A Study on Optimal Limit Order Strategy Using Multi-Period Stochastic Programming Considering Nonexecution Risk

Shumpei Sakurai () and Norio Hibiki ()
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Shumpei Sakurai: Tokyo Stock Exchange, Inc.
Norio Hibiki: Keio University

A chapter in Intelligent Engineering and Management for Industry 4.0, 2022, pp 77-89 from Springer

Abstract: Abstract Our paper discusses optimal trading strategy of stock using limit orders considering nonexecution risk for institutional investors. The limit order could satisfy their needs due to the smaller market impact than market order. However, the limit order has risk of not being filled which is called nonexecution risk. According to some empirical analyses, executing a larger amount of limit order is more difficult than a small amount, and this relationship should be considered in the execution strategy. We estimate the execution probability distribution empirically. The reorder strategy proposed in our paper allows investors to replace nonexecuted limit orders as new limit orders, and nonexecuted amounts at maturity will be executed through market orders. The strategy is determined considering the trade-off among nonexecution risk, market impact, and timing risk. We find the optimal strategy can reduce the execution cost with the nonexecution risk.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-94683-8_8

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DOI: 10.1007/978-3-030-94683-8_8

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