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Baa spreads gave no clear added weekly Nasdaq variance forecast gain after VIX in a 2016–2025 archive test

We tested whether a Baa corporate bond spread improves next-week Nasdaq Composite variation forecasts after past stock variation and VIX are known. Each forecast used a dated ALFRED archive, an earlier observation cutoff and only past fitting labels. Fixed ridge models used 520 common training weeks. The main test has 483 fresh weeks in 2016–2025. Adding spread level and recent change gave a mean QLIKE loss change of -0.00780, with a 95% paired eight-week block interval from -0.03403 to +0.01396. All planned credit checks gave intervals that include zero. Without 2020, the change was +0.00248. Variance mean squared error was 27.3% higher with credit, with wide uncertainty. Thus the test gives no clear added credit forecast gain in this scope. This is a retrospective test on one price index and one fixed model family. It shares a market sample with earlier SCI work and does not establish a trading profit. The package preserves code, source request records, forecasts, fits, scores, figures, uncertainty estimates, negative results and repeat instructions. Source data and measured outcomes keep their provider terms in separate retained records.

stock risk forecasts · credit spreads · VIX · point-in-time data · chronological test · forecast comparison · negative result

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References

6
  1. doi:10.1093/jjfinec/nbp001
  2. doi:10.1016/j.jeconom.2010.03.034
  3. doi:10.1257/aer.102.4.1692
  4. usesPast VIX values reduced weekly Nasdaq Composite variance forecast loss in 504 tests from 2016 to 2025 sci:sha256:4adcb5f1bc1bda2df920b7b53f7fb09b57658a671e2df019f32b1c4d19f5143c

    We use its weekly VIX variance forecast question and baseline design. Our schedule, common training cases and test sample differ.

  5. usesBaa credit spreads gave no clear gain in weekly Nasdaq return forecasts in a 2015–2025 archive test sci:sha256:5cc5b1fb7e17721ab436a4486b744031b2d7336dc8f523356bf3c9d2d1da2a26

    We reuse its retained credit and Nasdaq archives, adapt its MIT interval reader and timing design, and extend its mean-return question to added risk information after VIX.

  6. usesVolatility scaling cut lower 5% return forecast loss by 8.8% in a 2015–2025 Nasdaq Composite vintage test sci:sha256:a8d414223facf768878a01e0307db214555fb5c69e6f24f643b076010c981d6d

    We reuse the retained Nasdaq source and adapt its MIT ALFRED downloader to VIX.

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