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供需中的长期记忆理论。

Theory for long memory in supply and demand.

作者信息

Lillo Fabrizio, Mike Szabolcs, Farmer J Doyne

机构信息

Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, USA.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Jun;71(6 Pt 2):066122. doi: 10.1103/PhysRevE.71.066122. Epub 2005 Jun 22.

DOI:10.1103/PhysRevE.71.066122
PMID:16089835
Abstract

Recent empirical studies have demonstrated long-memory in the signs of orders to buy or sell in financial markets [J.-P. Bouchaud, Y. Gefen, M. Potters, and M. Wyart, Quant. Finance 4, 176 (2004); F. Lillo and J. D. Farmer Dyn. Syst. Appl. 8, 3 (2004)]. We show how this can be caused by delays in market clearing. Under the common practice of order splitting, large orders are broken up into pieces and executed incrementally. If the size of such large orders is power-law distributed, this gives rise to power-law decaying autocorrelations in the signs of executed orders. More specifically, we show that if the cumulative distribution of large orders of volume v is proportional to v(-alpha) and the size of executed orders is constant, the autocorrelation of order signs as a function of the lag tau is asymptotically proportional to tau(-(alpha-1)). This is a long-memory process when alpha < 2. With a few caveats, this gives a good match to the data. A version of the model also shows long-memory fluctuations in order execution rates, which may be relevant for explaining the long memory of price diffusion rates.

摘要

最近的实证研究表明,金融市场中买卖指令的信号存在长期记忆性[J.-P. 布沙尔、Y. 格芬、M. 波特斯和M. 怀亚特,《量化金融》4,176(2004);F. 利洛和J. D. 法默,《动态系统应用》8,3(2004)]。我们展示了这是如何由市场清算延迟导致的。在订单拆分的常见做法下,大订单被拆分成若干部分并逐步执行。如果此类大订单的规模服从幂律分布,这会导致已执行订单信号中出现幂律衰减的自相关性。更具体地说,我们表明,如果成交量为v的大订单的累积分布与v^(-α)成正比,且已执行订单的规模恒定,那么订单信号的自相关性作为滞后τ的函数渐近地与τ^(-(α - 1))成正比。当α < 2时,这是一个长期记忆过程。在一些注意事项下,这与数据有很好的匹配度。该模型的一个版本还显示了订单执行率中的长期记忆波动,这可能与解释价格扩散率的长期记忆有关。

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