Diebold-Mariano test statistic converges to a stable non-Gaussian limit under infinite-variance loss differentials, and subsampling yields valid inference without estimating long-run variance or tail index.
Journal of Business & Economic Statistics , volume=
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A Lasso-based screening step followed by low-dimensional mean-variance optimization on the selected assets improves high-dimensional portfolio construction, with a defactoring extension for strong factors.
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Heavy Tails and Predictive Ability Testing
Diebold-Mariano test statistic converges to a stable non-Gaussian limit under infinite-variance loss differentials, and subsampling yields valid inference without estimating long-run variance or tail index.
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Post-Screening Portfolio Selection
A Lasso-based screening step followed by low-dimensional mean-variance optimization on the selected assets improves high-dimensional portfolio construction, with a defactoring extension for strong factors.