BSfrequent

A matrix containing three months of synthetic daily buys and sells data representing a frequently traded stock.

datasets

Utilities for fast and stable estimation of the probability of
informed trading (PIN) in the model introduced by Easley et al. (2002)
<DOI:10.1111/1540-6261.00493> are implemented. Since the basic model developed
by Easley et al. (1996) <DOI:10.1111/j.1540-6261.1996.tb04074.x> is nested in the
former due to equating the intensity of uninformed buys and sells, functions
can also be applied to this simpler model structure, if needed.
State-of-the-art factorization of the model likelihood function as well as
most recent algorithms for generating initial values for optimization routines are implemented.
In total, two likelihood factorizations and three methodologies for
starting values are included.
Furthermore, functions for simulating datasets of daily aggregated buys and sells,
calculating confidence intervals for the probability of informed trading and posterior probabilities
of trading days' conditions are available.

Andreas Recktenwald

pinbasic

Fast and Stable Estimation of the Probability of Informed
Trading (PIN)

BSfrequent function

A matrix with 60 rows and 2 variables:<dl class="dl-horizontal">
 <dt>Buys</dt><dd>daily buys</dd>
 <dt>Sells</dt><dd>daily sells</dd>
</dl>

Format

Daily Buys and Sells — BSfrequent

A matrix with 60 rows and 2 variables:<dl class='dl-horizontal'>
 <dt>Buys</dt><dd>daily buys</dd>
 <dt>Sells</dt><dd>daily sells</dd>
</dl>

BSfrequent: Daily Buys and Sells

Description

Usage

Arguments

Format