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Investment profit folio Decisions based on CII Algorithm for Indian Stock Market

by Rajesh V. Argiddi, Sulabha S. Apte
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 65 - Number 16
Year of Publication: 2013
Authors: Rajesh V. Argiddi, Sulabha S. Apte
10.5120/11012-6348

Rajesh V. Argiddi, Sulabha S. Apte . Investment profit folio Decisions based on CII Algorithm for Indian Stock Market. International Journal of Computer Applications. 65, 16 ( March 2013), 46-51. DOI=10.5120/11012-6348

@article{ 10.5120/11012-6348,
author = { Rajesh V. Argiddi, Sulabha S. Apte },
title = { Investment profit folio Decisions based on CII Algorithm for Indian Stock Market },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 65 },
number = { 16 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 46-51 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume65/number16/11012-6348/ },
doi = { 10.5120/11012-6348 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:19:03.437275+05:30
%A Rajesh V. Argiddi
%A Sulabha S. Apte
%T Investment profit folio Decisions based on CII Algorithm for Indian Stock Market
%J International Journal of Computer Applications
%@ 0975-8887
%V 65
%N 16
%P 46-51
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The globalization in market, foreign investment and effect of current news issues makes difficult for investor to take better decisions. This paper introduces a new algorithm CII and describes the process of finding best association rules which is promising one to forecast the market. This experimental work reduces the time required for processing huge stock data and extract best rules with minimum window size to proper investment in stock market.

References
  1. Eugene F Fama: "The Behavior of stock Market Prices", The Journal of Business, Jan 1995
  2. R. Agrawal, R. Srikant: Fast algorithms for mining association rules, in: Proceedings of International Conference on Very Large Data Bases, Santiago, Chile, 1994, pp. 487–499.
  3. A. K. H. Tung, H. L. , J. Han, and L. Feng (2003): "Efficient mining of inter-transaction association rules. " IEEE Transactions on Knowledge and Data Engineering 15(1): 43-56.
  4. Agraw, R. , Imielinski, T. , Swami, A. , "Mining association rules between sets of items in large database", Proceedings of ACM-SIGMOD, Montreal, Canada, 1993
  5. Antony Tung,Jaiwei Han,Ling Feng : Beyond Intra-transaction Association Analysis: Mining Multi-dimensional Intertransaction Association Rules (Lu, Feng, Han, ACM journal, 30 pages)
  6. J. Han, J. Pei, and Y. Yin (2000): Mining frequent patterns without candidate generation. The 2000 ACM SIGMOD international conference on Management of data table of contents, USA.
  7. A. K. H. Tung, H. L. , J. Han, and L. Feng (2003): "Efficient mining of inter-transaction association rules. " IEEE Transactions on Knowledge and Data Engineering 15(1): 43-56.
  8. A. J. T. Lee and C. Wang (2007): "An efficient algorithm for mining frequent inter- transaction patterns. " Information Sciences 177(17): 3453-3476.
  9. Ranjeetsingh B. Parihar and Rajesh V. Argiddi (ITBI 2011): "Combined Intra-Inter transaction based approach for mining Association among the sectors in Indian Stock Market" In ITBI 2011). Page No. 26
Index Terms

Computer Science
Information Sciences

Keywords

CII Forecast Market association rule

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