We put forward two jump-robust estimators of integrated volatility, namely realized information variation (RIV) and realized information power variation (RIPV). The "information" here refers to the difference between two-grid of ranges in high-frequency intervals, which preserves continuous...

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...

The paper studies methods of dynamic estimation of volatility for financial time series. We suggest to estimate the volatility as the implied volatility inferred from some artificial 'dynamically purified' price process that in theory allows to eliminate the impact of the stock price movements....

We construct new features based on order book data and separate them into three groups, e.g., time-insensitive features, time-sensitive features and cointegration features. For time-insensitive features, we applied serval transformation on imbalance in different levels, and some other features...

Inspired by recent advances in the deep learning literature, this article introduces a novel hybrid anomaly detection framework specifically designed for limit order book (LOB) data. A modified Transformer autoencoder architecture is proposed to learn rich temporal LOB subsequence...

We propose a network model with communities to study the stock co-jump dependency. To estimate the community structure, we extend the SCORE algorithm in Jin (2015) and develop a Spectral Clustering On Ratios-of-Eigenvectors for networks with Dependent Multivariate Poisson edges (SCORE-DMP)...

We use deep neural networks to estimate an asset pricing model for individual stock returns that takes advantage of the vast amount of conditioning information, while keeping a fully flexible form and accounting for time-variation. The key innovations are to use the fundamental no-arbitrage...

This article provides an overview of existing community-contributed commands for executing event studies. I assess which command(s) could have been used to conduct event studies that have appeared in the past ten years in three leading accounting, finance and management journals. The older...

We study financial volatility during the Global Financial Crisis and use the largest volatility shocks to identify major events during the crisis. Our analysis makes extensive use of high-frequency financial data to model volatility and to determine the timing within the day when the largest...