High frequency data in finance typically denote observations taken daily or at a finer time scale. These data become available primarily because of advances in information technology and the trend of moving toward electronic trading. They have attracted much attention in recent years because the data are important in empirical study of market microstructure and high frequency trading. Extreme events such as the Flash Crash of May 6, 2010 highlight the need for a deeper understanding of market operation in real time. As a matter of fact, financial markets have witnessed ever increasing interest in direct market access (DMA) in recent years.
The ultimate high frequency data in finance are the transaction-by-transaction or tick-by-tick data in security markets. Here, time is often measured in seconds or fractions of a second. The Trades and Quotes (TAQ) database of the New York Stock Exchange (NYSE) contains all quotes and transactions of equities reported on the Consolidated Tape, which includes transactions on the NYSE, AMEX, NASDAQ, and the regional exchanges. For options data, see the Web site of Chicago Board Options Exchange (CBOE). Transactions data for many other securities and markets, both domestic and foreign, are continuously collected and processed. Wood (2000) provides some historical perspective of high frequency financial study.
High frequency financial data are important ...
Get An Introduction to Analysis of Financial Data with R now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.