摘要翻译：
金融和经济史上充斥着泡沫和崩溃、繁荣和萧条、危机和各种剧变。理解这些事件的起源可以说是经济理论中最重要的问题之一。在本文中，我们回顾了最近在决策模型中包括异质性和相互作用的努力。我们认为随机场伊辛模型(RFIM)确实为解释许多导致突然破裂和危机的集体社会经济现象提供了一个统一的框架。我们讨论了不同的模型，它们可以捕捉潜在的不稳定的自我参照反馈环，这些反馈环是由羊群效应（即对同行的参照）或趋势效应（即对过去的参照）引起的，并解释了标准模型中缺少的一些现象学。我们讨论了这些模型的一些经验可检验的预测，例如类RFIM羊群效应的鲁棒签名，或者投票模式的空间相关性的对数衰减。受统计物理方法的启发，最引人注目的结果之一是亚当·斯密的看不见的手在解决简单的协调问题时可能会严重失败。我们还坚持时间尺度的问题，在某些情况下，时间尺度可能非常长，并阻止达到社会最优平衡。作为一个理论挑战，需要研究违反决策规则的所谓“详细平衡”，以确定基于现有模型（都假设详细平衡）的结论是否确实稳健和通用。
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英文标题：
《Crises and collective socio-economic phenomena: simple models and
  challenges》
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作者：
Jean-Philippe Bouchaud (Capital Fund Management)
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最新提交年份：
2012
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分类信息：

一级分类：Physics        物理学
二级分类：Statistical Mechanics        统计力学
分类描述：Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变，热力学，场论，非平衡现象，重整化群和标度，可积模型，湍流
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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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英文摘要：
  Financial and economic history is strewn with bubbles and crashes, booms and busts, crises and upheavals of all sorts. Understanding the origin of these events is arguably one of the most important problems in economic theory. In this paper, we review recent efforts to include heterogeneities and interactions in models of decision. We argue that the Random Field Ising model (RFIM) indeed provides a unifying framework to account for many collective socio-economic phenomena that lead to sudden ruptures and crises. We discuss different models that can capture potentially destabilising self-referential feedback loops, induced either by herding, i.e. reference to peers, or trending, i.e. reference to the past, and account for some of the phenomenology missing in the standard models. We discuss some empirically testable predictions of these models, for example robust signatures of RFIM-like herding effects, or the logarithmic decay of spatial correlations of voting patterns. One of the most striking result, inspired by statistical physics methods, is that Adam Smith's invisible hand can badly fail at solving simple coordination problems. We also insist on the issue of time-scales, that can be extremely long in some cases, and prevent socially optimal equilibria to be reached. As a theoretical challenge, the study of so-called "detailed-balance" violating decision rules is needed to decide whether conclusions based on current models (that all assume detailed-balance) are indeed robust and generic.
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PDF链接：
https://arxiv.org/pdf/1209.0453