Systematic patterns before and after large price changes: evidence from high frequency data from the Paris Bourse

2003 ◽  
Vol 22 (6-7) ◽  
pp. 533-549 ◽  
Author(s):  
Foort Hamelink
Keyword(s):  
High Frequency ◽  
High Frequency Data ◽  
Frequency Data ◽  
Price Changes ◽  
Before And After ◽  
Paris Bourse

The intraday effect of nature disaster and production safety accident announcement based on high-frequency data from China’s stock markets

2015 ◽  
Vol 5 (3) ◽  
pp. 277-302 ◽  
Author(s):  
Ping Li ◽  
Huailin Tang ◽  
Jingchi Liao
Keyword(s):  
Stock Markets ◽  
High Frequency ◽  
Stock Price ◽  
Abnormal Returns ◽  
High Frequency Data ◽  
Frequency Data ◽  
Content Type ◽  
Production Safety ◽  
Before And After ◽  
Safety Accident

Purpose – The purpose of this paper is to investigate the intraday effect of nature disaster (external inevitable factor) and production safety accident (PSA) (internal factor regarding management level) announcement on stock price in China’s stock markets. Design/methodology/approach – Using high-frequency data, this study adopts event study method to examine the intraday abnormal returns as well as the volatility of stock price before and after the announcement of nature disaster and PSA. Findings – First, both nature disaster announcement and PSA announcement produce negative effects on stock returns. However, there are some differences in effects between the different types of announcement. Second, it is just within the event day (announcement day if trading day, otherwise the first trading day after announcement) that the volatility of stock price is distinctly increased by the two kinds of announcement. Third, there are some differences in the impacts of nature disaster announcement on firms in different industries. Finally, there are also some differences observed between the impacts of PSA announcement on chemical firms and other firms. Originality/value – It is the first time that using high-frequency data to analyze the intraday impact of nature disaster and PSA announcement on stock short price behavior. The results can help us to understand the role of market microstructure playing in the process of stock price formation, especially the stock price movements before and after disaster and accident announcement and the sensitivity to the announcement. The empirical results have important implications for investors when making trading decisions, and for market regulators when setting trading rules.

Using Mutual Information to Analyse Serial Dependence

2021 ◽  
pp. 411-427
Author(s):  
Andreia Dionísio ◽  
Paulo Ferreira
Keyword(s):  
Mutual Information ◽  
Stock Markets ◽  
High Frequency ◽  
Nonlinear Dependence ◽  
High Frequency Data ◽  
Frequency Data ◽  
Serial Dependence ◽  
Very High Frequency ◽  
Global Correlation ◽  
Before And After

The main objective of this research is to analyse the serial dependence of high frequency data for G7 stock indices. The authors use two different periodicities, and with linear and nonlinear approaches, they evaluate the stock markets' behaviour and conclude about the higher or lower dependence levels of the stock markets in the periods before and after the COVID-19 pandemic declaration. They use mutual information and the global correlation coefficient based on that measure, comparing results with the linear coefficient. The results are clear, showing that nonlinear dependence exists and could be an important factor in terms of historical information, especially for very high frequency data. Results are mixed in regard to the effect of the pandemic declaration in the dependence of stock markets.

Efficient Estimation of Volatility using High Frequency Data

2002 ◽  
Author(s):  
Gilles O. Zumbach ◽  
Fulvio Corsi ◽  
Adrian Trapletti
Keyword(s):  
High Frequency ◽  
Efficient Estimation ◽  
High Frequency Data ◽  
Frequency Data

Forecasting Exchange Rate Realized Volatility Through Decomposition Using High-Frequency Data

2017 ◽  
Author(s):  
Rim mname Lamouchi ◽  
Russell mname Davidson ◽  
Ibrahim mname Fatnassi ◽  
Abderazak Ben mname Maatoug
Keyword(s):  
Exchange Rate ◽  
High Frequency ◽  
Realized Volatility ◽  
High Frequency Data ◽  
Frequency Data

Stochastic Volatility: A Tale of Co-Jumps, Non-Normality, GMM and High Frequency Data

2019 ◽  
Author(s):  
Christian-Oliver Ewald ◽  
Yihan Zou
Keyword(s):  
Stochastic Volatility ◽  
High Frequency ◽  
High Frequency Data ◽  
Frequency Data
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