MARS-Diff: Guarded Residual Diffusion for Leakage-Disciplined Probabilistic Portfolio-Loss Forecasting
Journal of Forecasting, 2026 (SSCI, Scopus)
- Publication Type: Article / Article
- Publication Date: 2026
- Doi Number: 10.1002/for.70219
- Journal Name: Journal of Forecasting
- Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, Periodicals Index Online, ABI/INFORM, Compendex, EconLit, INSPEC, MathSciNet, Public Affairs Index, zbMATH, Business Source Ultimate (EBSCO)
- Keywords: CRPS, portfolio loss, probabilistic forecasting, residual diffusion, scenario generation, tail risk
- Ondokuz Mayıs University Affiliated: Yes
Abstract
This paper develops Masked Asset–Regime Scenario Diffusion (MARS-Diff), a leakage-disciplined framework for probabilistic forecasting of multiday portfolio losses. The framework combines a regularized heterogeneous autoregressive model with exogenous predictors (HAR-X) as its anchor, a train-only masked representation of a high-dimensional asset panel, train-only market-stress conditioning, and conditional residual diffusion. Rather than replacing the anchor, the diffusion correction is admitted only when it weakly improves outer-validation continuous ranked probability score (CRPS); otherwise, the final forecast reuses the anchor scenario distribution exactly. The empirical application begins with a prespecified universe of 50 exchange-traded funds and large-capitalization equities over 2010–2025, of which 49 satisfy the initial-period availability criterion. At the 5-day horizon, generalized autoregressive conditional heteroskedasticity (GARCH) benchmarks—specifically exponential GARCH (EGARCH)- (Formula presented.) and Glosten–Jagannathan–Runkle GARCH (GJR-GARCH)- (Formula presented.) —attain lower CRPS than guarded MARS-Diff and remain significantly better after multiplicity adjustment. The always-active residual diffusion is statistically indistinguishable from the retained anchor, whereas direct conditional diffusion performs significantly worse. At the 10-day horizon, guarded MARS-Diff is statistically indistinguishable in CRPS from the lowest-CRPS asymmetric GARCH benchmarks in the comparison set, whereas always-active residual diffusion and direct conditional diffusion produce significantly higher CRPS. Tail-score evidence is model- and horizon-dependent, and rolling guard diagnostics characterize the admission rule as conservative but imperfect. Controlled experiments further indicate that fitted residual diffusion can improve CRPS in a state-dependent positive-control setting, while producing higher losses in anchor-friendly and financial-stress environments. The results are therefore consistent with interpreting MARS-Diff primarily as an anchored validation-based admission architecture rather than as evidence of uniform diffusion superiority in financial loss forecasting.