Using monthly returns for over 27,000 stocks from 49 countries over a three-decade period, we show that a multifactor model that includes factor-mimicking portfolios based on momentum and cash flow-to-price captures significant time series variation in global stock returns, and has lower pricing errors and fewer model rejections than the global CAPM or a popular model that uses size and book-to-market factors. We find reliable evidence that the global cash flow-to-price factor is related to a covariance risk model. In contrast, we reject the covariance risk model in favor of a characteristic model for size and book-to-market factors.
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