The PIN model and its extensions have proven challenging in their estimation, as they suffer from several computational problems. We set in this paper to address these computational issues by proposing the use of the expectation-conditional maximization (ECM) algorithm to estimate the various...

The purpose of this paper is to introduce the R package PINstimation. The package is designed for estimating, in a precise and fast way, the probability of informed trading models through the implementation of the main estimation methods suggested in the literature so far. The models covered are...

The multilayer probability of informed trading (MPIN) model, developed by Ersan (2016), releases the assumption of single type of information events in the original PIN model of Easley et al. (1996). Identification of the number of layers in a dataset is applied through a layer detection...

It is well documented that computational problems may lead to large biases in the estimation of probability of informed trading (PIN) models. While effective remedial solutions have been suggested for the case of original PIN model (Easley et al., 1996), computational problems for its most...

The estimation of the PIN model and its extensions has posed significant challenges due to various computational problems. To address these issues, we propose a novel estimation method called the Expectation-Conditional Maximization (ECM) algorithm, which can serve as an alternative to existing...

Consider a population of n players playing a variant of Myerson's network formation model. Each player simultaneously chooses k other players he would want to be connected to. If two players are in each other's choice set, a matching occurs. We call the outcome of the network formation model a...

The paper presents a large-population analog of fictitious play in which players learn from personal experience. In each period, only one player updates his beliefs about the strategy distribution in the population. Through analysis and examples, we justify the relevance of the single update...

We suggest a two-step approach in detecting HFT activity from order and trade data. While the first step focuses on multiple actions of an order submitter in low latency, the second searches for the surroundings of these orders to link related orders. On a sample of 2015 data from Borsa...

This paper aims to explore the daily and intraday herd behavior of various investor groups trading in an emerging equity market, Borsa Istanbul (BIST). We analyze a one-year tick-by-tick order and trade data of BIST 100 Index stocks and document differences in herding behavior of investor groups...

High-frequency trading (HFT) has been dominating the activity in developed financial markets in the last two decades. Despite its recent formation, the literature on the impacts of HFT on financial markets and participants is broad. However, there are ongoing debates and unanswered questions...