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Analysis of Stock Volatility Clustering Using ANN

Analysis of Stock Volatility Clustering Using ANN

Manish Kumar, Santanu Das, Sneha Govil
Copyright: © 2015 |Volume: 28 |Issue: 2 |Pages: 14
ISSN: 1040-1628|EISSN: 1533-7979|EISBN13: 9781466675544|DOI: 10.4018/IRMJ.2015040103
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MLA

Kumar, Manish, et al. "Analysis of Stock Volatility Clustering Using ANN." IRMJ vol.28, no.2 2015: pp.32-45. http://doi.org/10.4018/IRMJ.2015040103

APA

Kumar, M., Das, S., & Govil, S. (2015). Analysis of Stock Volatility Clustering Using ANN. Information Resources Management Journal (IRMJ), 28(2), 32-45. http://doi.org/10.4018/IRMJ.2015040103

Chicago

Kumar, Manish, Santanu Das, and Sneha Govil. "Analysis of Stock Volatility Clustering Using ANN," Information Resources Management Journal (IRMJ) 28, no.2: 32-45. http://doi.org/10.4018/IRMJ.2015040103

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Abstract

The model building theories broadly categorize the stock index forecasting models into two broad categories: Based on statistical theory consisting models such as Stochastic Volatility model (SV) and General Autoregressive Conditional Heteroskedasticity (GARCH) whereas other one based on artificial intelligence based models, such as artificial neural network (ANN), the support vector machine (SVM) and technique used for optimization such as particle swarm optimization (PSO). In existing literature, many of the statistical models when compared with artificial neural network models were outperformed by these models. This paper analyses stock volatility using ANN models as Multilayer perceptron with back propagation model and Radial Basis function.

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