Time-variant CAPM: Learning about Factor Loading
نویسنده
چکیده
Adrian and Franzoni (2005) suggest that beta of a stock is determined by the factor loading of its unobservable long-run beta. The fundamental idea behind this model is that investors engage in a learning process of estimating this long-run beta. In this paper, a variation of this model is tested. Instead of estimating long-run beta, investors try to learn about factor loading. Given the long-run beta and the upcoming level of risk, investors must form the optimal factor loading that minimizes the pricing error. The evolution of the factor loading assumes to follow an AR(1) process. The mispricing results are as equally successful as Adrian’s model. The momentum in the optimal factor loading is confirmed. During the transitional business-cycle periods, the factor loading seems to be more volatile.
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