dailytrades

An example dataset representative of quarterly data containing
the aggregate numbers of buyer-initiated and seller-initiated trades for
each trading day.

datasets

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.

Montasser Ghachem

PINstimation

Estimation of the Probability of Informed Trading

Oguz Ersan

dailytrades function

A data frame with <code>60</code> observations and <code>2</code> variables:<ul>
<li><code>B</code>: total number of buyer-initiated trades.</li>
<li><code>S</code>: total number of seller-initiated trades.</li>
</ul>

dailytrades: Example of quarterly data

Description

Usage

Arguments

Format