IDEAS home Printed from https://ideas.repec.org/a/ags/injagm/399642.html

Volatility and spillover in onion prices in major markets of Karnataka, India

Author

Listed:
  • Paul, Ranjit Kumar
  • Das, Tanima
  • Panwar, Sanjeev
  • Paul, A. K.
  • Bhar, L. M.

Abstract

In the recent times, the price volatility has been the main centre of attention for the researchers also understanding the spillover effect of one market on the others is of great practical importance. It is therefore important to extend the consideration univariate Generalized autoregressive conditional heteroscedastic (GARCH) model to Multivariate GARCH (MGARCH) model. Various aspects of cointegration and vector error correction model have been discussed. In the MGARCH model, Baba-Engle-Kraft-Kroner (BEKK) and Constant Conditional Correlation (CCC) models are considered for modeling volatility of onion prices in two major markets of onion in Karnataka, India. It is concluded that that the two markets are cointegrated and there exists spillover effect among them.

Suggested Citation

  • Paul, Ranjit Kumar & Das, Tanima & Panwar, Sanjeev & Paul, A. K. & Bhar, L. M., 2019. "Volatility and spillover in onion prices in major markets of Karnataka, India," Indian Journal of Agricultural Marketing, Indian Society of Agricultural Marketing, vol. 33(2).
    • Handle: RePEc:ags:injagm:399642
    DOI: 10.22004/ag.econ.399642
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/399642/files/Volatility%20and%20spillover%20in%20onion%20prices%20in%20major%20markets%20of%20Karnataka%2C%20India.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.399642?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Paul, Ranjit Kumar & Panwar, Sanjeev & Sarkar, Susheel Kumar & Kumar, Anil & Singh, K.N. & Farooqi, Samir & Choudhary, Vipin Kumar, 2013. "Modelling and Forecasting of Meat Exports from India," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 26(2).
    2. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2013. "Multivariate Volatility Modeling Of Electricity Futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 743-761, August.
    3. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    4. Wani, M.H. & Paul, Ranjit Kumar & Bazaz, Naseer H. & Manzoor, M., 2015. "Market integration and Price Forecasting of Apple in India," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 70(2), pages 1-13.
    5. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Huang, Da & Wang, Hansheng & Yao, Qiwei, 2008. "Estimating GARCH models: when to use what?," LSE Research Online Documents on Economics 5398, London School of Economics and Political Science, LSE Library.
    8. Da Huang & Hansheng Wang & Qiwei Yao, 2008. "Estimating GARCH models: when to use what?," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 27-38, March.
    9. Wani, M.H & Bazaz, N.H. & Paul, R.K. & Itoo, S.A. & Bhat, A., 2015. "Inter-Sectoral Linkages in Jammu & Kashmir Economy — An Econometric Analysis," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 28(Conferenc).
    10. 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)

    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. Greg Hannsgen, 2011. "Infinite-variance, Alpha-stable Shocks in Monetary SVAR: Final Working Paper Version," Economics Working Paper Archive wp_682, Levy Economics Institute.
    2. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    3. M. Jiménez Gamero, 2014. "On the empirical characteristic function process of the residuals in GARCH models and applications," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(2), pages 409-432, June.
    4. repec:got:cegedp:89 is not listed on IDEAS
    5. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    6. Kühl, Michael, 2009. "Excess comovements between the Euro/US dollar and British pound/US dollar exchange rates," University of Göttingen Working Papers in Economics 89, University of Goettingen, Department of Economics.
    7. Fresoli, Diego E. & Ruiz, Esther, 2016. "The uncertainty of conditional returns, volatilities and correlations in DCC models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 170-185.
    8. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    9. Spierdijk, Laura, 2016. "Confidence intervals for ARMA–GARCH Value-at-Risk: The case of heavy tails and skewness," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 545-559.
    10. Nidhi Choudhary & Girish K. Nair & Harsh Purohit, 2015. "Volatility In Copper Prices In India," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-26, December.
    11. Hasanov, Akram Shavkatovich & Do, Hung Xuan & Shaiban, Mohammed Sharaf, 2016. "Fossil fuel price uncertainty and feedstock edible oil prices: Evidence from MGARCH-M and VIRF analysis," Energy Economics, Elsevier, vol. 57(C), pages 16-27.
    12. Ujjwala Vadrevu, 2026. "A Hybrid Gaussian Process Regression Framework for Stable Volatility-Covariance Estimation: Evidence from Global Equity Indices," Papers 2605.17275, arXiv.org.
    13. Julyerme M. Tonin & Carlos M. R. Vieira & Rui M. de Sousa Fragoso & João G. Martines Filho, 2020. "Conditional correlation and volatility between spot and futures markets for soybean and corn," Agribusiness, John Wiley & Sons, Ltd., vol. 36(4), pages 707-724, October.
    14. Cristiana Tudor & Aura Girlovan & Gabriel Robert Saiu & Daniel Dumitru Guse, 2025. "Asymmetric Shocks and Pension Fund Volatility: A GARCH Approach with Macroeconomic Predictors to an Unexplored Emerging Market," Mathematics, MDPI, vol. 13(7), pages 1-29, March.
    15. SILVESTRINI, Andrea & VEREDAS, David, 2005. "Temporal aggregation of univariate linear time series models," LIDAM Discussion Papers CORE 2005059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    17. Erie Febrian & Aldrin Herwany, 2009. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Economics and Development Studies (WoPEDS) 200911, Department of Economics, Padjadjaran University, revised Sep 2009.
    18. Michael Mcaleer & Bernardo da Veiga, 2008. "Forecasting value-at-risk with a parsimonious portfolio spillover GARCH (PS-GARCH) model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 1-19.
    19. Caporin, M. & McAleer, M.J., 2013. "Ten Things You Should Know About DCC," Econometric Institute Research Papers EI 2013-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. He, Zhongfang, 2018. "A Class of Generalized Dynamic Correlation Models," MPRA Paper 84820, University Library of Munich, Germany.
    21. Haigh, Michael S. & Bryant, Henry L., 2001. "The effect of barge and ocean freight price volatility in international grain markets," Agricultural Economics, Blackwell, vol. 25(1), pages 41-58, June.

    More about this item

    Keywords

    ;

    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:ags:injagm:399642. 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: AgEcon Search (email available below). General contact details of provider: https://agrilmktg.in/ .

    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.