Package: InfoTrad 1.2

InfoTrad: Calculates the Probability of Informed Trading (PIN)

Estimates the probability of informed trading (PIN) initially introduced by Easley et. al. (1996) <doi:10.1111/j.1540-6261.1996.tb04074.x> . Contribution of the package is that it uses likelihood factorizations of Easley et. al. (2010) <doi:10.1017/S0022109010000074> (EHO factorization) and Lin and Ke (2011) <doi:10.1016/j.finmar.2011.03.001> (LK factorization). Moreover, the package uses different estimation algorithms. Specifically, the grid-search algorithm proposed by Yan and Zhang (2012) <doi:10.1016/j.jbankfin.2011.08.003> , hierarchical agglomerative clustering approach proposed by Gan et. al. (2015) <doi:10.1080/14697688.2015.1023336> and later extended by Ersan and Alici (2016) <doi:10.1016/j.intfin.2016.04.001> .

Authors:Duygu Celik and Murat Tinic

# Install 'InfoTrad' in R:

install.packages('InfoTrad', repos = c('https://murattinic.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

Last updated 7 years agofrom:9d42ebdec9. Checks:OK: 7. Indexed: yes.

Dependencies:nloptr

Help page	Topics
Calculates the Probability of Informed Trading (PIN)	InfoTrad-package InfoTrad
Ersan and Alici (2016) Cluster analysis with the altered steps.	EA EA_class print print.EA_class
Likelihood factorization of Easley et. al. (2010) - EHO Factorization	EHO
GAN et al.(2015) Clustering based PIN Estimates	GAN GAN_class print.GAN_class
Likelihood factorization of Lin and Ke (2011) - LK Factorization	LK
Yan and Zhang (2012) Grid-Search based PIN Estimates	print.YZ_class YZ YZ_class