References in zbMATH (referenced in 15 articles , 1 standard article )

Showing results 1 to 15 of 15.
Sorted by year (citations)

  1. Kung, Ko-Lun; MacMinn, Richard D.; Kuo, Weiyu; Tsai, Chenghsien Jason: Multi-population mortality modeling: when the data is too much and not enough (2022)
  2. David Ardia, Keven Bluteau, Samuel Borms, Kris Boudt: The R package sentometrics to compute, aggregate and predict with textual sentiment (2021) arXiv
  3. Lattanzi, Chiara; Leonelli, Manuele: A change-point approach for the identification of financial extreme regimes (2021)
  4. Samuel Borms, David Ardia, Keven Bluteau, Kris Boudt, Jeroen Van Pelt, Andres Algaba: The R Package sentometrics to Compute, Aggregate, and Predict with Textual Sentiment (2021) not zbMATH
  5. De Zea Bermudez, P.; Marín, J. Miguel; Veiga, Helena: Data cloning estimation for asymmetric stochastic volatility models (2020)
  6. Eo, Yunjong; Kang, Kyu Ho: The effects of conventional and unconventional monetary policy on forecasting the yield curve (2020)
  7. Muzzioli, Silvia; Gambarelli, Luca; De Baets, Bernard: Option implied moments obtained through fuzzy regression (2020)
  8. Amo Baffour, Alexander; Feng, Jingchun; Fan, Liwei; Buanya, Beryl Adormaa: Forecasting volatility returns of oil price using gene expression programming approach. (2019)
  9. Shang, Han Lin: A robust functional time series forecasting method (2019)
  10. Guidolin, Massimo; Orlov, Alexei G.; Pedio, Manuela: How good can heuristic-based forecasts be? A comparative performance of econometric and heuristic models for UK and US asset returns (2018)
  11. Guidolin, Massimo; Orlov, Alexei G.; Pedio, Manuela: How good can heuristic-based forecasts be? A comparative performance of econometric and heuristic models for UK and US asset returns (2017)
  12. Amendola, A.; Candila, V.: Evaluation of volatility predictions in a VaR framework (2016)
  13. Lyócsa, Štefan; Molnár, Peter: Volatility forecasting of strategically linked commodity ETFs: gold-silver (2016)
  14. Mauro Bernardi, Leopoldo Catania: The Model Confidence Set package for R (2014) arXiv
  15. Hansen, Peter R.; Lunde, Asger; Nason, James M.: The model confidence set (2011)