%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