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Financial return series are often characterized by volatility clusters and a leptokurtic distribution. Many models that account for these properties exist, with the GARCH model proposed by Bollerslev (1986) being the most popular. This thesis explores an alternative model to capture the stochastic volatility in financial time series. The considered model is denoted the autoregressive gamma varianc
