Report NEP-ETS-2024-02-12

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:

• Dennis Koch & Vahidin Jeleskovic & Zahid I. Younas, 2024. "Modelling and Predicting the Conditional Variance of Bitcoin Daily Returns: Comparsion of Markov Switching GARCH and SV Models," Papers 2401.03393, arXiv.org, revised Jan 2024.
• Chenlei Leng & Degui Li & Hanlin Shang & Yingcun Xia, 2024. "Covariance Function Estimation for High-Dimensional Functional Time Series with Dual Factor Structures," Papers 2401.05784, arXiv.org, revised Jan 2024.
• Parley R Yang & Alexander Y Shestopaloff, 2023. "Bayesian Analysis of High Dimensional Vector Error Correction Model," Papers 2312.17061, arXiv.org, revised Mar 2024.
• Jad Beyhum, 2024. "Counterfactuals in factor models," Papers 2401.03293, arXiv.org.
• Da Huo, Da, 2024. "Efficient Estimation of Stochastic Parameters: A GLS Approach," MPRA Paper 119731, University Library of Munich, Germany.
• Katerina Petrova, 2024. "On the Validity of Classical and Bayesian DSGE-Based Inference," Staff Reports 1084, Federal Reserve Bank of New York.
• Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
• Shun Liu & Kexin Wu & Chufeng Jiang & Bin Huang & Danqing Ma, 2023. "Financial Time-Series Forecasting: Towards Synergizing Performance And Interpretability Within a Hybrid Machine Learning Approach," Papers 2401.00534, arXiv.org.
• Brahmana, Rayenda Khresna, 2022. "Do Machine Learning Approaches Have the Same Accuracy in Forecasting Cryptocurrencies Volatilities?," MPRA Paper 119598, University Library of Munich, Germany.
• Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.