Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters

Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters

The inhomogeneity of the cross-sectional distribution of realized assets’ volatility is explored and used to build a novel class of GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models. The inhomogeneity of the cross-sectional distribution of realized volatility is captured by a...

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Bibliographic Details
Main Authors: Pietro Coretto, Michele La Rocca, Giuseppe Storti
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Journal of Risk and Financial Management
Subjects:
GARCH models
realized volatility
model-based clustering
robust clustering
Online Access:https://www.mdpi.com/1911-8074/13/4/64

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