英文标题：
《High-speed detection of emergent market clustering via an unsupervised
parallel genetic algorithm》
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作者：
Dieter Hendricks, Diane Wilcox, Tim Gebbie
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最新提交年份：
2015
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英文摘要：
We implement a master-slave parallel genetic algorithm (PGA) with a bespoke log-likelihood fitness function to identify emergent clusters within price evolutions. We use graphics processing units (GPUs) to implement a PGA and visualise the results using disjoint minimal spanning trees (MSTs). We demonstrate that our GPU PGA, implemented on a commercially available general purpose GPU, is able to recover stock clusters in sub-second speed, based on a subset of stocks in the South African market. This represents a pragmatic choice for low-cost, scalable parallel computing and is significantly faster than a prototype serial implementation in an optimised C-based fourth-generation programming language, although the results are not directly comparable due to compiler differences. Combined with fast online intraday correlation matrix estimation from high frequency data for cluster identification, the proposed implementation offers cost-effective, near-real-time risk assessment for financial practitioners.
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中文摘要：
我们实现了一个主从并行遗传算法（PGA），该算法带有一个定制的对数似然适应度函数，用于识别价格演化中出现的聚类。我们使用图形处理单元（GPU）实现PGA，并使用不相交的最小生成树（MST）将结果可视化。我们证明，我们的GPU PGA在商用通用GPU上实现，能够基于南非市场的一部分股票以亚秒的速度恢复股票集群。这代表了低成本、可扩展并行计算的实用选择，并且比基于优化C的第四代编程语言中的原型串行实现要快得多，尽管由于编译器的差异，结果无法直接比较。结合基于高频数据的快速在线日内相关矩阵估计进行聚类识别，该方案为金融从业者提供了经济高效的近实时风险评估。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Computational Finance 计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
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一级分类：Computer Science 计算机科学
二级分类：Distributed, Parallel, and Cluster Computing 分布式、并行和集群计算
分类描述：Covers fault-tolerance, distributed algorithms, stabilility, parallel computation, and cluster computing. Roughly includes material in ACM Subject Classes C.1.2, C.1.4, C.2.4, D.1.3, D.4.5, D.4.7, E.1.
包括容错、分布式算法、稳定性、并行计算和集群计算。大致包括ACM学科类C.1.2、C.1.4、C.2.4、D.1.3、D.4.5、D.4.7、E.1中的材料。
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一级分类：Computer Science 计算机科学
二级分类：Neural and Evolutionary Computing 神经与进化计算
分类描述：Covers neural networks, connectionism, genetic algorithms, artificial life, adaptive behavior. Roughly includes some material in ACM Subject Class C.1.3, I.2.6, I.5.
涵盖神经网络，连接主义，遗传算法，人工生命，自适应行为。大致包括ACM学科类C.1.3、I.2.6、I.5中的一些材料。
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