Trend momentum utilizes moving average prices and returns respectively of various time lengths 3 days, 5 days, 10 days, 20 days, 50 days, 100 days and 200 days to capture information which is justified by a proposed general equilibrium model.
Stocks that have high forecasted expected returns from the cross-section regression yield higher future returns on average, and stocks that have low forecasted expected returns tend to yield lower future returns on average.
In order to calculate trends, trend momentum focuses on the moving averages of prices and returns. Also different from price momentum, trend momentum looks at more time cadences.
We applied trend momentum metrics to a universe of the largest 500 US equities by market capitalization and ranked each stock on its overall trend momentum. We then divided the universe into 10 quantiles of stocks, with the top quantile (Q_10) representing the highest trend momentum stocks and the bottom quantile (Q_1) representing the lowest trend momentum stocks.
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