Our work aims to study the tail behaviour of weighted sums of the form $sum_{i=1}^{infty} X_{i} prod_{j=1}^{i}Y_{j}$, where $(X_{i}, Y_{i})$ are independent and identically distributed, with common joint distribution bivariate Sarmanov. Such quantities naturally arise in financial risk models. Each $X_{i}$ has a regularly varying tail. With sufficient conditions similar to those used by Denisov and Zwart (2007) imposed on these two sequences, and with certain suitably summable bounds similar to those proposed by Hazra and Maulik (2012), we explore the tail distribution of the random variable $sup_{n geq 1}sum_{i=1}^{n} X_i prod_{j=1}^{i}Y_{j}$. The sufficient conditions used will relax the moment conditions on the ${Y_{i}}$ sequence.
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