IDEAS home Printed from https://ideas.repec.org/a/mgt/youmgt/v13y2015i1p27-41.html
   My bibliography  Save this article

Modelling Stock Market Volatility: Evidence from India

Author

Listed:
  • Karunanithy Banumathy

    (Pondicherry Central University, India)

  • Ramachandran Azhagaiah

    (Pondicherry Central University, India)

Abstract

This study empirically investigates the volatility pattern of Indian stock market based on time series data which consists of daily closing prices of S&P CNX Nifty Index for ten years period from 1st January 2003 to 31st December 2012. The analysis has been done using both symmetric and asymmetric models of Generalized Autoregressive Conditional Heteroscedastic (GARCH). As per Akaike Information Criterion (AIC) and Schwarz Information Criterion (SIC), the study proves that GARCH (1,1) and TGARCH (1,1) estimations are found to be most appropriate model to capture the symmetric and asymmetric volatility respectively. The study also provides evidence for the existence of a positive and insignificant risk premium as per GARCH-M (1,1) model. The asymmetric effect (leverage) captured by the parameter of EGARCH (1,1) and TGARCH (1,1) models show that negative shocks have significant effect on conditional variance (volatility).

Suggested Citation

  • Karunanithy Banumathy & Ramachandran Azhagaiah, 2015. "Modelling Stock Market Volatility: Evidence from India," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 13(1 (Spring), pages 27-41.
    • Handle: RePEc:mgt:youmgt:v:13:y:2015:i:1:p:27-41
    as

    Download full text from publisher

    File URL: http://www.fm-kp.si/zalozba/ISSN/1581-6311/13_027-041.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Neville Zivanayi Mandimika & Zivanemoyo Chinzara, 2012. "Risk–Return Trade-Off And Behaviour Of Volatility On The South African Stock Market: Evidence From Both Aggregate And Disaggregate Data," South African Journal of Economics, Economic Society of South Africa, vol. 80(3), pages 345-366, September.
    2. Chou, Ray Yeutien, 1988. "Volatility Persistence and Stock Valuations: Some Empirical Evidence Using Garch," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(4), pages 279-294, October-D.
    3. Schwert, G William, 1990. "Stock Volatility and the Crash of '87," The Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 77-102.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    6. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kumar Arya & Sahoo Jyotirmayee & Sahoo Jyotsnarani & Nanda Subhashree & Debyani Devi, 2024. "Exploring Asymmetric GARCH Models for Predicting Indian Base Metal Price Volatility," Folia Oeconomica Stetinensia, Sciendo, vol. 24(1), pages 105-123.
    2. Shekar Bose & Hafizur Rahman, 2022. "Are News Effects Necessarily Asymmetric? Evidence from Bangladesh Stock Market," SAGE Open, , vol. 12(4), pages 21582440221, October.
    3. Neifar, Malika, 2020. "Stock Market Volatility Analysis: A Case Study of TUNindex," MPRA Paper 99140, University Library of Munich, Germany.
    4. Novy Ann M. Etac & Roel F. Ceballos, 2019. "Forecasting the Volatilities of Philippine Stock Exchange Composite Index Using the Generalized Autoregressive Conditional Heteroskedasticity Modeling," Papers 1904.00749, arXiv.org.
    5. Bonga, Wellington Garikai, 2019. "Stock Market Volatility Analysis using GARCH Family Models: Evidence from Zimbabwe Stock Exchange," MPRA Paper 94201, University Library of Munich, Germany.
    6. Anas Eisa Abdelkreem Mohammed & Henry Mwambi & Bernard Omolo, 2024. "Time-Varying Correlations between JSE.JO Stock Market and Its Partners Using Symmetric and Asymmetric Dynamic Conditional Correlation Models," Stats, MDPI, vol. 7(3), pages 1-16, July.
    7. Amanjot SINGH, 2017. "Modeling Conditional Volatility Of Indian Banking Sector’S Stock Market Returns," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 64(3), pages 325-338, September.
    8. Aluko Olufemi Adewale & Adeyeye Patrick Olufemi & Migiro Stephen Oseko, 2017. "Modelling Volatility Persistence and Asymmetry with Structural Break: Evidence from the Nigerian Stock Market," Journal of Economics and Behavioral Studies, AMH International, vol. 8(6), pages 153-160.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jorge Caiado, 2004. "Modelling And Forecasting The Volatility Of The Portuguese Stock Index Psi-20," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 9(1), pages 3-21.
    2. Madhusudan Karmakar, 2007. "Asymmetric Volatility and Risk-return Relationship in the Indian Stock Market," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 8(1), pages 99-116, January.
    3. Tim Bollerslev & Ray Y. Chou & Narayanan Jayaraman & Kenneth F. Kroner - L, 1991. "es modéles ARCH en finance : un point sur la théorie et les résultats empiriques," Annals of Economics and Statistics, GENES, issue 24, pages 1-59.
    4. Kim, Dongcheol & Kon, Stanley J., 1999. "Structural change and time dependence in models of stock returns," Journal of Empirical Finance, Elsevier, vol. 6(3), pages 283-308, September.
    5. Yueh-Neng Lin & Ken Hung, 2008. "Is Volatility Priced?," Annals of Economics and Finance, Society for AEF, vol. 9(1), pages 39-75, May.
    6. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.
    7. Bauer, Rob M M J & Nieuwland, Frederick G M C & Verschoor, Willem F C, 1994. "German Stock Market Dynamics," Empirical Economics, Springer, vol. 19(3), pages 397-418.
    8. Christensen, Bent Jesper & Nielsen, Morten Ørregaard & Zhu, Jie, 2010. "Long memory in stock market volatility and the volatility-in-mean effect: The FIEGARCH-M Model," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 460-470, June.
    9. Pandey, Ajay, 2003. "Modeling and Forecasting Volatility in Indian Capital Markets," IIMA Working Papers WP2003-08-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    10. Choudhry, Taufiq, 1996. "Stock market volatility and the crash of 1987: evidence from six emerging markets," Journal of International Money and Finance, Elsevier, vol. 15(6), pages 969-981, December.
    11. Sheriffdeen A. Tella & Olumuyiwa G. Yinusa & Ayinde Taofeek Olusola & Saban Celik, 2011. "Global Economic Crisis And Stock Markets Efficiency: Evidence From Selected Africa Countries," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 25(1), pages 139-169.
    12. Cong, Ren & Lo, Alex Y., 2017. "Emission trading and carbon market performance in Shenzhen, China," Applied Energy, Elsevier, vol. 193(C), pages 414-425.
    13. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    14. Elyasiani, Elyas & Mansur, Iqbal, 1998. "Sensitivity of the bank stock returns distribution to changes in the level and volatility of interest rate: A GARCH-M model," Journal of Banking & Finance, Elsevier, vol. 22(5), pages 535-563, May.
    15. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    16. Calzolari, Giorgio & Fiorentini, Gabriele & Panattoni, Lorenzo, 1993. "Alternative estimators of the covariance matrix in GARCH models," MPRA Paper 24433, University Library of Munich, Germany.
    17. Wang, Yuanfang & Roberts, Matthew C., 2005. "Realized Volatility in the Agricultural Futures Market," 2005 Annual meeting, July 24-27, Providence, RI 19211, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    18. Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    19. Committee, Nobel Prize, 2003. "Time-series Econometrics: Cointegration and Autoregressive Conditional Heteroskedasticity," Nobel Prize in Economics documents 2003-1, Nobel Prize Committee.
    20. Faisal Khan & Saif-Ur-Rehman Khan & Hashim Khan, 2016. "Pricing of Risk, Various Volatility Dynamics and Macroeconomic Exposure of Firm Returns: New Evidence on Age Effect," International Journal of Economics and Financial Issues, Econjournals, vol. 6(2), pages 551-561.

    More about this item

    Keywords

    asymmetric volatility; conditional volatility; GARCH models and leverage effect;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mgt:youmgt:v:13:y:2015:i:1:p:27-41. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Alen Jezovnik (email available below). General contact details of provider: https://edirc.repec.org/data/fmkupsi.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.