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Report NEP-ETS-2023-07-17
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:
- Cheng Yu & Dong Li & Feiyu Jiang & Ke Zhu, 2023, "Matrix GARCH Model: Inference and Application," Papers, arXiv.org, number 2306.05169, Jun.
- Markus Leippold & Hanlin Yang, 2023, "Mixed-Frequency Predictive Regressions with Parameter Learning," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 23-39, Mar, revised Jun 2023.
- Kasper Johansson & Mehmet Giray Ogut & Markus Pelger & Thomas Schmelzer & Stephen Boyd, 2023, "A Simple Method for Predicting Covariance Matrices of Financial Returns," Papers, arXiv.org, number 2305.19484, May, revised Nov 2023.
- Alex Maynard & Katsumi Shimotsu & Nina Kuriyama, 2023, "Inference in Predictive Quantile Regressions," Papers, arXiv.org, number 2306.00296, May, revised May 2024.
- Jad Beyhum & Jonas Striaukas, 2023, "Factor-augmented sparse MIDAS regressions with an application to nowcasting," Papers, arXiv.org, number 2306.13362, Jun, revised Oct 2025.
- Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023, "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers, Center for Quantitative Economics (CQE), University of Muenster, number 10523, Jun.
- Vygintas Gontis, 2023, "Discrete $q$-exponential limit order cancellation time distribution," Papers, arXiv.org, number 2306.00093, May, revised Oct 2023.
- Espasa, Antoni & Carlomagno Real, Guillermo, 2023, "Tall big data time series of high frequency: stylized facts and econometric modelling," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de EstadÃstica, number 37746, Jul.
- Runyu Dai & Yasumasa Matsuda, 2023, "Estimation of Large Volatility Matrices with Low-Rank Signal Plus Sparse Noise Structures," DSSR Discussion Papers, Graduate School of Economics and Management, Tohoku University, number 135, Jun.