Abstract
In this article, normal inverse Gaussian (NIG) autoregressive model is introduced. The parameters of the model are estimated using expectation maximization (EM) algorithm. The efficacy of the EM algorithm is shown using simulated and real-world financial data. It is shown that NIG autoregressive model fit very well on the considered financial data and hence could be useful in modelling of various real-life time-series data.
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More From: International Journal of Advances in Engineering Sciences and Applied Mathematics
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