重新审视交易价值的动态
The dynamics of traded value revisited
摘要：
通过对纽约证券交易所高分辨率数据的分析，我们得出结论：对于大多数股票$i$，交易价值$f_i$（或交易量）的分布具有有限的方差$σ_i$，并且分布本身在股票之间是非普适的。同一时间序列的Hurst指数在1天左右的时间尺度上表现出从弱相关到强相关的交叉行为。强相关机制的持续性随着平均交易活动$\ev{f_i}$作为$H_i=H_0+γ\log\ev{f_i}$而增加，这是非普遍行为的另一个迹象。这种流动性依赖相关性的存在与经验观察一致，即$σ_i\propto\ev{f_i}^α$，其中$α$是一个非平凡的时间尺度依赖指数。
英文摘要：
We conclude from an analysis of high resolution NYSE data that the distribution of the traded value $f_i$ (or volume) has a finite variance $σ_i$ for the very large majority of stocks $i$, and the distribution itself is non-universal across stocks. The Hurst exponent of the same time series displays a crossover from weakly to strongly correlated behavior around the time scale of 1 day. The persistence in the strongly correlated regime increases with the average trading activity $\ev{f_i}$ as $H_i=H_0+γ\log\ev{f_i}$, which is another sign of non-universal behavior. The existence of such liquidity dependent correlations is consistent with the empirical observation that $σ_i\propto\ev{f_i}^α$, where $α$ is a non-trivial, time scale dependent exponent.
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