PIN estimation resultsSource:
logical) takes the value
TRUEwhen the estimation has succeeded,
character) contains an error message if the
PINestimation has failed, and is empty otherwise.
numeric) returns the number of initial parameter sets at which the likelihood maximization converged.
character) returns the algorithm used to determine the set of initial parameter sets for the maximum likelihood estimation. It takes one of the following values:
"YZ": Yan and Zhang (2012)
"GWJ": Gan, Wei and Johnstone (2015)
"YZ*": Yan and Zhang (2012) as modified by Ersan and Alici (2016)
"EA": Ersan and Alici (2016)
"CUSTOM": Custom initial parameter sets
character) returns the factorization of the
PINlikelihood function as used in the maximum likelihood estimation. It takes one of the following values:
"NONE": No factorization
"EHO": Easley, Hvidkjaer and O'Hara (2010)
"LK": Lin and Ke (2011)
"E": Ersan (2016)
list) returns the list of the maximum likelihood estimates (\(\alpha\), \(\delta\), \(\mu\), \(\epsilon\)b, \(\epsilon\)s)
numeric) returns the value of (the factorization of) the likelihood function evaluated at the optimal set of parameters.
numeric) returns the value of the probability of informed trading.
list) returns a list containing a decomposition of
PINinto good-news, and bad-news
PINcomponents. The decomposition has been suggested in Brennan et al. (2016) . The list has two elements:
pinBare the good-news, and bad-news components of
dataframe) returns the dataset of buys and sells used in the maximum likelihood estimation of the PIN model.
dataframe) returns the initial parameter sets used in the maximum likelihood estimation of the PIN model.
dataframe) returns a dataframe containing the estimated parameters by the
MLEmethod for each initial parameter set.
numeric) returns the running time of the estimation of the
PINmodel in seconds.