Impact of Position-Based Market Makers to Shares of Markets' Volumes -- an Artificial Market Approach

Abstract

keywords: market maker, competition among markets, share of trading volume, high frequency trading, multi agent-based simulation SummaryWe analyzed the impact of position-based market maker, which tries to maintain its neutral position, to the competition among stock exchanges by an artificial market simulation approach. In the previous study, we built an artificial market model and investigated for the impact of non-position-based market maker's spread to the markets' shares of trading volumes. However it had the serious problem that the non-position-based market maker is too simple to manage its own position properly and so we could not judge weather the result of previous study is correct or not. Thus in this study, we made a position-based market maker and explored the competition, in terms of taking markets' shares of trading volumes, between two artificial financial markets that have exactly the same specifications except existing a market maker, the non-position-based market maker or the position-based market maker. As a result, we found that the position-based market maker can acquire the share of trading volumes from the competitor even though its spread is bigger than bid-offer-spread of the competitor. Moreover, we revealed that position-based market maker can get a profit even in the situation that its spread or tick sizes of the stock exchanges are small. In addition to that, position-based market maker made a profit in almost all experiments which we conducted in this research by changing its spread and tick sizes of markets. At last, we confirmed that position-based market maker can manage its position properly compared to non-position-based market maker. In conclusion, the position-based market maker can not only supply liquidity to stock exchanges and contribute to acquire the share from the competitor as well as the non-position-based market maker does, but also manage its own position properly and make a profit.

Analysis of the Impact of High-Frequency Trading on Artificial Market Liquidity

“…We seek to investigate the relationship among the four market liquidity indicators by changing the parameters. For simplicity, the HFT agent is modeled on the basis of Kusada et al [52], which is a market making strategy. The model constructed in the present work has a single risk asset associated with trading, which is simply referred to as an asset, and a non-risk asset is referred to as cash.…”

“…Next, we will explain the HFT agent model in detail. Among the market making strategy models that have been proposed [51], [52], [55], we modeled the HFT agent on the basis of Kusada et al [52] for simplicity. There is only one HFT agent.…”

“…That is, when the HFT agent has a long position, which means the agent buys and holds some amount of an asset, its buy and sell order prices are set lower so that its sell order matches an order from normal agents easier than its buy order. On the other hand, when the HFT agent has a short position, which means the agent short-sells the asset, its buy and sell order prices are set higher so that its buy order matches an order from normal agents easier than its sell order [55], [56]. Let the base spread of the HFT agent and the coefficient of its position (its initial value is set based on Kusaka et al [55] as 5.0 × 10 −8 ) be θ h and w h .…”

“…On the other hand, when the HFT agent has a short position, which means the agent short-sells the asset, its buy and sell order prices are set higher so that its buy order matches an order from normal agents easier than its sell order [55], [56]. Let the base spread of the HFT agent and the coefficient of its position (its initial value is set based on Kusaka et al [55] as 5.0 × 10 −8 ) be θ h and w h . Let the best-bid, the best-ask, its basic order price, its buy order price, its sell order price at time t, and the HFT's position between time t and t + 1 be P t bb , P t ba , P t bv,h , P t bo,h , P t so,h , and s t h , respectively.…”

“…When the sell (buy) order price of the HFT agent is lower (higher) than the best-bid (best-ask), the HFT agent's order becomes a market order. Therefore, if the following conditions are satisfied, the buy and sell order prices of the HFT agent are changed [52]. That is, if P t bo,h ≥ P t ba , then P t bo,h = P t ba − P (13) P t so,h = P t ba − P…”