A motif-based decomposition of quantile risk networks shows that local triadic topology and orbit-position diversity carry portfolio-relevant information missed by aggregate connectedness, with motif-based portfolios outperforming benchmarks and positional diversity marking tail transmitters.
Journal of Econometrics 182, 119–134
2 Pith papers cite this work. Polarity classification is still indexing.
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Develops consistent procedures and an efficient alternating least squares algorithm for determining the number of dynamic factors and filter length in dynamic factor models, applied to US macroeconomic time series.
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A Motif-Based Framework for Decomposing Risk Spillovers
A motif-based decomposition of quantile risk networks shows that local triadic topology and orbit-position diversity carry portfolio-relevant information missed by aggregate connectedness, with motif-based portfolios outperforming benchmarks and positional diversity marking tail transmitters.
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Determining the Structure of Dynamic Factor Models
Develops consistent procedures and an efficient alternating least squares algorithm for determining the number of dynamic factors and filter length in dynamic factor models, applied to US macroeconomic time series.