By isolating credit as a distinct asset class, credit derivatives provide new vehicles for synthetically trading and transferring credit exposure of commercial real estate without buying or selling the physical assets. Recent developments of CMBS index-based synthetics, namely the CMBX, have allowed systematic market exposure to a basket of CMBS credit default swaps. The creation of these credit derivatives indices has enabled market participants to trade rating-specific risk, hedge against market-wide credit risk, and express a macro view within the CMBS sector. This thesis identifies the key underlying source of credit default risk as the commercial real estate market itself, and explores the concept of a CMBS default risk synthetic that is based on transaction-based commercial property price index movements. Such indices would allow investors to more precisely target and hedge the particular risk in their CMBS portfolios that is exposed to specific commercial real estate markets tracked by the indices. The thesis proposes a methodology for the new synthetic product to approximately replicate the credit loss behavior of specific rated tranches of a CMBS. This thesis utilizes Monte Carlo simulation to test the hedging performance of the proposed property price index-based synthetic, considering both cash flow correlation and hedge ratio analyses. The results reveal that the effectiveness of the hedge varies depending on the investor's horizon or degree of temporal precision the investor seeks in the hedge, as well as the target tranche rating. The hedge ratio is very dynamic throughout the life of the synthetic, suggesting that the investor buying the synthetic for hedging purposes would need to rebalance his position accordingly.