Limit Order Strategic Placement with Adverse Selection Risk and the Role of Latency

書誌事項

公開日
2017-03
DOI
  • 10.1142/s2382626617500095
公開者
World Scientific Pub Co Pte Lt

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<jats:p> This paper is split in three parts: first, we use labeled trade data to exhibit how market participants’ decisions depend on liquidity imbalance; then, we develop a stochastic control framework where agents monitor limit orders, by exploiting liquidity imbalance, to reduce adverse selection. For limit orders, we need optimal strategies essentially to find a balance between fast execution and avoiding adverse selection: if the price has chances to go down, the probability to be filled is high, but it is better to wait a little more to get a better price. In a third part, we show how the added value of exploiting liquidity imbalance is eroded by latency: being able to predict future liquidity consuming flows is of less use if you do not have enough time to cancel and reinsert your limit orders. There is thus a rationale for market makers to be as fast as possible to reduce adverse selection. Latency costs of our limit order driven strategy can be measured numerically. </jats:p><jats:p> To authors’ knowledge, this paper is the first to make the connection between empirical evidences, a stochastic framework for limit orders including adverse selection, and the cost of latency. Our work is a first step to shed light on the role played by latency and adverse selection in optimal limit order placement. </jats:p>

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