Dynamic Spectrum Sharing (DSS) aims to provide opportunistic access to under-utilized spectrum in cellular networks for secondary network operators. In this paper we propose an algorithm using stochastic and optimization models to borrow spectrum bandwidths under the assumption that more resources exist for secondary access than the secondary network demand by considering a merchant mode. The main aim of the paper is to address the problem of spectrum borrowing in DSS environments, where a secondary network operator aims to borrow the required spectrum from multiple primary network operators to achieve a maximum profit under specific grade of service (GoS) and budget restriction. We assume that the primary network operators offer spectrum access opportunities with variable number of channels (contiguous and/or non- contiguous) at variable prices. Results obtained are then compared with results derived from a heuristic algorithm in which spectrum borrowing are random. Comparisons showed that the gain in the results obtained from our proposed stochastic-optimization framework is significantly higher than random counterpart.