Leveraging asymmetric price limits for financial stability in industrial applications: An agent-based model

IF 8.2 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers in Industry Pub Date : 2024-10-30 DOI:10.1016/j.compind.2024.104197
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Abstract

How to upgrade business processes to improve production efficiency is an ongoing concern in industrial research. While previous studies have extensively examined various prioritization schemes at each stage of the business process, there has been a lack of investigation into the financial resources required for their implementation. The attainment of sufficient and stable financial support necessitates stability in stock prices, making the control of significant volatility in stock markets a critical issue. This study examines the effectiveness of three design schemes of price limit policy, a prevalent policy that intends to control significant volatility in financial markets and stabilize the market. Utilizing a heterogeneous agent-based model that simulates trading agents' processes of updating strategies through genetic programming algorithms and incorporates specialized designs for price limit policies, this study demonstrates that an asymmetric limit policy—consisting solely of a lower price limit (without an upper price limit)—can significantly enhance market quality by achieving lower volatility, higher market liquidity and better price effectiveness. Furthermore, we investigate the applicable conditions of asymmetric price limits. The findings suggest that an extremely restrictive limit range could lead to volatility spillover, while a 10 % range is deemed appropriate for achieving better efficiency. Additionally, the asymmetric price limit mechanism has the potential to significantly reduce market volatility by up to 12.5 % in volatile, low liquidity, and low price efficiency markets, which aligns with the declining range from bubble-crash periods to stable periods in the Chinese stock market. These results are further supported by sensitivity analysis.
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利用非对称限价促进工业应用中的金融稳定:基于代理的模型
如何升级业务流程以提高生产效率是工业研究中一直关注的问题。以往的研究广泛探讨了业务流程各阶段的各种优先排序方案,但对实施这些方案所需的财政资源却缺乏研究。要获得充足而稳定的资金支持,就必须稳定股票价格,因此控制股票市场的大幅波动成为一个关键问题。限价政策是一种旨在控制金融市场大幅波动并稳定市场的普遍政策,本研究考察了限价政策三种设计方案的有效性。本研究利用基于异质代理的模型,通过遗传编程算法模拟交易代理的策略更新过程,并结合限价政策的专门设计,证明了非对称限价政策--只包含价格下限(没有价格上限)--可以通过实现更低的波动性、更高的市场流动性和更好的价格有效性来显著提高市场质量。此外,我们还研究了非对称限价的适用条件。研究结果表明,极其严格的限价范围可能会导致波动溢出,而 10% 的限价范围则被认为适合实现更高的效率。此外,在波动大、流动性低和价格效率低的市场中,非对称限价机制有可能显著降低市场波动率,最高可达 12.5%,这与中国股市从泡沫崩溃期到稳定期的下降区间相吻合。敏感性分析进一步支持了这些结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computers in Industry
Computers in Industry 工程技术-计算机:跨学科应用
CiteScore
18.90
自引率
8.00%
发文量
152
审稿时长
22 days
期刊介绍: The objective of Computers in Industry is to present original, high-quality, application-oriented research papers that: • Illuminate emerging trends and possibilities in the utilization of Information and Communication Technology in industry; • Establish connections or integrations across various technology domains within the expansive realm of computer applications for industry; • Foster connections or integrations across diverse application areas of ICT in industry.
期刊最新文献
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