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Asymmetric Price Volatility of Onion in India

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  • Rakshit, Debopam
  • Paul, Ranjit Kumar
  • Panwar, Sanjeev

Abstract

Price of onion shows a high degree of volatility. Price volatility is said to be asymmetric when it is affected by positive and negative shocks of same magnitude with different degree. Asymmetric volatility can be captured by asymmetric GARCH type of model such as EGARCH, APARCH and GJR-GARCH. Weekly modal price of onion for Delhi, Lasalgaon and Bengaluru markets are modelled with the help of these asymmetric variance models. For the present investigation, APARCH model outperformed the other competing models and it is considered as the best fit model for the data under consideration. Finally, the extent of asymmetry due to positive and negative shocks for all these markets are visualised with the help of News Impact Curves.

Suggested Citation

  • Rakshit, Debopam & Paul, Ranjit Kumar & Panwar, Sanjeev, 2021. "Asymmetric Price Volatility of Onion in India," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 0(Number 2), June.
    • Handle: RePEc:ags:inijae:345159
    DOI: 10.22004/ag.econ.345159
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    References listed on IDEAS

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    1. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    2. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Saxena, Raka & Paul, Ranjit Kumar & Kumar, Rohit, 2020. "Transmission of price shocks and volatility spillovers across major onion markets in India," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 33(01), June.
    5. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    6. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    7. Sekhar, C. S. C. & Roy, Devesh & Bhatt, Yogesh, 2017. "Food inflation and food price volatility in India: Trends and determinants," IFPRI discussion papers 1640, International Food Policy Research Institute (IFPRI).
    8. Paul, R.K. & Saxena, R. & Chaurasia, S. & Zeeshan & Rana, S., 2015. "Examining Export Volatility, Structural Breaks in Price Volatility and Linkages between Domestic and Export Prices of Onion in India," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 28(Conferenc).
    9. 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.
    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.
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