PINstimation: An R Package for Estimating Probability of Informed Trading Models

The purpose of this paper is to introduce the R package PINstimation. The package is designed for fast and accurate estimation of the probability of informed trading models through the implementation of well-established estimation methods. The models covered are the original PIN model (Easley and O’Hara 1992; Easley et al. 1996), the multilayer PIN model (Ersan 2016), the adjusted PIN model (Duarte and Young 2009), and the volume- synchronized PIN (Easley et al. 2011, 2012). These core functionalities of the package are supplemented with utilities for data simulation, aggregation and classification tools. In addition to a detailed overview of the package functions, we provide a brief theoretical review of the main methods implemented in the package. Further, we provide examples of use of the package on trade-level data for 58 Swedish stocks, and report straightforward, comparative and intriguing findings on informed trading. These examples aim to highlight the capabilities of the package in tackling relevant research questions and illustrate the wide usage possibilities of PINstimation for both academics and practitioners.

Montasser Ghachem (Department of Economics, Stockholm University) , Oguz Ersan (International Trade and Finance Department, Kadir Has University)
2023-11-01

0.1 Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at RJ-2023-044.zip

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For attribution, please cite this work as

Ghachem & Ersan, "PINstimation: An R Package for Estimating Probability of Informed Trading Models", The R Journal, 2023

BibTeX citation

@article{RJ-2023-044,
  author = {Ghachem, Montasser and Ersan, Oguz},
  title = {PINstimation: An R Package for Estimating Probability of Informed Trading Models},
  journal = {The R Journal},
  year = {2023},
  note = {https://doi.org/10.32614/RJ-2023-044},
  doi = {10.32614/RJ-2023-044},
  volume = {15},
  issue = {2},
  issn = {2073-4859},
  pages = {145-168}
}

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