Applications of Computer Aided Time Series Modeling (Paperback)

From the contents: Part I: Introduction to state space modeling.- The Aoki state space algorithm and subspace methods.- A guide to state space modeling of multiple time series. Part II: Applications of state space algorithm.- Evaluating state space forecasts of soybean complex prices.- A state space model of monthly U.S. wheat prices.- Managing the herd: Price forecasts for California cattle production.- Labor market and cyclical fluctuations.- Modeling cointegrated processes by a vector-valued state space algorithm.- A method for identification of combined deterministic stochastic systems.- Competing exchange rate models.- Application of state-space models to ocean climate variability in the Northeast Pacific ocean. Part III: Applications of Neural Networks.- On the equivalence between ARMA models and simple recurrent neural networks.- Forecasting stock market indices with recurrent neural networks.