NDLI: Econometric analysis of high frequency data

Content Provider	Springer Nature Link
Author	Herwartz, Helmut
Copyright Year	2006
Abstract	Owing to enormous advances in data acquisition and processing technology the study of high (or ultra) frequency data has become an important area of econometrics. At least three avenues of econometric methods have been followed to analyze high frequency financial data: Models in tick time ignoring the time dimension of sampling, duration models specifying the time span between transactions and, finally, fixed time interval techniques. Starting from the strong assumption that quotes are irregularly generated from an underlying exogeneous arrival process, fixed interval models promise feasibility of familiar time series techniques. Moreover, fixed interval analysis is a natural means to investigate multivariate dynamics. In particular, models of price discovery are implemented in this venue of high frequency econometrics. Recently, a sound statistical theory of ‘realized volatility’ has been developed. In this framework high frequency log price changes are seen as a means to observe volatility at some lower frequency.
Starting Page	89
Ending Page	104
Page Count	16
File Format	PDF
ISSN	00026018
Journal	AStA Advances in Statistical Analysis
Volume Number	90
Issue Number	1
e-ISSN	16140176
Language	English
Publisher	Springer-Verlag
Publisher Date	2006-01-01
Publisher Place	Berlin, Heidelberg
Access Restriction	Subscribed
Subject Keyword	High frequency data price discovery realized volatility. JEL G15, C22 Probability Theory and Stochastic Processes Statistics Statistics for Business/Economics/Mathematical Finance/Insurance Econometrics
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability

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