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This randomized trial develops a novel alpha test for conditional multi-factor models, suggesting improved detection capabilities.
In this paper, a novel test, called the maximum conditional alpha (MCA) test, which enhances the testing power for detecting alpha in linear multi-factor models, is proposed. This test is specifically designed for conditional multi-factor models with time-varying coefficients, where the number of test assets (N ) exceeds the number of observations (T ) and the alternative hypothesis is a sparse vector, meaning that only a few components violate the null hypothesis.
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Zhang et al. (2023) studied this question.
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