Maximizing equity market sector predictability in a Bayesian time-varying parameter model

The Kalman filter methodology is employed to develop a dynamic sector allocation model for US equities. Bayesian parameter estimation and model selection criteria result in significantly improved sector return predictability over static or rolling parameter specifications. A simple trading strategy illustrates how widely tested financial and economic variables can be used as inputs in for a potentially profitable investment strategy.

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