Suppose a fund manager uses predictors in changing portfolio allocations over time. How does predictability translate into portfolio decisions? To answer this question, we derive a new Bayesian time-varying CAPM-based beta model, where managers modulate the systematic risk in part by observing how the benchmark returns are related to some set of imperfect predictors, and in part reflecting their own information set. Based on single and equally weighted portfolios of U.S. domestic equity mutual funds over the 1990–2014 period, we estimate our model providing new evidence on mutual fund dynamics: (1) beta dynamics are significantly affected by economic variables, although (2) managers seem not to care about benchmark sensitivities toward predictors in choosing their instrument exposure; and (3) instruments play a key role on the long run.

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