Daniel Borup
Daniel Borup is an Assistant Professor at the Department of Economics and Business Economics, Aarhus University, and a research fellow at CREATES and the Danish Finance Institute. He holds a PhD in Economics from Aarhus University (2019). During 2017, Daniel visited the Department of Economics at the University of Pennsylvania. His main research interests are in asset pricing, forecasting, financial econometrics, and applications of machine learning methods to finance.
Borup, D., Rapach, D. E. & Schütte, E. C. M. (2023). Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data. International Journal of Forecasting, 39(3), 1122-1144. https://doi.org/10.1016/j.ijforecast.2022.05.005
Andersen, D. B., Christensen, B. J., Mühlbach, N. A. S. & Nielsen, M. S. (2023). Targeting Predictors in Random Forest Regression. International Journal of Forecasting, 39(2), 841-868. https://doi.org/10.1016/j.ijforecast.2022.02.010
Borup, D. & Montes Schütte, E. C. (2022). Asset pricing with data revisions. Journal of Financial Markets, 59(Part B), Article 100620. https://doi.org/10.1016/j.finmar.2021.100620
Borup, D. & Montes Schütte, E. C. (2022). In search of a job: Forecasting employment growth using Google Trends. Journal of Business and Economic Statistics, 40(1), 186-200. https://doi.org/10.1080/07350015.2020.1791133
Bertelsen, K. P., Borup, D. & Jakobsen, J. S. (2021). Stock market volatility and public information flow: A non-linear perspective. Economics Letters, 204, Article 109905. https://doi.org/10.1016/j.econlet.2021.109905
Borup, D. (2019). Asset pricing model uncertainty. Journal of Empirical Finance, 54, 166-189. https://doi.org/10.1016/j.jempfin.2019.07.005
Borup, D. & Jakobsen, J. S. (2019). Capturing volatility persistence: a dynamically complete realized EGARCH-MIDAS model. Quantitative Finance, 19(11), 1839-1855. https://doi.org/10.1080/14697688.2019.1614653
