Modelling non-linear moving average processes using neural networks with error feedback: An application to implied volatility forecasting

DOI10.1016/S0165-1684(98)00202-3zbMATH Open0928.62100OpenAlexW1995474051MaRDI QIDQ1285706

A.-P. N. Refenes, A. N. Burgess

Publication date: 28 April 1999

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0165-1684(98)00202-3

zbMATH Keywords

neural networkstime series analysisvolatilitymodel identification

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Learning and adaptive systems in artificial intelligence (68T05)

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Efficient estimation of average derivatives in NPIV models: simulation comparisons of neural network estimators ⋮ A neural network-based ARMA model for fuzzy time series data

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