Discovery of time-inconsecutive co-movement patterns of foreign currencies using an evolutionary biclustering method
Discovery of time-inconsecutive co-movement patterns of foreign currencies using an evolutionary biclustering method
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DOI：
10.1016/j.amc.2011.10.011
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发表时间：
2011-12
期刊：
影响因子：
--
通讯作者：
Qinghua Huang
中科院分区：
文献类型：
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作者：
Qinghua Huang
本文提出了一种进化双聚类算法来发现不同汇率的非连续共同运动模式。双簇（即具有行子集和列子集的子矩阵）的行/列不一定是连续的。在行和/或列上具有恒定值的典型双聚类表示为高维空间中的超平面，并且使用遗传算法确定超平面的系数。检测到的双聚类显示了一组货币在不连续时间段内的共同移动行为，表明这些货币在某些特定时间段内以不同的方式移动。在实验中，我们将这些模式与地理上紧密的经济联系联系起来，并找出名义汇率与经济状况之间的对应关系。这些发现对投资外汇很有帮助。
This paper proposes an evolutionary biclustering algorithm to discover inconsecutive co-movement patterns of different foreign exchange rates. The rows/columns of a bicluster (i.e. a submatrix with a subset of rows and a subset of columns) are not necessarily consecutive. A typical bicluster with constant values on rows and/or columns is represented as a hyperplane in a high-dimensional space and the coefficients of the hyperplane are determined using a genetic algorithm. A detected bicluster demonstrates the co-moving behaviors of a subset of currencies in inconsecutive time periods, indicating that the currencies moved in different manners in some specific time periods. In our experiments, we relate these patterns to the geographically close economic connections and find out the correspondence between the nominal exchange rates and the economic conditions. The findings are useful as a guide for investing foreign currencies.