Abstract
In the present paper, a stochastic volatility model generated by a first-order induced Garima Markov sequence has been suggested for modeling financial time series. The statistical and probabilistic properties of the suggested model are studied, and the estimation of the model parameters is done using the generalized method of moments. Simulation studies and real data analysis aredone to demonstrate the applicability of the model. Also, the fit has been compared with an existing stochastic volatility model.
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