simulated ratings are sensitive to the model assumptions. * The default probabilities resulting from the agencies’ ratings underestimate both historically observed and bootstrap-simulated default probabilities. * The non-parametric approach most closely matches the historically observed probabilities of default. The results demonstrate the benefit of a data-driven, non-parametric modelling approach to rating CCOs.