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This paper focuses on the construction of an optimized financial transmission rights (FTR) or congestion revenue rights portfolio for an FTR market participant given his assessment of the frequency and economic impacts of binding constraints in the transmission network. We overcome the data handling and heavy computing demands of locational marginal price (LMP)-difference-based methods for FTR selection by recasting the problem into one that focuses on the underlying product of “binding constraints”, which are physically observable phenomena, based on the mathematical insights into the structural characteristics of the model used for the clearing of the hourly day-ahead markets. Differentials in the LMPs are due to system congestion and so are merely manifestations of binding constraints in the transmission network. In addition, we exploit extensively the salient topological characteristics of large-scale interconnections. The market participant specifies the subset of “focus” constraints and the position he is willing to take on them. Our approach builds on the mathematical insights and topological characteristics with the effective deployment of the orthogonal matching pursuit algorithm to construct the optimized FTR portfolio characterized by the minimum number of node pairs for the specification of the FTR elements. We apply the proposed approach to a test system based on the PJM ISO network and markets to illustrate its capabilities for solving the FTR market participant's problem in realistic large-scale systems.