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An Order-Driven Agent-Based Artificial Stock Market to Analyze Liquidity Costs of Market Orders in the Taiwan Stock Market

机译：基于订单驱动代理的人工股票市场分析台湾股票市场中市场订单的流动性成本

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We developed an order-driven agent-based artificial stock market to analyze the liquidity costs of market orders in the Taiwan Stock Market (TWSE). The agent-based stock market was based on the DFGIS model proposed by Daniels, Farmer, Gillemot, Iori and Smith [2]. When tested on 10 stocks and securities in the market, the model-simulated liquidity costs were higher than those of the TWSE data. We identified some possible factors that have contributed to this result: 1) the overestimated effective market order size; 2) the random market orders arrival time designed in the DFGIS model; and 3) the zero-intelligence of the artificial agents in our model. We continued improving the model so that it could be used to study liquidity costs and to devise liquidation strategies for stocks and securities traded in the Taiwan Stock Market.

机译：我们开发了基于订单驱动的基于代理的人工股票市场，以分析台湾股票市场（TWSE）中市场订单的流动性成本。基于代理的股票市场是基于Daniels，Farmer，Gillemot，Iori和Smith [2]提出的DFGIS模型。当对市场上的10只股票和证券进行测试时，模型模拟的流动性成本高于TWSE数据的流动性成本。我们确定了导致这一结果的一些可能因素：1）高估了有效的市场订单规模； 2）DFGIS模型中设计的随机市场订单到达时间； 3）我们模型中的人工代理的零智能。我们继续改进该模型，以便将其用于研究流动性成本并为台湾股票市场上交易的股票和证券设计清算策略。

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《Natural computing in computational finance》|2010年|p.163-179|共17页
会议地点 Istanbul(TR);Istanbul(TR)
作者
Yi-Ping Huang; Shu-Heng Chen; Min-Chin Hung; Tina Yu;
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作者单位

Department of Financial Engineering and Actuarial Mathematics, Soochow University, Taipei, Taiwan;

AI-ECON Research Center, Department of Economics, National Chengchi University, Taipei, Taiwan;

Department of Financial Engineering and Actuarial Mathematics, Soochow University, Taipei, Taiwan;

Department of Computer Science, Memorial University of Newfoundland, St John's, NL A1B 3X5, Canada;

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正文语种 eng
中图分类人工智能理论;
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1. Liquidity cost of market orders in the Taiwan Stock Market: A study based on an order-driven agent-based artificial stock market [J] . Yi-Ping Huang, Shu-Heng Chen, Ming-Chin Hung, International Review of Financial Analysis . 2012,第Juna期

机译：台湾股票市场中市场订单的流动性成本：基于以订单驱动的基于代理的人工股票市场的研究
2. Liquidity and stock returns: Evidence from a pure order-driven market using a new liquidity proxy [J] . Ben R. Marshall International Review of Financial Analysis . 2006,第1期

机译：流动性和股票收益：使用新的流动性代理从纯粹的订单驱动市场得出的证据
3. Corporate governance and stock liquidity dimensions: Panel evidence from pure order-driven Australian market [J] . Ali Searat, Liu Benjamin, Su Jen Je International review of economics & finance . 2017,第JULa期

机译：公司治理和股票流动性维度：来自纯订单驱动的澳大利亚市场的面板证据
4. An Order-Driven Agent-Based Artificial Stock Market to Analyze Liquidity Costs of Market Orders in the Taiwan Stock Market [C] . Yi-Ping Huang, Shu-Heng Chen, Min-Chin Hung, European workshop on evolutionary computation in finance and economics . 2011

机译：一个基于秩序驱动的代理人的人工股票，分析台湾股市市场订单的流动性成本
5. Taiwanese high -tech stocks: Using artificial neural networks to test weak -form market efficiency in the Taiwan Electronic Index and to develop an evaluation model of investment strategy in Taiwanese stock markets. [D] . Shih, Kuang-Hsun. 2003

机译：台湾高科技股票：使用人工神经网络在台湾电子指数中测试弱形式的市场效率，并开发台湾股票市场的投资策略评估模型。
6. Nonlinear relationship between money market rate and stock market liquidity in China: A multifractal analysis [O] . Yihong Sun, Xuemei Yuan, J E. Trinidad Segovia, 2021

机译：中国货币市场率与股票市场流动性的非线性关系：多重分析
7. We develop a sequential trade model of Iceberg order execution in a limit order book. The Iceberg-trader has the freedom to expose his trading intentions or (partially) shield the true order size against other market participants. Order exposure can cause drastic market reactions (“market impact”) in the end leading to higher transaction costs. On the other hand the Iceberg trader faces a loss-in-priority when he hides his intentions, as most electronic limit order books penalize the usage of hidden liquidity. Thus the Iceberg-trader is faced with the problem to find the right trade-off. Our model provides optimal exposure strategies for Iceberg traders in limit order book markets. In particular, we provide a range of analytical statements that are in line with recent empirical findings on the determinants of trader’s exposure strategies. In this framework, we also study the market impact also market impact of limit orders. We provide optimal exposure profiles for a range of hightech stocks from the US SP500 and how they scale with the state-of-the-book. We finally test the Iceberg’s performance against the limit orders and find that Iceberg orders can significantly enhance trade performance by up to 60. [O] . Gökhan Cebiro˜glu, Ulrich Horst 100

机译：我们在限价订单簿中开发了冰山订单执行的顺序交易模型。 Iceberg-trader可以自由地揭露他的交易意图，或者（部分）屏蔽其他市场参与者的真实订单规模。订单暴露最终会导致市场反应激烈（“市场影响”），导致交易成本上升。另一方面，冰山交易员在隐藏他的意图时面临优先权损失，因为大多数电子限价订单都会惩罚隐藏流动性的使用。因此，冰山商人面临着找到正确权衡的问题。我们的模型为限额订单市场中的冰山交易者提供了最佳的风险敞口策略。特别是，我们提供了一系列分析性陈述，这些陈述与最近关于交易者暴露策略决定因素的实证研究结果一致。在此框架下，我们还研究了市场影响以及限价订单的市场影响。我们为来自美国标准普尔500指数的一系列高科技股票提供最佳曝光配置文件，以及它们如何随着本书的规模扩展。我们最终根据极限订单测试了冰山的表现，发现冰山订单可以显着提升贸易业绩高达60％。

An Order-Driven Agent-Based Artificial Stock Market to Analyze Liquidity Costs of Market Orders in the Taiwan Stock Market

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