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Informal Introduction to Stochastic Processes with Maple pp 215–250Cite as

Autoregressive Models

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Abstract

We investigate processes having the following generalized Markovian property: to forecast their future, we need only the last k consecutive observations; a more distant past becomes irrelevant. We also discuss the issue of parameter estimation (unique to this chapter). The resulting theory can be applied to model random daily fluctuations (but not systematic or seasonal trends) of a stock market and similar situations.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Brock University, St Catharines, Ontario, Canada

    Jan Vrbik

  2. Department of Computer Science, The University of Western Ontario, London, Ontario, Canada

    Paul Vrbik

Authors
  1. Jan Vrbik
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  2. Paul Vrbik
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Vrbik, J., Vrbik, P. (2013). Autoregressive Models. In: Informal Introduction to Stochastic Processes with Maple. Universitext. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4057-4_11

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