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Number of statistical independent factors in arbitrage pricing theory from the perspective of non-Gaussian factor analysis

机译:非高斯因素分析视角下套利定价理论中统计独立因素的数量

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A recently developed factor analytic technique, non-Gaussian factor analysis (NFA) is found to be well-suited for the analysis of classical arbitrage pricing theory (APT). In particular, the model selection ability of NFA is of substantial benefit to the critical task of factor number determination in traditional APT analysis. We aim to demonstrate how a reasonable number of independent factors in APT could be determined by applying the NFA technique. Experimental comparisons with the other two conventional methods are illustrated to confirm the superiority of this new approach.
机译:发现最近开发的因子分析技术非高斯因子分析(NFA)非常适合经典套利定价理论(APT)的分析。特别是,NFA的模型选择能力对于传统APT分析中确定因子数量的关键任务具有实质性的好处。我们旨在证明如何通过应用NFA技术确定APT中合理数量的独立因素。说明了与其他两种常规方法的实验比较,以确认此新方法的优越性。

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