用仿真模型揭示国债市场流动性机制,助力稳定交易
Decoding OTC Government Bond Market Liquidity: An ABM Model for Market Dynamics
- 构建代理模型模拟做市商互动,研究市场微观结构
- 发现做市商多样性提升可增强市场流动性
- 适合关注金融市场监管与量化交易的研究者
场外交易(OTC)政府债券市场以双边交易为特征,对市场稳定性和流动性理解带来独特挑战。本文开发了一个定制化基于代理的模型(ABM),模拟典型政府债券市场中做市商的交互行为。模型聚焦于二级市场中流动性与稳定性动态,尤其针对澳大利亚和英国等集中型市场。通过仿真,验证了提升市场稳定性的若干假设,重点考察了代理多样性、做市成本及客户基数大小的影响。结果表明,更高的代理多样性有助于提升市场流动性,降低做市成本可增强整体市场稳定性。该模型在无价格透明度条件下模拟交易,揭示微观结构因素如何影响宏观市场表现。本研究为计算金融领域提供新视角,借助计算智能技术深入解析政府债券市场的基本运行机制,为学术界与实务界提供可操作的洞见。
原文摘要 · Abstract (English)
The over-the-counter (OTC) government bond markets are characterised by their bilateral trading structures, which pose unique challenges to understanding and ensuring market stability and liquidity. In this paper, we develop a bespoke ABM that simulates market-maker interactions within a stylised government bond market. The model focuses on the dynamics of liquidity and stability in the secondary trading of government bonds, particularly in concentrated markets like those found in Australia and the UK. Through this simulation, we test key hypotheses around improving market stability, focusing on the effects of agent diversity, business costs, and client base size. We demonstrate that greater agent diversity enhances market liquidity and that reducing the costs of market-making can improve overall market stability. The model offers insights into computational finance by simulating trading without price transparency, highlighting how micro-structural elements can affect macro-level market outcomes. This research contributes to the evolving field of computational finance by employing computational intelligence techniques to better understand the fundamental mechanics of government bond markets, providing actionable insights for both academics and practitioners.
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