Abstract
By using datas of Chinese fuel oil futures market, this pater establishes VAR model based on low frequency, high frequency and ultra-high frequency data, to measure the value at risk, and compares the prediction accuracy of different frequency. The research results show that the high frequency and ultra-high frequency data have better accuracy in the VAR measuring, as they contain more intraday information and can reflect the futures market microstructure better.
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