Report NEP-ETS-2018-01-22

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.

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Other reports in NEP-ETS

The following items were announced in this report:

• Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
• Chambers, MJ, 2018. "Frequency Domain Estimation of Cointegrating Vectors with Mixed Frequency and Mixed Sample Data," Economics Discussion Papers 21144, University of Essex, Department of Economics.
• Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2016. "Maximum Likelihood Estimation in Markov Regime-Switching Models with Covariate-Dependent Transition Probabilities," Papers 1612.04932, arXiv.org, revised Dec 2021.
• Christiane J.S. Baumeister & James D. Hamilton, 2017. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks," NBER Working Papers 24167, National Bureau of Economic Research, Inc.
• Güriş, Burak, 2017. "A Flexible Fourier Form Nonlinear Unit Root Test Based on ESTAR Model," MPRA Paper 83472, University Library of Munich, Germany.
• Thomas R. Cook & Aaron Smalter Hall, 2017. "Macroeconomic Indicator Forecasting with Deep Neural Networks," Research Working Paper RWP 17-11, Federal Reserve Bank of Kansas City.
• Yun-Cheng Tsai & Jun-Hao Chen & Jun-Jie Wang, 2018. "Predict Forex Trend via Convolutional Neural Networks," Papers 1801.03018, arXiv.org.
• Trabelsi, Mohamed Ali & Hmida, Salma, 2017. "A Dynamic Correlation Analysis of Financial Contagion: Evidence from the Eurozone Stock Markets," MPRA Paper 83718, University Library of Munich, Germany, revised 2017.