著者

星野 真広 水田 孝信 八木 勲

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.36, no.5, pp.AG21-G_1-10, 2021-09-01 (Released:2021-09-01)

参考文献数

23

被引用文献数

1

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Recently, most stock exchanges in the U.S. employ maker-taker fees, in which an exchange pays rebates to traders placing make orders (remaining on an order book) and charges fees to traders taking orders (executed immediately). The maker-taker fees will encourage traders to place many make orders and the orders will provide liquidity to the exchange. However, the effects of the maker-taker fees for a total cost of a taking order, including all the charged fees and market impact, are not clear. In this study, we investigated the effects of the maker-taker fees for the total costs of a taking orders using our artificial market model, which is an agent-based model for financial markets. In addition, we examine the difference of market liquidity in the market between with and without a makertaker fee structure. We found that the maker-taker fees encourage the traders to provide liquidity, whereas increase the total costs of taking orders. Furthermore, we found market liquidity improved when the market maker rebates increased.