At present, GARCH type models have been employed to model these high frequency financial time series due to their ability to capture the dynamic characteristics.
近年来GARCH模型被广泛地用于对变动频率很高的金融时间序列建模，它能较好地抓住此类时间序列的动态特征。
The existing methods of similarity search are not suitable for high frequency financial data, which is a kind of non-interval time series.
金融高频数据是一种不等间隔的时间序列，现有的相似性查找技术对高频数据的处理效果不佳。
High frequency time series is referred to financial data which is sampled with interval of one hour, one minute even one second.
高频时间序列通常是指以每小时、每分钟甚至每秒为频率所采集的金融类数据；
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