A generalized bivariate mixture model for stock price volatility and trading volume

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Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity (2011, unknown): “See also Andersen (1996) and Liesenfeld (2001).”
Testing the Mixture of Distributions Hypothesis Using (2002, unknown): “Also, if the view of Liesenfeld (2001) holds and volatility is driven by a second latent variable (in addition to the information arrival rate) that does not affect volume, then INTRA is preferred over volume as it measures information provided by both latent variables(5).”
Local Polynomial Whittle Estimation of Perturbed Fractional Processes (2008, result): “The formulation in (2) allows the volatility to be a¤ected by both long and short-lived news impacts, which is also consistent with the ndings of Liesenfeld (2001).”
Duration, Volume and Volatility Impact of Trades (2005, background): “On days when not much information is available, trading is slow and there are only few price 2 See also Epps and Epps (1976), Tauchen and Pitts (1983), Andersen (1996) and Liesenfeld (2001).”
Estimation methods for stochastic volatility models: a survey (2004, methodology): “The SML estimator has been implemented to the empirical analysis of financial returns by, for example, Liesenfeld (1998), Liesenfeld and Jung (2000) and Liesenfeld (2001).”
Modelling financial transaction price movements: a dynamic integer count data model (2006, background): “13 See Andersen (1996) and Liesenfeld (1998, 2001) for extensions of the mixture models.”