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...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Published: |
MDPI AG
2020
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082703763&doi=10.3390%2fapp10061949&partnerID=40&md5=6b7a451733670f0baef0cba392e3496d http://eprints.utp.edu.my/23358/ |
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