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This analysis develops a Bayesian dynamic state-state factor model to capture and forecast time-varying risk premia in U.S. equity markets, integrating both Fama-French factors and macro-level indicators from Bloomberg. The study builds on the foundational work of Fama and French (1993) and Carhart (1997) by allowing for dynamic factor exposures.
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dylanlucko/bayesian_dynamic_factor_model
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This analysis develops a Bayesian dynamic state-state factor model to capture and forecast time-varying risk premia in U.S. equity markets, integrating both Fama-French factors and macro-level indicators from Bloomberg. The study builds on the foundational work of Fama and French (1993) and Carhart (1997) by allowing for dynamic factor exposures.
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