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The Implications of Big Data in Indian Stock Market

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 99 - Number 5
Year of Publication: 2014
Authors:
Krishna Kumar Singh
Priti Dimri
Krishna Nand Rastogi
10.5120/17368-7892

Krishna Kumar Singh, Priti Dimri and Krishna Nand Rastogi. Article: The Implications of Big Data in Indian Stock Market. International Journal of Computer Applications 99(5):8-11, August 2014. Full text available. BibTeX

@article{key:article,
	author = {Krishna Kumar Singh and Priti Dimri and Krishna Nand Rastogi},
	title = {Article: The Implications of Big Data in Indian Stock Market},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {99},
	number = {5},
	pages = {8-11},
	month = {August},
	note = {Full text available}
}

Abstract

Big, Unstructured, heterogeneous and temporal data is being generated every second in the stock market and it requires a new school of thought which can not only handles its complexities but also able to help in the future prediction and analytics of the market. Big data analytics is a very promising area and buzz word for the next generation information technologies. Knowledge discovery and future forecasting will not possible without handling the core challenges of big data. Stock market is one of the burning areas where data is growing day by day. Because of these heterogeneity and other complexities of data, big data architecture and design is needed which specifically deals with the stock market data and analyze these heterogeneous data for the future prediction of the market. This paper deals with nature of data generated and required for knowledge discovery & future prediction of the stock market. It also deals with the relevance of big data analytics in the stock market.

References

  • Chien-Jen Huang, Peng-Wen Chen, Wen-Tsao Pan, "Using multi-stage data mining technique to build forecast model for Taiwan stocks", Springer-Verlag London Limited 2011.
  • David J. Hand, "Data, Not Dogma: Big Data, Open Data, and the Opportunities Ahead", LNCS 8207, pp. 1-12, 2013.
  • Emerson, J. W. , Kane, M. J. : Don't drown in data. Significance Vol. 9(4), pp. 38–39, 2012.
  • FergusonGT. Strategy in the digital age: Role of information technology in corporate strategic planning. Journal of Business Strategy, Vol. 17(6), pp. 28–31, 1996.
  • Gartner (2012), http://www. gartner. com/Display Document? id=2057415&ref =client FriendlyUrl.
  • Hand, D. J. , Blunt, G. , Kelly, M. G. , Adams, N. M. : Data mining for fun and profit. Statistical Science 15, pp. 111–131, 2000.
  • Hand, D. J. : Mining the past to determine the future: problems and possibilities. International Journal of Forecasting 25, pp. 441–451, 2008.
  • Hoplin HP. Re-engineering information technology: An enabler for the new business strategy. Industrial Management & Data System, Vol. 95(2), pp. 24–27, 1995.
  • Kamran Rezaie, Vahid Majazi Dalfard, Loghman Hatami-Shirkouhi, Salman Nazari-Shirkouhi, "Efficiency appraisal and ranking of decision-making units using data envelopment analysis in fuzzy environment: a case study of Tehran stock exchange", Neural Comput & Applic DOI 10. 1007/s00521-012-1209-6.
  • Krishna Kumar Singh, Dr. Priti Dimri and Madhu Rawat, "Fractal Market Hypothesis in Indian Stock Market", IJARCSSE, Vol. 3(11), pp. 739-743, Nov 2013.
  • Manyika, J. , Chui, M. , Brwon, B. , Bughin, J. , Dobbs, R. , Roxburgh, C. ,Byers, R. H. : Big data: the next frontier for innovation, competition, and productivity (2011), http://www. mckinsey. com/insights/business technology/big data the next frontier for innovation.
  • Patrick Thomas, "A relationship between technology indicators and stock market performance", Jointly published by Kluwer Academic Publishers, Dordrecht Scientometrics, and Akadémiai Kiadó, Budapest Vol. 51, No. 1, pp. 319–333, 2001.
  • Oussaide`ne M, Chopard B, Pictet OV, Tomassini M Parallel genetic programming: an application to trading models evolution. In: Proceedings of the first annual conference on genetic programming, GECCO '96. MIT Press, Cambridge, pp 357–362, 1996.
  • Oussaide`ne M, Chopard B, Pictet OV, Tomassini M, Parallel genetic programming and its application to trading model induction. Parallel Comput 23, pp. 1183–1198, 1997.
  • Sampler JL, Redefining industry structure for the information age. Strategic Management Journal Vol. 19(4), pp. 343–355, 1998.