《Visualizing the Invisible Hand of Markets: Simulating complex dynamic
economic interactions》
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作者:
Klaus Jaffe
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最新提交年份:
2015
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英文摘要:
In complex systems, many different parts interact in non-obvious ways. Traditional research focuses on a few or a single aspect of the problem so as to analyze it with the tools available. To get a better insight of phenomena that emerge from complex interactions, we need instruments that can analyze simultaneously complex interactions between many parts. Here, a simulator modeling different types of economies, is used to visualize complex quantitative aspects that affect economic dynamics. The main conclusions are: 1- Relatively simple economic settings produce complex non-linear dynamics and therefore linear regressions are often unsuitable to capture complex economic dynamics; 2- Flexible pricing of goods by individual agents according to their micro-environment increases the health and wealth of the society, but asymmetries in price sensitivity between buyers and sellers increase price inflation; 3- Prices for goods conferring risky long term benefits are not tracked efficiently by simple market forces. 4- Division of labor creates synergies that improve enormously the health and wealth of the society by increasing the efficiency of economic activity. 5- Stochastic modeling improves our understanding of real economies, and didactic games based on them might help policy makers and non specialists in grasping the complex dynamics underlying even simple economic settings.
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中文摘要:
在复杂系统中,许多不同的部分以不明显的方式相互作用。传统的研究侧重于问题的几个或单个方面,以便使用可用的工具进行分析。我们需要从许多复杂的相互作用中获得更好的洞察力。这里,一个模拟不同类型经济的模拟器被用来可视化影响经济动态的复杂数量方面。主要结论是:1——相对简单的经济环境产生复杂的非线性动态,因此线性回归往往不适合捕捉复杂的经济动态;2.个体代理人根据其微观环境对商品进行灵活定价,增加了社会的健康和财富,但买家和卖家之间价格敏感性的不对称增加了价格通胀;3-简单的市场力量无法有效跟踪具有风险长期利益的商品价格。4.分工产生协同效应,通过提高经济活动的效率,极大地改善社会的健康和财富。5-随机建模提高了我们对实体经济的理解,基于它们的说教游戏可能有助于决策者和非专家掌握即使是简单经济环境下的复杂动态。
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分类信息:
一级分类:Computer Science 计算机科学
二级分类:Multiagent Systems 多智能体系统
分类描述:Covers multiagent systems, distributed artificial intelligence, intelligent agents, coordinated interactions. and practical applications. Roughly covers ACM Subject Class I.2.11.
涵盖多Agent系统、分布式人工智能、智能Agent、协调交互。和实际应用。大致涵盖ACM科目I.2.11类。
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一级分类:Quantitative Finance 数量金融学
二级分类:General Finance 一般财务
分类描述:Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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