PINstimation0.1.2 package

Estimation of the Probability of Informed Trading

adjpin

Estimation of adjusted PIN model

data.series-class

List of dataset objects

dataset-class

Simulated data object

detecting-layers

Layer detection in trade-data

estimate.adjpin-class

AdjPIN estimation results

estimate.mpin-class

MPIN estimation results

estimate.mpin.ecm-class

MPIN estimation results (ECM)

estimate.pin-class

PIN estimation results

estimate.vpin-class

VPIN estimation results

factorizations

Factorizations of the different PIN likelihood functions

generatedata_adjpin

Simulation of AdjPIN model data.

generatedata_mpin

Simulation of MPIN model data

get_posteriors

Posterior probabilities for PIN and MPIN estimates

initials_adjpin

AdjPIN initial parameter sets of Ersan & Ghachem (2022b)

initials_adjpin_cl

AdjPIN initial parameter sets of Cheng and Lai (2021)

initials_adjpin_rnd

AdjPIN random initial sets

initials_mpin

MPIN initial parameter sets of Ersan (2016)

initials_pin_ea

Initial parameter sets of Ersan & Alici (2016)

initials_pin_gwj

Initial parameter set of Gan et al.(2015)

initials_pin_yz

Initial parameter sets of Yan and Zhang (2012)

mpin_ecm

MPIN model estimation via an ECM algorithm

mpin_ml

MPIN model estimation via standard ML methods

pin

PIN estimation - custom initial parameter sets

pin_bayes

PIN estimation - Bayesian approach

pin_ea

PIN estimation - initial parameter sets of Ersan & Alici (2016)

pin_gwj

PIN estimation - initial parameter set of Gan et al. (2015)

pin_yz

PIN estimation - initial parameter sets of Yan & Zhang (2012)

PINstimation-package

An R package for estimating the probability of informed trading

set_display_digits

Package-wide number of digits

trade_classification

Classification and aggregation of high-frequency data

vpin

Estimation of Volume-Synchronized PIN model

A comprehensive bundle of utilities for the estimation of probability of informed trading models: original PIN in Easley and O'Hara (1992) and Easley et al. (1996); Multilayer PIN (MPIN) in Ersan (2016); Adjusted PIN (AdjPIN) in Duarte and Young (2009); and volume-synchronized PIN (VPIN) in Easley et al. (2011, 2012). Implementations of various estimation methods suggested in the literature are included. Additional compelling features comprise posterior probabilities, an implementation of an expectation-maximization (EM) algorithm, and PIN decomposition into layers, and into bad/good components. Versatile data simulation tools, and trade classification algorithms are among the supplementary utilities. The package provides fast, compact, and precise utilities to tackle the sophisticated, error-prone, and time-consuming estimation procedure of informed trading, and this solely using the raw trade-level data.

  • Maintainer: Montasser Ghachem
  • License: GPL (>= 3)
  • Last published: 2023-03-20