TY  - JOUR
T1  - Forecasting the Stock Index Movements of India: Application of Neural Networks
AU - Marxiaoli, Sigo AU - Selvam, Murugesan AU - Lingaraja, Kasilingam AU - Vasanth, Vinayagamoorthi 
JO  - International Journal of Soft Computing
VL  - 12
IS  - 2
SP  - 120
EP  - 131
PY  - 2017
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2017.120.131
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2017.120.131
KW  - Artificial intelligence
KW  -behavioural finance
KW  -capital market
KW  -forecasting
KW  -investment
KW  -neural network
KW  -predictive analytics
KW  -regression
KW  -stochastic and stock index
AB  - Prediction of financial markets, especially prediction of highly volatile stochastic stock market indices, plays a crucial role in identifying profitable investment avenues by the financial investors at large. The investing community encompasses retail investors, financial institutions, investment banks and Foreign Institutional Investors who look for the creation of wealth in the form of capital appreciation and earning the title of ownership of business enterprises by investing in the securities market, through buying and selling of shares of stock exchange listed corporate entities. The forecasting of dynamic financial market movements is one of the scientific endeavours which demands a great deal of market intelligence, financial acumen and domain knowledge of the characteristics of behavioural finance in a wider spectrum. This paper aims to discuss the non-linear movement pattern/trend of the most active two stock indices of India, namely, the Sensex and Nifty, during the study period from 2009-2015 by applying the traditional logistic regression method and one of the neural network tools, namely, k-nearest neighbourhood algorithm. This study would help the investors to streamline their investment patterns and strategies in order to take well informed investment decisions and optimize their stock returns by using the relevant market information.
ER  -