Prediction of nonlinear nonstationary time series data using a digital filter and support vector regression
Volatility is a key parameter when measuring the size of the errors made in modelling returns and other nonlinear nonstationary time series data. The Autoregressive Integrated Moving- Average (ARIMA) model is a linear process in time series; whilst in the nonlinear system, the Generalised Autoregres...
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Imperial College London
2013
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.650612 |