The Virtue of Sparsity in Complexity
Sparsity or complexity? In modern high-dimensional asset pricing, these are often viewed as competing principles: recent empirical evidence favors richer models, while economic intuition has long favored parsimony. We reconcile this tension by distinguishing capacity sparsity-restrictions on effective model capacity-from factor sparsity-the parsimonious structure of priced risks. Revisiting the benchmark empirical design of Didisheim et al. (2025), we combine nonlinear feature expansions with basis pursuit, using column generation and GPU acceleration to scale estimation to 432 million candidate factors. Reaching this scale reveals a reversal in out-of-sample performance: sparse portfolio...
| Authors | Nima Afsharhajari, Jonathan Yu-Meng Li |
|---|---|
| Primary category | q-fin.GN |
| Published | 18 April 2026 |
| Last updated at source | 21 September 2026 |
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