摘要翻译：
我们将41种货币（包括黄金）的汇率收益分解为它们的符号和振幅分量。然后用一个共同的基础货币对所有汇率进行分组，分别为每个分组构造最小生成树，并分析这些树的性质。我们表明，就核心网络结构而言，符号时间序列和振幅时间序列都具有相似的相关性质。然而，存在着有趣的外围差异，这可能会打开一个新的视角来看待外汇动态。
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英文标题：
《Sign and amplitude representation of the forex networks》
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作者：
Sylwia Gworek, Jaroslaw Kwapien, Stanislaw Drozdz
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最新提交年份：
2009
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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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英文摘要：
  We decompose the exchange rates returns of 41 currencies (incl. gold) into their sign and amplitude components. Then we group together all exchange rates with a common base currency, construct Minimal Spanning Trees for each group independently, and analyze properties of these trees. We show that both the sign and the amplitude time series have similar correlation properties as far as the core network structure is concerned. There exist however interesting peripheral differences that may open a new perspective to view the Forex dynamics.
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PDF链接：
https://arxiv.org/pdf/0911.3045