Abstract
Event processing is playing a progressively more important part in building inventiveness in the application that can instantaneously answer to the business acute event. Several technologies have been anticipated in recent years, for example, event processing and data streams. Live Data Analysis [1] had bagged lots of investigation attention nowadays, and an ample range of novel techniques and applications have been evolved based on business needs. In financial data analysis [2] however, analysts still generally are dependent on statistical performance parameters blended with conventional line charts to facilitate the consideration of assets and to make decisions. For the evolution of better trading techniques, a live data or event stream is mandatory requirement asset which is highly costly. The proposed technique that creates a live stream of data from historical data sets eliminating the inadequacies, offering a complete ease of working with live streams. This technique can be further used for the creation of a new trend of data analysis [3] and visualization mechanisms [4, 5].
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hartmut Ziegler, Tilo Nietzschmann, Daniel A. Keim.: Visual Analytics on the Financial Market: Pixel-based Analysis and Comparison of Long-Term Investments: 12th International Conference Information Visualisation, 2008.
Erographics Digital Library, http://diglib.eg.org.
Allen D. Malony Daniel, A. Reedy: An Integrated Performance Data Collection, Analysis, and Visualization System: NTRS, Center for Supercomputing Research and Development University of Illinois Urbana., 1998.
Havre, S., Hetzler, E. G., Nowell L.T.: “ThemeRiver: Visualizing Theme Changes over Time”, Proceedings of the Infovis 2000, pp. 115–124.
Dwyer T., Gallagher D.R.: Visualising Changes in Fund Manager Holdings in Two and a Half-dimensions. Information Visualization 3, 4 (2004), 227–244.
TrueFX by Integral, https://www.truefx.com.
Deboeck G. J., Kohonen T. K., Visual Explorations in Finance with Self Organizing Maps. Springer-Verlag New York, Inc., Secaucus, NJ, USA, 1998.
David Leinweber: If You Had Everything Computationally, Where Would You Put It, Financially?: Oreially Money Tech Conference, New York, 2008.
Vizualization Group, http://www-vis.lbl.gov/.
Hochheiser, H.: Interactive Graphical Querying of Time Series and Linear Sequence Data Sets Ph.D. Dissertation, University of Maryland, Dept. of Computer Science, May 2003.
The Odysci Academic Search System, academic.odysci.com.
The Science Search Engine, http://research.omicsgroup.org.
Lepmodas Fegaras.: Data stream management for historical XML data.: International Conference on Management of Data, ACM SIGMOD, 2004.
Ziegler, Hartmut, Nietzschmann, Tilo, Keim, Daniel A., Relevance driven visualization of financial applications.
Acknowledgements
It is our responsibility to thank our Advisor Dr. V. Srikanth, Director, Citi Bank, U.K. for his valuable advice in this area. Thanks to our Technical Supporter Mr. Vamsi Nadella, Grad Student, University of Georgia, Athens, USA. Thanks to Dr. K. Suvarna Vani, Professor, CSE, VRSEC for her moral support and valuable suggestions.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Vijaya Lakshmi, K.S., Sambasiva Rao, K.V., Prasad, E.V. (2018). Stream Preparation from Historical Data for High-Velocity Financial Applications. In: Bhateja, V., Tavares, J., Rani, B., Prasad, V., Raju, K. (eds) Proceedings of the Second International Conference on Computational Intelligence and Informatics . Advances in Intelligent Systems and Computing, vol 712. Springer, Singapore. https://doi.org/10.1007/978-981-10-8228-3_24
Download citation
DOI: https://doi.org/10.1007/978-981-10-8228-3_24
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-8227-6
Online ISBN: 978-981-10-8228-3
eBook Packages: EngineeringEngineering (R0)