Daniel Borup

424 total citations
17 papers, 222 citations indexed

About

Daniel Borup is a scholar working on Economics and Econometrics, Finance and Epidemiology. According to data from OpenAlex, Daniel Borup has authored 17 papers receiving a total of 222 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Economics and Econometrics, 10 papers in Finance and 4 papers in Epidemiology. Recurrent topics in Daniel Borup's work include Financial Markets and Investment Strategies (8 papers), Market Dynamics and Volatility (5 papers) and COVID-19 epidemiological studies (4 papers). Daniel Borup is often cited by papers focused on Financial Markets and Investment Strategies (8 papers), Market Dynamics and Volatility (5 papers) and COVID-19 epidemiological studies (4 papers). Daniel Borup collaborates with scholars based in Denmark, United States and Canada. Daniel Borup's co-authors include Bent Jesper Christensen, David E. Rapach, Benjamin D. Liengaard and Philippe Goulet Coulombe and has published in prestigious journals such as Journal of Business and Economic Statistics, Economics Letters and International Journal of Forecasting.

In The Last Decade

Daniel Borup

15 papers receiving 212 citations

Peers

Daniel Borup
Max Menzies Australia
Zifeng Zhao United States
Lixian Su China
Anton Pichler United States
J. Doyne Farmer United States
Max Menzies Australia
Daniel Borup
Citations per year, relative to Daniel Borup Daniel Borup (= 1×) peers Max Menzies

Countries citing papers authored by Daniel Borup

Since Specialization
Citations

This map shows the geographic impact of Daniel Borup's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Borup with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Borup more than expected).

Fields of papers citing papers by Daniel Borup

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Borup. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Borup. The network helps show where Daniel Borup may publish in the future.

Co-authorship network of co-authors of Daniel Borup

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Borup. A scholar is included among the top collaborators of Daniel Borup based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Borup. Daniel Borup is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Borup, Daniel, et al.. (2024). Predicting bond return predictability. 2 indexed citations
2.
Borup, Daniel, et al.. (2023). Quantifying investor narratives and their role during COVID‐19. Journal of Applied Econometrics. 38(4). 512–532. 3 indexed citations
3.
Borup, Daniel, et al.. (2022). Targeting predictors in random forest regression. International Journal of Forecasting. 39(2). 841–868. 84 indexed citations
4.
Borup, Daniel, et al.. (2022). Immunization With Consistent Term Structure Dynamics. SSRN Electronic Journal.
5.
Borup, Daniel, et al.. (2022). Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data. International Journal of Forecasting. 39(3). 1122–1144. 11 indexed citations
6.
Borup, Daniel, et al.. (2022). The Anatomy of Out-of-Sample Forecasting Accuracy. SSRN Electronic Journal. 5 indexed citations
7.
Borup, Daniel, et al.. (2021). Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data. RePEc: Research Papers in Economics. 2 indexed citations
8.
Borup, Daniel, et al.. (2021). Predictive Regressions under Arbitrary Persistence and Stock Return Predictability. SSRN Electronic Journal. 1 indexed citations
9.
Borup, Daniel, et al.. (2021). Stock market volatility and public information flow: A non-linear perspective. Economics Letters. 204. 109905–109905. 2 indexed citations
10.
Borup, Daniel, et al.. (2021). Asset pricing with data revisions. Journal of Financial Markets. 59. 100620–100620. 6 indexed citations
11.
Borup, Daniel, et al.. (2020). Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data. SSRN Electronic Journal. 4 indexed citations
12.
Borup, Daniel, et al.. (2020). In Search of a Job: Forecasting Employment Growth Using Google Trends. Journal of Business and Economic Statistics. 40(1). 186–200. 59 indexed citations
13.
Borup, Daniel, et al.. (2020). Tell Me a Story: Quantifying Economic Narratives and Their Role during COVID-19. SSRN Electronic Journal. 2 indexed citations
14.
Borup, Daniel, et al.. (2019). Asset Pricing With Data Revisions. SSRN Electronic Journal.
15.
Borup, Daniel. (2019). Asset pricing model uncertainty. Journal of Empirical Finance. 54. 166–189. 5 indexed citations
16.
Borup, Daniel, et al.. (2019). Capturing volatility persistence: a dynamically complete realized EGARCH-MIDAS model. Quantitative Finance. 19(11). 1839–1855. 34 indexed citations
17.
Borup, Daniel, et al.. (2017). Statistical tests for equal predictive ability across multiple forecasting methods. RePEc: Research Papers in Economics. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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