Abstract
Stock factor returns exhibit greater predictability from the weighted least squares (WLS) estimator of autoregressions with time-varying volatility. The predictability transmits into superior mean-variance optimal portfolio performance that is hardly achieved by other strategies that utilize volatility timing and return predictability. This outperformance can be interpreted through an empirically weak factor risk-return relation. A WLS-based systematic factor long-short strategy subsumes the stock momentum factor, industry momentum and factor momentum, and produces sizable excess returns. The outperformance is not limited to particular ways of portfolio formation, which testifies that the WLS-based strategy fully exploits predictability.
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