Proposes fMSV framework using factor decomposition, two-stage estimation, and derived asymptotics for high-dimensional multivariate stochastic volatility, tested via simulations and portfolio applications.
Forecasting Using Principal Components From a Large Number of Predictors
2 Pith papers cite this work. Polarity classification is still indexing.
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A four-factor dynamic factor model from global macro variables explains cross-sectional equity returns in ten G20 countries better than the single-factor CAPM.
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Factor multivariate stochastic volatility models of high dimension
Proposes fMSV framework using factor decomposition, two-stage estimation, and derived asymptotics for high-dimensional multivariate stochastic volatility, tested via simulations and portfolio applications.
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Pricing Global Macroeconomic Risk in Equity Markets: Evidence from Selected G20 Economies
A four-factor dynamic factor model from global macro variables explains cross-sectional equity returns in ten G20 countries better than the single-factor CAPM.