Forecasting Indian Stock Market Using Artificial Neural Networks

被引：0
|
作者：
Kale, Ashutosh [1 ]
Khanvilkar, Omkaar [1 ]
Jivani, Hardik [1 ]
Kumkar, Prathamesh [1 ]
Madan, Ishan [1 ]
Sarode, Tanuja [1 ]
机构：
[1] Thadomal Shahani Engn Coll, Dept Comp Engn, Mumbai, Maharashtra, India
来源：
2018 FOURTH INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA) | 2018年
关键词：
Nifty-100; Index; Artificial Neural Networks; Backpropagation Algorithm; Cross-validation; Forecasting Indian Stock Market;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The objective of this research is to predict the next day's opening value of Nifty-100 index of the National Stock Exchange (NSE) using Artificial Neural Networks (ANNs). The ANN is trained using Error Backpropagation Training Algorithm (EBPTA). The multilayer feedforward network is trained using the present day's closing values of seven input parameters which are Gold, Silver, Copper, Crude Oil, Natural Gas and Foreign Exchange (FOREX) rates. In addition to these six rates, the closing value of Nifty-100 index was incorporated as input using Simple Moving Average (SMA) model. The relationship between each input parameter and Nifty-100 index was studied and analyzed using correlation technique. This research proves that Nifty-100 index can be predicted using ANNs.
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页数：5
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