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What is High-Frequent Data

Handbook of Research on Financial Management During Economic Downturn and Recovery
Type of data which, associated with financial time series analysis, means that data is intraday.
Published in Chapter:
Using Mutual Information to Analyse Serial Dependence: The Effects of COVID-19
Andreia Dionísio (CEFAGE, IIFA, Universidade de Évora, Portugal) and Paulo Ferreira (Polytechnic Institute of Portalegre, Portugal)
DOI: 10.4018/978-1-7998-6643-5.ch023
Abstract
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.
Full Text Chapter Download: US $37.50 Add to Cart
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How Does COVID-19 Impact the Efficiency of the Chinese Stock Market?: A Sliding Windows Approach
Type of data which, associated with financial time series analysis, means that data is intraday.
Full Text Chapter Download: US $37.50 Add to Cart
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