@article{(Open Science Index):https://publications.waset.org/pdf/10007933, title = {Forecasting the Volatility of Geophysical Time Series with Stochastic Volatility Models}, author = {Maria C. Mariani and Md Al Masum Bhuiyan and Osei K. Tweneboah and Hector G. Huizar}, country = {}, institution = {}, abstract = {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.}, journal = {International Journal of Mathematical and Computational Sciences}, volume = {11}, number = {10}, year = {2017}, pages = {444 - 450}, ee = {https://publications.waset.org/pdf/10007933}, url = {https://publications.waset.org/vol/130}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 130, 2017}, }