Bagher Adabi Firouzjaee - Ph.D. Candidate in Faculty of Economics, University of Tehran, Iran
Mohsen Mehrara - Professor, Faculty of Economics, University of Tehran, Iran
Shapour Mohammadi - Associated Professor, Faculty of Management, University of Tehran, Iran

The purpose of this study is estimation of daily Value at Risk (VaR) for total index of Tehran Stock Exchange using parametric, nonparametric and semi-parametric approaches. Conditional and unconditional coverage backtesting are used for evaluating the accuracy of calculated VaR and also to compare the performance of mentioned approaches. In most cases, based on backtesting statistics Results, accuracy of calculated VaR is approved for historical, Monte Carlo and Volatility-Weighted historical simulation methods. It is also approved for GARCH type of volatility models under normal distribution and Riskmetrics model under student-t distribution. On the other hand, it is observed that parametric approach measures VaR value more than non-parametric and semi-parametric approaches. This result indicates that GARCH type of volatility models under student-t distribution overestimate magnitude of value at risk. Finally, four volatility models of parametric approach including NARCH, NAGARCH and APGARCH under normal distribution and Riskmetrics under student-t distribution are selected best methods to measure accurate value of VaR.

Nonparametric approach, Parametric Approach, Semi-Parametric Approach, Value at Risk