Forecasting the Volatility of Geophysical Time Series with Stochastic Volatility Models
| Main Authors: | Maria C. Mariani, Md Al Masum Bhuiyan, Osei K. Tweneboah, Hector G. Huizar |
|---|---|
| Format: | Article |
| Bahasa: | eng |
| Terbitan: |
, 2017
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/1132226 |
Daftar Isi:
- 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.