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Report NEP-ETS-2024-03-25
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:
- Gabriel, Stefan & Kunst, Robert M., 2024, "Cointegrated portfolios and volatility modeling in the cryptocurrency market," IHS Working Paper Series, Institute for Advanced Studies, number 52, Mar.
- Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin & Daniel F. Waggoner, 2024, "Inference Based on Time-Varying SVARs Identified with Sign Restrictions," Working Papers, Federal Reserve Bank of Philadelphia, number 24-05, Feb, DOI: 10.21799/frbp.wp.2024.05.
- Steven Y. K. Wong & Jennifer S. K. Chan & Lamiae Azizi, 2024, "Quantifying neural network uncertainty under volatility clustering," Papers, arXiv.org, number 2402.14476, Feb, revised Sep 2024.
- Guglielmo Maria Caporale & Luis Alberiko Gil-Alana, 2024, "A Long-Memory Model for Multiple Cycles with an Application to the S&P500," CESifo Working Paper Series, CESifo, number 10947.
- Alexander Mayer & Dominik Wied & Victor Troster, 2024, "Quantile Granger Causality in the Presence of Instability," Papers, arXiv.org, number 2402.09744, Feb, revised Dec 2024.
- Zhang, Xinyu & Li, Dong & Tong, Howell, 2024, "On the least squares estimation of multiple-threshold-variable autoregressive models," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 118377, Jan.
- Juan Carlos Escanciano & Ricardo Parra, 2024, "Extending the Scope of Inference About Predictive Ability to Machine Learning Methods," Papers, arXiv.org, number 2402.12838, Feb, revised May 2025.