Using High-Frequency Data to Price Financial Assets: A Systematic Review Abstract

Using High-Frequency Data to Price Financial Assets: A Systematic Review Abstract

• Author
• Joao Vitor de Mattos
• Co-authors
• Eli Hadad Junior
• Abstract

• This study conducts a bibliometric analysis and systematic review of the empirical literature on using high-frequency data to price financial assets, examining 93 articles. The bibliometric analysis was developed by counting frequency and co-citations, while the systematic review encompassed qualitative analysis to establish a correlation between relevant themes still little explored. These articles were retrieved from the Scopus and Web of Science databases, and the software Biblioshiny and Rank Words were adopted to conduct the analysis and the review. In addition, the study verified the main laws of bibliometric analysis, such as Zipf (1949), Bradford (1934), and Lotka (1926). The research contributed to delving into modeling and predictability models to price financial assets based on high-frequency data and identify the main gaps to increase knowledge in the area.

• Keywords
• volatility; high-frequency data; forecast
• Subject Area
• Asset pricing, investments, and Derivatives

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