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Forecasting Volatility in Indian Stock Market using Artificial Neural Network with Multiple Inputs and Outputs

by Tamal Datta Chaudhuri, Indranil Ghosh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 120 - Number 8
Year of Publication: 2015
Authors: Tamal Datta Chaudhuri, Indranil Ghosh
10.5120/21245-4034

Tamal Datta Chaudhuri, Indranil Ghosh . Forecasting Volatility in Indian Stock Market using Artificial Neural Network with Multiple Inputs and Outputs. International Journal of Computer Applications. 120, 8 ( June 2015), 7-15. DOI=10.5120/21245-4034

@article{ 10.5120/21245-4034,
author = { Tamal Datta Chaudhuri, Indranil Ghosh },
title = { Forecasting Volatility in Indian Stock Market using Artificial Neural Network with Multiple Inputs and Outputs },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 120 },
number = { 8 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 7-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume120/number8/21245-4034/ },
doi = { 10.5120/21245-4034 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:05:40.344320+05:30
%A Tamal Datta Chaudhuri
%A Indranil Ghosh
%T Forecasting Volatility in Indian Stock Market using Artificial Neural Network with Multiple Inputs and Outputs
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 8
%P 7-15
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Volatility in stock markets has been extensively studied in the applied finance literature. In this paper, Artificial Neural Network models based on various back propagation algorithms have been constructed to predict volatility in the Indian stock market through volatility of NIFTY returns and volatility of gold returns. This model considers India VIX, CBOE VIX, volatility of crude oil returns (CRUDESDR), volatility of DJIA returns (DJIASDR), volatility of DAX returns (DAXSDR), volatility of Hang Seng returns (HANGSDR) and volatility of Nikkei returns (NIKKEISDR) as predictor variables. Three sets of experiments have been performed over three time periods to judge the effectiveness of the approach.

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Index Terms

Computer Science
Information Sciences

Keywords

Implied Volatility India VIX CBOE VIX Multi Layered Feed Forward Neural Network Back Propagation Algorithms Cascaded Feed Forward Neural Network Mean Square Error.

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