The adaptive nature of liquidity taking in limit order books
Damian Eduardo Taranto,
Giacomo Bormetti and
Papers from arXiv.org
In financial markets, the order flow, defined as the process assuming value one for buy market orders and minus one for sell market orders, displays a very slowly decaying autocorrelation function. Since orders impact prices, reconciling the persistence of the order flow with market efficiency is a subtle issue. A possible solution is provided by asymmetric liquidity, which states that the impact of a buy or sell order is inversely related to the probability of its occurrence. We empirically find that when the order flow predictability increases in one direction, the liquidity in the opposite side decreases, but the probability that a trade moves the price decreases significantly. While the last mechanism is able to counterbalance the persistence of order flow and restore efficiency and diffusivity, the first acts in opposite direction. We introduce a statistical order book model where the persistence of the order flow is mitigated by adjusting the market order volume to the predictability of the order flow. The model reproduces the diffusive behaviour of prices at all time scales without fine-tuning the values of parameters, as well as the behaviour of most order book quantities as a function of the local predictability of order flow.
New Economics Papers: this item is included in nep-mst
Date: 2014-03, Revised 2014-04
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (6) Track citations by RSS feed
Downloads: (external link)
http://arxiv.org/pdf/1403.0842 Latest version (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1403.0842
Access Statistics for this paper
More papers in Papers from arXiv.org
Series data maintained by arXiv administrators ().