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Value at Risk Models in the Indian Stock Market

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  • Varma, Jayanth R.

Abstract

This paper provides empirical tests of different risk management models in the Value at Risk (VaR) framework in the Indian stock market. It is found that the GARCH-GED (Generalised Auto-Regressive Conditional Heteroscedasticity with Generalised Error Distribution residuals) performs exceedingly well at all common risk levels (ranging from 0.25% to 10%). The EWMA (Exponentially Weighted Moving Average) model used in J. P. Morgan’s RiskMetrics® methodology does well at the 10% and 5% risk levels but breaks down at the 1% and lower risk levels. The paper then suggests a way of salvaging the EWMA model by using a larger number of standard deviations to set the VaR limit. For example, the paper suggests using 3 standard deviations for a 1% VaR while the normal distribution indicates 2.58 standard deviations and the GED indicates 2.85 standard deviations. With this modification the EWMA model is shown to work quite well. Given its greater simplicity and ease of interpretation, it may be more convenient in practice to use this model than the more accurate GARCH-GED specification. The paper also provides evidence suggesting that it may be possible to improve the performance of the VaR models by taking into account the price movements in foreign stock markets.

Suggested Citation

  • Varma, Jayanth R., 1999. "Value at Risk Models in the Indian Stock Market," IIMA Working Papers WP1999-07-05, Indian Institute of Management Ahmedabad, Research and Publication Department.
    • Handle: RePEc:iim:iimawp:wp01615
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    Cited by:

    1. Biswajit Patra & Puja Padhi, 2015. "Backtesting of Value at Risk Methodology: Analysis of Banking Shares in India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 9(3), pages 254-277, August.
    2. Rupika Khanna & Chandan Sharma & Abhay Pant, 2022. "COVID-19, firm characteristics and stock volatility: new evidence from the Indian tourism sector," International Journal of Emerging Markets, Emerald Group Publishing Limited, vol. 19(6), pages 1563-1585, October.
    3. Sinha, Pankaj & Agnihotri, Shalini, 2014. "Sensitivity of Value at Risk estimation to NonNormality of returns and Market capitalization," MPRA Paper 56307, University Library of Munich, Germany, revised 26 May 2014.
    4. Varma, Jayanth R., 2002. "Mispricing of Volatility in theIndian Index Options Market," IIMA Working Papers WP2002-04-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    5. Jitender, 2021. "Value-at-Risk Estimation of Equity Market Risk in India," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 9(1), pages 1-24, September.
    6. Malay Bhattacharyya & Dileep Kumar M & Ramesh Kumar, 2009. "Optimal sampling frequency for volatility forecast models for the Indian stock markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 38-54.
    7. Alok Pandey & Surya Bhushan Kumar, 2011. "Volatility Transmission from Global Stock Exchanges to India," Vision, , vol. 15(4), pages 347-360, December.

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