构建英国金融状况指数:比较分析

Sheng Zhu, Ella Kavanagh, Niall O’Sullivan
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引用次数: 1

摘要

我们使用少量的金融指标来研究英国金融状况指数(FCI)的最优成分变量加权方法。选择最优加权模型的标准集中在指数预测经济活动的能力上。我们开发了一个“两步”过程作为一种新的加权和方法,并表明它在创建FCI方面优于其他现有的加权和模型。为了比较起见,我们使用时变参数因子增强向量自回归(TVP-FAVAR)创建另一个FCI,随机波动模型作为主成分方法。结果表明,就预测经济发展的目的而言,TVP-FAVAR模型是创建FCI的最佳变量加权模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Constructing A Financial Conditions Index for the United Kingdom: A Comparative Analysis
We investigate the optimal constituent variable weighting method for a UK financial conditions index (FCI) using a small number of financial indicators. The criterion for choosing the optimal weighting model concentrates on the index’s ability to predict economic activity. We develop a ‘two-step’ process as a new weighted-sum method and show that it is superior to other existing weighted-sum models in creating an FCI. For comparative purposes, we create another FCI using a time-varying parameter factor-augmented vector autoregressive (TVP-FAVAR) with stochastic volatility model as a principal-component method. The results suggest that the TVP-FAVAR model is the best variable-weighting model to create an FCI in relation to its purpose of forecasting developments in the economy.
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