金融高频数据有助于探索市场的微观结构和价格的短期行为,同时也为验证市场有效性提供了有力的佐证。但是将金融高频数据简单理解为一个细化的时间序列的做法至少忽略了日内与日间两个不同维度各自所具有的分布特征,为此本文提出双重视角。同时,受市场微结构噪声、跳跃等因素影响,金融高频数据也并不是一个优质的时间序列。从经验和理论特征两方面研究了金融高频数据的基本统计性质。The financial high-frequency data(FHD) could help to understand the market microstructure and short time behavior.It also documents the evidence for or against the efficient market hypothesis.But we point out that the FHD cannot merely be treated as a finer time series, because, at least, it ignore the distribution characteristics of inter-days and intraday.So we have a dual perspective of the FHD.And FHD is not a time series with high quality because of the market microstructure noise and the jump.At last, we explore the empirical and the theoretical characteristics of the FHD.国家社科基金项目(11BTJ001);国家社科基金重点项目(13QZD148); 辽宁省社会科学规划基金青年项目(L13CTJ004)资
