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Report NEP-ETS-2024-11-18
This is the archive for NEP-ETS, a report on new working papers in the area of Econometric Time Series. Yong Yin issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-ETS
The following items were announced in this report:
- Luca Vincenzo Ballestra & Enzo D'Innocenzo & Christian Tezza, 2024, "GARCH option valuation with long-run and short-run volatility components: A novel framework ensuring positive variance," Papers, arXiv.org, number 2410.14513, Oct.
- Farley Ishaak & Peng Liu & Egbert Hardeman & Hilde Remoy, 2024, "Forecasting House Prices And Rents: Combining Dynamic Factor Models and Machine Learning," ERES, European Real Estate Society (ERES), number eres2024-207, Jan.
- Yannick Hoga, 2024, "Persistence-Robust Break Detection in Predictive CoVaR Regressions," Papers, arXiv.org, number 2410.05861, Oct, revised Mar 2026.
- Anubha Goel & Puneet Pasricha & Juho Kanniainen, 2024, "Time-Series Foundation AI Model for Value-at-Risk Forecasting," Papers, arXiv.org, number 2410.11773, Oct, revised May 2025.
- Pulikandala Nithish Kumar & Nneka Umeorah & Alex Alochukwu, 2024, "Dynamic graph neural networks for enhanced volatility prediction in financial markets," Papers, arXiv.org, number 2410.16858, Oct.
- Ter Steege, Lucas, 2024, "Variational inference for Bayesian panel VAR models," Working Paper Series, European Central Bank, number 2991, Oct.
- Sohyeon Kwon & Yongjae Lee, 2024, "Can GANs Learn the Stylized Facts of Financial Time Series?," Papers, arXiv.org, number 2410.09850, Oct.