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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. 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:
- 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, arXiv.org, number 2401.03393, Jan, 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, arXiv.org, number 2401.05784, Jan, revised Jan 2024.
- Parley R Yang & Alexander Y Shestopaloff, 2023, "Bayesian Analysis of High Dimensional Vector Error Correction Model," Papers, arXiv.org, number 2312.17061, Dec, revised Mar 2024.
- Jad Beyhum, 2024, "Counterfactuals in factor models," Papers, arXiv.org, number 2401.03293, Jan.
- Da Huo, Da, 2024, "Efficient Estimation of Stochastic Parameters: A GLS Approach," MPRA Paper, University Library of Munich, Germany, number 119731, Jan.
- Katerina Petrova, 2024, "On the Validity of Classical and Bayesian DSGE-Based Inference," Staff Reports, Federal Reserve Bank of New York, number 1084, Jan, DOI: 10.59576/sr.1084.
- Allayioti, Anastasia & Venditti, Fabrizio, 2024, "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series, European Central Bank, number 2901, Feb.
- 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, arXiv.org, number 2401.00534, Dec.
- Brahmana, Rayenda Khresna, 2022, "Do Machine Learning Approaches Have the Same Accuracy in Forecasting Cryptocurrencies Volatilities?," MPRA Paper, University Library of Munich, Germany, number 119598, Dec.
- Cristina Chinazzo & Vahidin Jeleskovic, 2024, "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers, arXiv.org, number 2401.02049, Jan.