Originally developed as a statistical tool for empirical research in accounting and finance, event studies have since migrated to other disciplines as well, including economics, history, law, management, marketing, and political science. Despite the elegant simplicity of a standard event study,...

The objective of this paper is to examine the impact of demutualization upon the performance of stock exchanges' in terms of their liquidity as per the share turnover velocity and the returns that are generated from the broad indexes. The impact of demutualization has been examined upon a global...

The aim of this comparative research is to recognize and assess intra-day seasonality of investors activity on a stock market using high-frequency data. Three indicators of intra-day investors activity based on different market characteristics are utilized: (1) hourly aggregated trading volume...

A Hidden Markov Model (HMM) is used to model the VIX (the Cboe Volatility Index). A 4- state Gaussian mixture is fitted to the VIX price history from 1990 to 2022. Using a growing window of training data, the price of the S&P500 is predicted and two trading algorithms are presented, based on the...

This paper explores the utilization of text data as a new α return resource for individual stock investment. In particular, we propose a new construction scheme of a polarity dictionary based on ChatGPT, a state-of-the-art language model, which is also directly used for sentiment analysis. Our...

We estimate a general microstructure model of the transitory and permanent impact of order flow on stock prices. Jumps are detected in both the transaction price (observation equation) and fundamental value (state equation). The model's parameters and variances are updated in real time. Prices...

Finding a precise variance-covariance matrix is the building block of empirical finance. While microstructure-noise-robust methods for realized volatility are in the mainstream of financial econometrics, little if any attention has been devoted to estimating a noise-free realized covariance for...

This paper introduces a new class of stochastic volatility models which allows for stochastic volatility of volatility (SVV): Volatility modulated non-Gaussian Ornstein-Uhlenbeck (VMOU) processes. Various probabilistic properties of (integrated) VMOU processes are presented. Further we study the...

The objective of this paper is to provide a practical tool for stock price evaluation and forecasting under Extreme Value Theory (EVT). Three existing models are reviewed; these models include: Mordern Portfolio Theory, Black-Scholes, and Jarrow-Rudd models. It was found that these models may not...