Report NEP-ETS-2021-02-08

This is the archive for NEP-ETS, a report on new working papers in the area of Econometric Time Series. Jaqueson K. Galimberti issued this report. It is usually issued weekly.

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Other reports in NEP-ETS

The following items were announced in this report:

• Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.
• Paulo M.M. Rodrigues & Marina Balboa, 2021. "Multivariate Fractional Integration Tests allowing for Conditional Heteroskedasticity with an Application to Return Volatility and Trading Volume," Working Papers w202102, Banco de Portugal, Economics and Research Department.
• Pablo Montero-Manso & Rob J Hyndman, 2020. "Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality," Monash Econometrics and Business Statistics Working Papers 45/20, Monash University, Department of Econometrics and Business Statistics.
• Ken Chung & Anthony Bellotti, 2021. "Evidence and Behaviour of Support and Resistance Levels in Financial Time Series," Papers 2101.07410, arXiv.org.
• Pincheira, Pablo & Hardy, Nicolás & Muñoz, Felipe, 2021. ""Go wild for a while!": A new asymptotically Normal test for forecast evaluation in nested models," MPRA Paper 105368, University Library of Munich, Germany.
• Racine Ly & Fousseini Traore & Khadim Dia, 2021. "Forecasting Commodity Prices Using Long Short-Term Memory Neural Networks," Papers 2101.03087, arXiv.org, revised Jan 2021.
• Leonard Goke & Mario Kendziorski, 2021. "Adequacy of time-series reduction for renewable energy systems," Papers 2101.06221, arXiv.org, revised Aug 2021.
• Florian Eckert & Philipp Kronenberg & Heiner Mikosch & Stefan Neuwirth, 2020. "Tracking Economic Activity With Alternative High-Frequency Data," KOF Working papers 20-488, KOF Swiss Economic Institute, ETH Zurich.
• Fajar, Muhammad & Prasetyo, Octavia Rizky & Nonalisa, Septiarida & Wahyudi, Wahyudi, 2020. "Forecasting unemployment rate in the time of COVID-19 pandemic using Google trends data (case of Indonesia)," MPRA Paper 105042, University Library of Munich, Germany, revised 30 Nov 2020.