A novel fuzzy linear regression slidingwindow GARCH model for time-series forecasting
Generalized autoregressive conditional heteroskedasticity (GARCH) is one of the most popular models for time-series forecasting. The GARCH model uses a maximum likelihood method for parameter estimation. For the likelihood method to work, there should be a known and specific distribution. However, d...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG,
2020
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| Subjects: | |
| Online Access: | View Fulltext in Publisher View in Scopus |