%0 Journal Article %A Maria C. Mariani and Md Al Masum Bhuiyan and Osei K. Tweneboah and Hector G. Huizar %D 2017 %J International Journal of Mathematical and Computational Sciences %B World Academy of Science, Engineering and Technology %I Open Science Index 130, 2017 %T Forecasting the Volatility of Geophysical Time Series with Stochastic Volatility Models %U https://publications.waset.org/pdf/10007933 %V 130 %X This work is devoted to the study of modeling geophysical time series. A stochastic technique with time-varying parameters is used to forecast the volatility of data arising in geophysics. In this study, the volatility is defined as a logarithmic first-order autoregressive process. We observe that the inclusion of log-volatility into the time-varying parameter estimation significantly improves forecasting which is facilitated via maximum likelihood estimation. This allows us to conclude that the estimation algorithm for the corresponding one-step-ahead suggested volatility (with ±2 standard prediction errors) is very feasible since it possesses good convergence properties. %P 444 - 450