We focus on the existence of bubbles in fan tokens, utilizing the Supremum Augmented Dickey-Fuller (SADF) and Generalized Supremum Augmented Dickey-Fuller (GSADF) tests. We use daily closing prices of the top 20 fan tokens according to their market capitalization, along with Bitcoin, Ethereum,...

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...

Using earthquake exposure during pregnancy as a proxy for in utero insult, we examine the impact of prenatal stress on investment decisions during adulthood. We find that investors exposed to major earthquakes in utero participate less in the stock market and hold less diversified portfolios,...

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...

Ghost liquidity (GL) in fragmented markets, is defined as the observable but not accessible liquidity that is mostly associated with the rapid cancellations of multiple orders in different venues when an order is executed in a venue. We track the prevalence and the impacts of GL in the case of a...

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 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 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...