@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},
	}