Paper Title : ENHANCEMENT OF MARKET DATA PARTITIONING SCALABILITY AND HIGH DIAMENTIONALITY MANAGEMENT USING DEEP LEARNING

ISSN : 2394-2231
Year of Publication : 2021

10.29126/23942231/IJCT-v8i2p29

Authors: K.E.Eswari., MCA., M.Phil.,M.E., P.Sivanandham

         



MLA Style: K.E.Eswari., MCA., M.Phil.,M.E., P.Sivanandham "ENHANCEMENT OF MARKET DATA PARTITIONING SCALABILITY AND HIGH DIAMENTIONALITY MANAGEMENT USING DEEP LEARNING " Volume 8 - Issue 2 March-April , 2021 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

APA Style: K.E.Eswari., MCA., M.Phil.,M.E., P.Sivanandham "ENHANCEMENT OF MARKET DATA PARTITIONING SCALABILITY AND HIGH DIAMENTIONALITY MANAGEMENT USING DEEP LEARNING " Volume 8 - Issue 2 March-April , 2021 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

Abstract
Forecasting store arrival is essential economic topics that have involved researchers’ concentration for several years. It involves a supposition that primary information widely offered in the precedent have various predictive associations to the expectations supply profits. Stock marketplace prediction is performing of annoying to decide the prospect worth of a concern stock or some other monetary tool traded on a replace. The unbeaten calculation of a stock's prospect cost might give up important income. The efficient-market theory suggests that stockpile rates replicate all presently accessible record and some cost modify that are not depend on recently exposed information thus are intrinsically changeable. Others diverge and those with this point of view have countless methods and technologies which supposedly let them to get prospect cost value. Our project has proposed ANN is a better suitable algorithm to predict stock market databases with better result.

Reference
[1] Al-Haddad W. Alzurqan S. and Al_Sufy S, The Effect of Corporate Governance on the Performance of Jordanian Industrial Companies: An empirical study on Bombay Stock Exchange. International Journal of Humanities and Social Science, Vol. 1 No. 4; April 2011. [2] Al-Debie, M., Walker, M. (1999). “Fundamentalinformation analysis: An extension and UK evidence”,Journal of Accounting Research, 31(3), pp. 261–280. [3] Cao, Q., Leggio, K.B., and Schniederjans, M.J., (2005) “A comparison between Fama and French’s model and artificial neural networks in predicting the Chinese stock market”, Computers & Operations Research, 32, pp. 2499-2512. [4] Chapman P., Clinton J., Kerber R., Khabaza T., Reinartz T., Shearer C., and Wirth R., (2000). “CRISPDM 1.0: Step-by-step data mining guide” [5] Enke, D., Thawornwong, S. (2005) “The use of data mining and neural networks for forecasting stock market returns”, Expert Systems with Applications, 29, pp. 927- 940

Keywords
— Forecasting, Market data, Scalability, Marketplace, Machine Learning, ANN, Dimensionality.