Estimation of dynamic VaR using JSU and PIV distributions
Sree Vinutha Venkataraman () and
S. V. D. Nageswara Rao ()
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Sree Vinutha Venkataraman: School Great Lakes Institute of Management
S. V. D. Nageswara Rao: Indian Institute of Technology (IIT), Bombay
Risk Management, 2016, vol. 18, issue 2, 111-134
Abstract This paper explores the estimation of value at risk (VaR) dynamically for the top three ranked Diversified Equity Schemes, Large Cap Equity Schemes, and Small & Mid Cap Equity Schemes in India in addition to S&P CNX Nifty and BSE SENSEX. While volatility clustering is addressed using GARCH model, the non-normality behavior associated with equity returns is handled by employing the Johnson’s SU (JSU) or Pearson Type IV (PIV) distributed innovations in the ARMA–GARCH model. We find that both JSU and PIV distributions demonstrate better predictive abilities than Normal distribution. Further, the model incorporates current volatility and administers prior warning to the market participants without disturbing the price discovery process. Regulators can determine capital requirements by implementing the dynamic VaR model. Also, through such a mechanism, additional margins can be imposed in advance during extreme price fluctuations. We propose JSU distribution in conjunction with ARMA–GARCH model based on superior out-sample VaR prediction.
Keywords: Value at risk; ARMA; GARCH; Johnson’s SU distribution (JSU); Pearson type IV distribution (PIV) (search for similar items in EconPapers)
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