摘要翻译：
我们提出了一个简单的基于Agent的模型来研究泡沫的发展和随之而来的崩溃，并研究它们的邻近触发因素如何与其基本机制有关，反之亦然。我们的代理商根据他们对未来价格变动的看法进行投资，这是基于三个信息来源:(i)公共信息，即新闻，(ii)来自他们“友谊”网络的信息，(iii)私人信息。我们的有限理性代理人不断调整他们的交易策略以适应当前的市场机制，并根据其最近的预测表现在交易决策中对这些信息来源进行加权。我们发现泡沫源于随机的积极消息的幸运条纹，由于这些消息对代理人策略的反馈机制，泡沫发展成为一个短暂的集体羊群机制。在这种自我放大的繁荣之后，价格已经达到了一个不可持续的高值，被崩溃所纠正，这使价格甚至低于其基本价值。这些成分为金融市场中记录的过度波动提供了一个简单的机制。矛盾的是，正是投资者试图适应当前的市场制度，导致价格波动性急剧放大。两个主导机制（适应和模仿）形成了一个正反馈循环，它们通过相互加强，导致泡沫和崩溃。该模型在一个单一框架内简单地调和了关于崩盘起源的两个相反（羊群相对于基本面）建议，并证明了在回报分布中存在两个群体的合理性，举例说明了崩盘在性质上不同于其他价格波动的概念。
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英文标题：
《How to grow a bubble: A model of myopic adapting agents》
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作者：
Georges Harras, Didier Sornette
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最新提交年份：
2010
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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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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一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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英文摘要：
  We present a simple agent-based model to study the development of a bubble and the consequential crash and investigate how their proximate triggering factor might relate to their fundamental mechanism, and vice versa. Our agents invest according to their opinion on future price movements, which is based on three sources of information, (i) public information, i.e. news, (ii) information from their "friendship" network and (iii) private information. Our bounded rational agents continuously adapt their trading strategy to the current market regime by weighting each of these sources of information in their trading decision according to its recent predicting performance. We find that bubbles originate from a random lucky streak of positive news, which, due to a feedback mechanism of these news on the agents' strategies develop into a transient collective herding regime. After this self-amplified exuberance, the price has reached an unsustainable high value, being corrected by a crash, which brings the price even below its fundamental value. These ingredients provide a simple mechanism for the excess volatility documented in financial markets. Paradoxically, it is the attempt for investors to adapt to the current market regime which leads to a dramatic amplification of the price volatility. A positive feedback loop is created by the two dominating mechanisms (adaptation and imitation) which, by reinforcing each other, result in bubbles and crashes. The model offers a simple reconciliation of the two opposite (herding versus fundamental) proposals for the origin of crashes within a single framework and justifies the existence of two populations in the distribution of returns, exemplifying the concept that crashes are qualitatively different from the rest of the price moves.
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PDF链接：
https://arxiv.org/pdf/0806.2989