Report NEP-ETS-2019-10-07

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:

• Karina Arias-Calluari & Morteza. N. Najafi & Michael S. Harr'e & Fernando Alonso-Marroquin, 2019. "Stationarity of the detrended price return in stock markets," Papers 1910.01034, arXiv.org, revised Aug 2020.
• Majid M. Al-Sadoon & Piotr Zwiernik, 2019. "The Identification Problem for Linear Rational Expectations Models," Working Papers 1114, Barcelona School of Economics.
• Juan Manuel Julio-Román, 2019. "Estimating the Exchange Rate Pass-Through: A Time-Varying Vector Auto-Regression with Residual Stochastic Volatility Approach," Borradores de Economia 1093, Banco de la Republica de Colombia.
• Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2019. "A Non-Elliptical Orthogonal GARCH Model for Portfolio Selection under Transaction Costs," Swiss Finance Institute Research Paper Series 19-51, Swiss Finance Institute.
• Yi Huang & Ishanu Chattopadhyay, 2019. "Data Smashing 2.0: Sequence Likelihood (SL) Divergence For Fast Time Series Comparison," Papers 1909.12243, arXiv.org, revised Oct 2019.
• Aitor Muguruza, 2019. "Not so Particular about Calibration: Smile Problem Resolved," Papers 1909.13366, arXiv.org.
• Naoki Awaya & Yasuhiro Omori, 2019. "Particle Rolling MCMC," CIRJE F-Series CIRJE-F-1126, CIRJE, Faculty of Economics, University of Tokyo.
• Danilo Vassallo & Giacomo Bormetti & Fabrizio Lillo, 2019. "A tale of two sentiment scales: Disentangling short-run and long-run components in multivariate sentiment dynamics," Papers 1910.01407, arXiv.org, revised Sep 2020.
• Peter Carr & Liuren Wu & Zhibai Zhang, 2019. "Using Machine Learning to Predict Realized Variance," Papers 1909.10035, arXiv.org.