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,...

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...

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...

This paper demonstrates the multilayer structure of information in financial markets. While only 3.59% of 8,190 stock/quarter pairs have single information layer, 75% have two to five layers and 18% have six to eight layers. We develop a clustering algorithm which determines the number of...

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...

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,...

The market reaction speeds to the news flow are currently measured at the millisecond level in developed markets. We investigate, using a unique setting from Turkey, whether the market reaction speeds in less sophisticated markets are on par with those of developed markets. We find that market...

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...