A Filtered Historical Simulation Approach to Macroeconomic Scenario Analysis

Kaname Hirano
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Abstract

This paper applies a filtered historical simulation (FHS) approach to macroeconomic scenario generation. The aim of the approach is to generate more plausible macroeconomic scenarios than other macroeconomic scenario models such as the global vector autoregression (GVAR) model. This paper shows how to handle the relation between macroeconomic statistics and financial market factors in a filtered historical simulation approach. The application fields of the approach are integrated risk management, stress testing, business planning and so on.
宏观经济情景分析的过滤历史模拟方法
本文将滤波历史模拟(FHS)方法应用于宏观经济情景生成。该方法的目的是生成比其他宏观经济情景模型(如全局向量自回归(GVAR)模型)更合理的宏观经济情景。本文展示了如何处理宏观经济统计与金融市场因素之间的关系,在一个过滤的历史模拟方法。该方法的应用领域包括综合风险管理、压力测试、业务规划等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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