CFP last date
20 May 2024
Reseach Article

Predicting India Volatility Index: An Application of Artificial Neural Network

by Gaurav Dixit, Dipayan Roy, Nishant Uppal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 4
Year of Publication: 2013
Authors: Gaurav Dixit, Dipayan Roy, Nishant Uppal
10.5120/11950-7768

Gaurav Dixit, Dipayan Roy, Nishant Uppal . Predicting India Volatility Index: An Application of Artificial Neural Network. International Journal of Computer Applications. 70, 4 ( May 2013), 22-30. DOI=10.5120/11950-7768

@article{ 10.5120/11950-7768,
author = { Gaurav Dixit, Dipayan Roy, Nishant Uppal },
title = { Predicting India Volatility Index: An Application of Artificial Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 4 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 22-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number4/11950-7768/ },
doi = { 10.5120/11950-7768 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:31:58.910079+05:30
%A Gaurav Dixit
%A Dipayan Roy
%A Nishant Uppal
%T Predicting India Volatility Index: An Application of Artificial Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 4
%P 22-30
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Forecasting has always been an area of interest for the researchers in various realms of finance especially in the stock market e. g. stock index, return on a stock, etc. Stock market volatility is one such area. Since the inception of implied volatility index (VIX) by the Chicago Board of Options Exchange (CBOE) in 1993, VIX index has generated a lot of interest. This study examines the predicting ability of several technical indicators related to VIX index to forecast the next trading day's volatility. There is a wide set of methods available for forecasting in finance. In this study, Artificial neural network (ANN) modeling technique has been employed to forecast the upwards or downwards movement in next trading day's volatility using India VIX (a volatility index based on the NIFTY Index Option prices) based indicators. The results of the study reveal that ANN models can be real handy in forecasting the downwards movement in VIX. The knowledge about a more probable downwards movement in volatility might be significant value add for the investors and help them in making decisions related to trading.

References
  1. Adya M, & Collopy F. 1998. How Effective are Neural Networks at Forecasting and Prediction? A Review and Evaluation. Journal of Forecasting 17(5-6): 481-495.
  2. Al-Hindi HA, Al-Hasan ZF. 2002. Forecasting Stock Returns with the Neural Network Models. Journal of King Saud University 14(1): 65-81.
  3. Andersen TG, Sorensen BE. 1997. GMM and QML Asymptotic Standard Deviations in Stochastic Volatility Models, Journal of Econometrics 76: 397-403.
  4. Avci E. 2007. Forecasting Daily and Seasonal Returns of the ISE-100 Index with Neural Network Models. Dogus University Journal 8(2): 128-142.
  5. Bannerjee, A. & Kumar, R. (2011). Realized Volatility and India VIX. IIM Calcutta working paper series no 688.
  6. Black F, Scholes M. (1973). The Pricing of Options and Corporate Liabilities. The Journal of Political Economy 81(3): 637-654.
  7. Blair BJ, Poon S-H, Taylor SJ. 2001. Forecasting S&P100 Volatility: The Incremental Information Content of Implied Volatilities and High-Frequency Index Returns. Journal of Econometrics 105: 5-26.
  8. Cajal R. S. (1911). Histology of the nervous system of man and vertebrates. New York: Oxford University Press.
  9. Danielsson J. 1994. Stochastic Volatility in Asset Prices: Estimation with Simulated Maximum Likelihood. Journal of Econometrics 64: 375–400.
  10. Degiannakis S. 2008. Forecasting VIX. Journal of Money, Investment and Banking 4: 5-19.
  11. Degiannakis S, Floros C. 2010. VIX Index in Interday and Intraday Volatility Models. Journal of Money, Investment and Banking 13: 21-26.
  12. Diler AI. 2003. Forecasting the direction of ISE National-100 index by neural networks backpropagation algorithm. ISE Review 7(25-26): 65-81.
  13. Duffie D, Singleton KJ. 1993. Simulated Moments Estimation of Markov Models of Asset Prices. Econometrica 6: 929-52.
  14. Engle RF. 1993. Statistical Models for Financial Volatility. Financial Analysts Journal. 49(1): 72-78.
  15. Fridman M. , Harris L. 1998. A Maximum Likelihood Approach for Non Gaussian Stochastic Volatility Models. Journal of Business and Economic Statistics 16: 284-91.
  16. Garson GD. 1998. Neural Networks: An Introductory Guide for Social Scientists. London: Sage.
  17. Gencay R. 1998. Optimization of Technical Trading Strategies and the Profitability in the Stock Markets. Economic Letters 59(2): 249-254.
  18. Giles CL, Lawrence S, Tsoi AC. 2001. Noisy Time Series Prediction using Recurrent Neural Networks and Grammatical Inference. Machine Learning 44: 161-183.
  19. Hull J, White A. 1987. The pricing of options on assets with stochastic volatilities. Journal of Finance 42(2): 281-300.
  20. Hull J, White A. 1988. An Analysis Of The Bias In Option Pricing Caused By A Stochastic Volatility. Advances in Options and Futures Research 3: 27-61.
  21. Kim SH, Chun SH. 1998. Graded Forecasting Using Array of Bipolar Predictions: Application of Probabilistic Neural Networks to a Stock Market Index. International Journal of Forecasting, 14(3): 323-337.
  22. Kim KJ. 2006. Artificial Neural Networks with Evolutionary Instance Selection for Financial Forecasting. Expert System Applications, Vol. 30, No. 3, pp. 519-526.
  23. Kohonen T. 1998. The self-organizing map. Neurocomputing 21: 1-6.
  24. Kroner KF. 1996. Creating and using volatility forecasts. Derivatives Quarterly 3(2): 39-53.
  25. Kwong, C. K. 2001. Financial Forecasting Using Neural Networks or Machine Learning Techniques. http://www. innovexpo. itee. uq. edu. au/2001/projects/s804018/index. html [19 January 2013].
  26. Lam M. 2004. Neural Network Techniques for Financial Performance Prediction: Integrating Fundamental and Technical Analysis. Decision Support Systems, 37(4):567-581.
  27. Lim GC, McNelis PD. 1998. The Effect of the Nikkei and the S&P on the All- Ordinaries: A Comparision of Three Models. International Journal of Finance and Economics 3(3): 217-228.
  28. Majumdar U, Banerjee A. 2004. VIX Forecasting. Social Science Research Network, Working Paper id-533583.
  29. McCulloch WS, Pitts W. 1943. A logical calculus of the ideas immanent in nervous activity. The Bulletin of Mathematical Biophysics 5(4):115-133.
  30. Nakamura E. 2005. Inflation forecasting using a neural network. Economics Letters. 86(3) 373-378.
  31. Pavlidis NG, Tasoulis DK, Plagianakos VP, Nikiforidis G & Vrahatis MN. 2005. Spiking neural network training using evolutionary algorithms. International Joint Conference on Neural Networks (IJCNN 2005). IEEE: 2190-2194.
  32. Poon SH, Granger CWJ. 2003. Forecasting Volatility in Financial Markets: A Review. Journal of Economic Literature 41 (2): 478-539.
  33. Rodriguez JV, Torra S, Andrada FJ. 2005. STAR and ANN models: forecasting performance on the Spanish Ibex-35 stock index. Journal of Empirical Finance 12(3): 490-509.
  34. Roy P, Roy A. 2008. Forecasting Daily Returns of Nifty Index – Using the Method of Artificial Neural Network. Forecasting Financial Markets in India (FFMI) 2008 Conference Proceedings: 787-800.
  35. Singleton K. 2001. Estimation of Affine Asset Pricing Models Using the Empirical Characteristic Function. Journal of Econometrics 102:111-141.
  36. The CBOE Volatility Index- VIX. http://www. cboe. com/micro/vix/vixwhite. pdf [12 December 2012]
  37. Vashisth R, Chandra A. 2010. Predicting stock returns in Nifty index: An application of artificial neural network. International Research Journal of Finance and Economics 49: 15-24.
  38. White H. 1988. Economic Prediction Using Neural Networks: The Case of IBM Daily Stock Returns. Proceedings of the Second Annual IEEE Conference on Neural Networks, II:451-458.
  39. White paper on India VIX. http://www. nseindia. com/content/vix/white_paper_IndiaVIX. pdf [12 December 2012]
  40. Xin M. 2011. The VIX Volatility Index. uu. divaportal. org/smash/get/diva2:417612/FULLTEXT01 [19 January 2013].
Index Terms

Computer Science
Information Sciences

Keywords

Artificial Neural Network India VIX Forecasting NIFTY Index options