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摘要翻译：
考虑了无标度网络按优先附着方案的演化，给出了表征度分布的指数有上下界的条件。我们的框架是一个代理模型，它是在贸易经济网络的背景下提出的，它表明了临界行为的出现。本文从简要讨论交易网络演化的主要特征出发，证明了对数收益分布具有有界重尾，并导出了相应的有界指数值。最后，我们在模型风险的背景下讨论这些发现。
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英文标题：
《The bounds of heavy-tailed return distributions in evolving complex
networks》
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作者：
Jo\~ao P. da Cruz, Pedro G. Lind
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最新提交年份：
2013
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分类信息：
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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一级分类：Quantitative Finance 数量金融学
二级分类：Risk Management 风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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英文摘要：
We consider the evolution of scale-free networks according to preferential attachment schemes and show the conditions for which the exponent characterizing the degree distribution is bounded by upper and lower values. Our framework is an agent model, presented in the context of economic networks of trades, which shows the emergence of critical behavior. Starting from a brief discussion about the main features of the evolving network of trades, we show that the logarithmic return distributions have bounded heavy-tails, and the corresponding bounding exponent values can be derived. Finally, we discuss these findings in the context of model risk.
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PDF链接：
https://arxiv.org/pdf/1109.2803
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