This paper reviews the up-to-date theoretical, empirical, and experimental literature related to the trading venue choice in the context of the fragmented equity markets. We provide a brief background on the history of trading fragmentation in the equity market and its determinants. We discuss...

The present paper is focused on the solution of optimal control problems such as optimal acquisition, optimal liquidation, and market making in relation to the high-frequency trading market. We have modeled optimal control problems with the price approximated by the diffusion process for the...

We examine the soundness of high-frequency trading (HFT) proxies that are widely defined on the limit order book (LOB) information. We use a unique TRTH (Thomson Reuters Tick History) millisecond time-stamped intraday trades and quotes dataset enriched with 10 levels of LOB depth messages for...

The recent emergence of COVID-19 and the subsequent short-selling restriction (SSR) imposed on some equity markets provide us with a unique framework to analyze the effects of this kind of measure on market quality in the context of increasingly automated equity markets. We contribute to the...

It is well known that intraday returns tend to reverse the following intraday period, conditional on excess buying pressure on the bid or ask side. This suggests that liquidity providers "overreact" to order imbalance (OIB) by initially altering quotes so much that a negative autocorrelation is...

The transaction-level analysis of security price changes by Madhavan, Richardson, and Roomans (1997, hereafter MRR) is a useful framework for financial analysis. The first-order Markov property of trading indicator variables is a critical assumption in the MRR model, which contradicts the...

In today's complex financial markets, "Algorithmic Trading" has become very important. The study delves into the amalgamation of four pivotal indicators - Relative Strength Index (RSI), Exponential Moving Average (EMA), Volume-Weighted Average Price (VWAP), and Moving Average...

Time-series data, which exhibit a low signal-to-noise ratio, non-stationarity, and non-linearity, are commonly seen in high-frequency stock trading, where the objective is to increase the likelihood of profit by taking advantage of tiny discrepancies in prices and trading on them quickly and in...

In this research, we attempted to fit a trading system based on polynomial moving regression bands (MRB) to Nasdaq100 stocks from 2017 till the end of March 2024. Since stocks movement does not follow a linear behavior, we used multiple degree polynomial regression models to identify the stocks'...

Using data from the Bucharest Stock Exchange, we examine the factors influencing the probability of informed trading (PIN) during February-October 2020, a COVID-19 pandemic period. Based on an unconditional quantile regression approach, we show that PIN exhibit asymmetric dependency with...