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市场中的数据,从本质上讲都是一种时间序列,这与小波分析中的信号有着相同的特征,本文将甲醇期货的时间序列数据看成信号,用依层次分解的方法来研究该期货的波动性以及长记忆性。研究发现,在月份相同的情况下,尺度不同的小波方差会导致不同的结果,小波方差主要是受不同时间段内交易频率的影响,即甲醇期货的收盘价的波动受到季节交替的影响。
The data in the market is essentially a time series, which has the same characteristics as the signals in wavelet analysis. In this paper, the time series data of methanol futures are regarded as signals, and the futures are studied by the method of level decomposition Volatility and long memory. The results show that the wavelet variance with different scales can lead to different results at the same month. The variance of the wavelet is mainly affected by the trading frequency in different time periods. That is, the fluctuation of the closing price of methanol futures is affected by the seasonal alternation.