On the Ordering of Dynamic Principal Components and the Implications for Portfolio Analysis
33 Pages Posted: 17 May 2022
Date Written: April 26, 2022
Abstract
When principal component analysis (PCA) is used on a rolling or conditional setting, ordering and incoherence issues may emerge. We provide empirical evidence supporting this claim and introduce an algorithm that allows dynamic re-ordering of the principal components (PCs). We provide additional results that shed light on the consequences of incoherence when analyzing the link between PCs and macroeconomic risk factors, with a focus on the COVID-19 pandemic period. When PCs are optimally re-ordered, the role of factors emerges more clearly, with relevant implications for risk management.
Keywords: principal component analysis, dynamic principal component GARCH, risk factors, principal components ordering
JEL Classification: C38, C32, C58, G11, G17
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