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Margin-Setting in Chinese Commodity Futures Markets: A VaR Approach

Statistical theory is used to help select a margin level. This paper present a prudent margin-setting models to protect futures positions from extreme price movement. Five methods based GARCH models to estimate the current volatility are proposed to estimate Value at risk describing the tail of the conditional or unconditional distributions of two financial return series. Using backtesting of historical daily return series we show that our procedure gives better 1-day estimates than methods which ignore the heavy tails of the innovations or the stochastic nature of the volatility. Furthermore, the empirical results show that the default risk of GPD distribution is judged to the most prudential method among the three fat fail distributions.