In this chapter, we discuss dynamic models for discrete-valued data and quote processes. As illustrated in Chap. 4, the time series of the number of events in a given time interval yields a counting process and provides an alternative way to characterize the underlying point process. Section 13.1 presents a class of univariate autoregressive models for count data based on dynamic parameterizations of the conditional mean function in a Poisson distribution. Moreover, we discuss extensions thereof, such as the Negative Binomial distribution and Double Poisson distribution.
CITATION STYLE
Hautsch, N. (2012). Autoregressive Discrete Processes and Quote Dynamics. In Econometrics of Financial High-Frequency Data (pp. 331–355). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-21925-2_13
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