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Report NEP-ETS-2026-04-20
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:
- Anna Bykhovskaya & Nour Meddahi, 2026, "Generalized Autoregressive Multivariate Models: From Binary to Poisson," Papers, arXiv.org, number 2604.14394, Apr.
- Hilde C. Bjornland & Nicolas Hardy & Dimitris Korobilis, 2026, "Forecasting Oil Prices Across the Distribution: A Quantile VAR Approach," Papers, arXiv.org, number 2604.12927, Apr.
- Bidoia, M. & Harvey, A. & Palumbo, D., 2026, "Dynamic Models for Climate Extremes," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2620, Mar.
- Fantazzini, Dean & Kurbatskii, Alexey, 2026, "Nowcasting and Forecasting Russian Regional CPI: Sparse Models and the Time-Varying Value of Online Data," MPRA Paper, University Library of Munich, Germany, number 128456.
- Marco Brianti & Mario Forni & Luca Gambetti & Antonio Granese, 2026, "Nonlinear Business-Cycle Anatomy," Working Papers, Dipartimento Scienze Economiche, Universita' di Bologna, number wp1221, Apr.
- Guo, Hongfei & Marín Díazaraque, Juan Miguel & Veiga, Helena, 2026, "Target-Driven Bayesian Stacking of Realized and Implied Volatility Forecasts," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de EstadÃstica, number 49851, Apr.
- Tenghan Zhong, 2026, "Risk-Sensitive Specialist Routing for Volatility Forecasting," Papers, arXiv.org, number 2604.10402, Apr, revised Apr 2026.
- Younghoon Kim & Changryong Baek, 2026, "Latent community paths in VAR-type models via dynamic directed spectral co-clustering," Papers, arXiv.org, number 2604.12563, Apr.
- Oleg Kiriukhin, 2026, "Entropy-Rate Selection for Partially Observed Processes," Papers, arXiv.org, number 2604.10752, Apr.
- Onur Polat & Rangan Gupta & Dhanashree Somani & Sayar Karmakar, 2026, "Machine Learning Forecasting of U.S. Stock Market Volatility: The Role of Stock and Oil Bubbles," Working Papers, University of Pretoria, Department of Economics, number 202611, Apr.