Learn the measure, estimate the moment: machine-learned drivers in dynamic conditional correlation models
Combining machine-learned forecasts of realized measures with dynamic conditional correlation models improves correlation matrix forecasts, producing valid predictions and beating realized-driver baselines across multiple horizons.
Featured in No. 133 on 2 Oct 2026 · 2 days after release
- Released
- 30 Sep 2026
- First featured
- No. 133 · 2 Oct 2026
- Published in
- Not yet, as far as Semantic Scholar knows
- Fanfare
- 2 of 5
- Identifier
- RePEc:cdf:wpaper:2026/12
- Authors
- Yongdeng Xu
Citations and venue from Semantic Scholar (ODC-BY), refreshed weekly. Summary: Quant Letter (CC BY 4.0).