Abstract
In this paper we deal with the problem of visualizing and exploring specific time series such as high-frequency financial data. These data present unique features, absent in classical time series, which involve the necessity of searching and analysing an aggregate behaviour. Therefore, we define peculiar aggregated time series called beanplot time series. We show the advantages of using them instead of scalar time series when the data have a complex structure. Furthermore, we underline the interpretative proprieties of beanplot time series by comparing different types of aggregated time series. In particular, with simulated and real examples, we illustrate the different statistical performances of beanplot time series respect to boxplot time series.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Arroyo, J., & Maté C. (2009). Forecasting histogram time series with k-nearest neighbours methods. International Journal of Forecasting, 25, 192–207.
Benjamini, Y. (1988). Opening the box of the box plot. The American Statistician, 42, 257–262.
Engle, R. F., & Russell, J. (in press). Analysis of high frequency and transaction data. In Handbook of financial econometrics. North-Holland.
Fryer, M. J. (1977). A review of some non-parametric methods of density estimation. Journal of the Institute of Mathematics Applications, 20, 335–354.
Kampstra, P. (2008). Beanplot: A boxplot alternative for visual comparison of distributions. Journal of Statistical Software, 28.
R Development Core Team. (2009). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.
Silverman, B. W. (1986). Density estimation for statistics and data analysis. London: Chapman and Hall.
Sheather, S. J., & Jones, M. C. (1991). A reliable data-based bandwidth selection method for kernel density estimation. Journal of the Royal Statistical Society. Series B, 53, 683–690.
Tukey, J. W. (1977). Exploratory data analysis. Reading: Addison-Wesley.
Yan, B., & Zivot G. (2003). Analysis of high-frequency financial data with S-PLUS. Working Paper.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Drago, C., Scepi, G. (2011). Visualizing and Exploring High Frequency Financial Data: Beanplot Time Series. In: Ingrassia, S., Rocci, R., Vichi, M. (eds) New Perspectives in Statistical Modeling and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11363-5_32
Download citation
DOI: https://doi.org/10.1007/978-3-642-11363-5_32
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11362-8
Online ISBN: 978-3-642-11363-5
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)