I evaluate the out-of-sample predictability of several major indicators for bull and bear markets in monthly S&P 500 series with three quadratic probability score components: calibration, sharpness, and uncertainty. I find that uncertainty limits the trend characterization and thus provides a new perspective from which to identify bull and bear markets. I also find that sharpness plays a key role in determining portfolio returns. Trading strategies that capitalize on sharpness generate higher Sharpe ratios and portfolio returns. The Aruoba–Diebold–Scotti business conditions index is the most profitable indicator for both medium- and long-term trends.
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