Daniel Borup : Citation Profile


Are you Daniel Borup?

Aarhus Universitet

4

H index

3

i10 index

56

Citations

RESEARCH PRODUCTION:

7

Articles

9

Papers

RESEARCH ACTIVITY:

   7 years (2017 - 2024). See details.
   Cites by year: 8
   Journals where Daniel Borup has often published
   Relations with other researchers
   Recent citing documents: 32.    Total self citations: 4 (6.67 %)

MORE DETAILS IN:
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   Permalink: http://citec.repec.org/pbo994
   Updated: 2024-11-08    RAS profile: 2024-09-09    
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Relations with other researchers


Works with:

Schütte, Erik Christian (7)

Christensen, Bent Jesper (4)

Authors registered in RePEc who have co-authored more than one work in the last five years with Daniel Borup.

Is cited by:

Goller, Daniel (5)

Stevanovic, Dalibor (4)

Lechner, Michael (3)

Conrad, Christian (2)

Demirer, Riza (2)

Sorić, Petar (1)

Hansen, Erwin (1)

Lolić, Ivana (1)

Nielsen, Morten (1)

Marçal, Emerson (1)

McCracken, Michael (1)

Cites to:

Diebold, Francis (16)

McCracken, Michael (14)

West, Kenneth (13)

Bollerslev, Tim (12)

Timmermann, Allan (11)

Campbell, John (10)

Ng, Serena (10)

Fama, Eugene (9)

Mariano, Roberto (9)

French, Kenneth (9)

Elliott, Graham (9)

Main data


Where Daniel Borup has published?


Journals with more than one article published# docs
International Journal of Forecasting2

Working Papers Series with more than one paper published# docs
FRB Atlanta Working Paper / Federal Reserve Bank of Atlanta2

Recent works citing Daniel Borup (2024 and 2023)


YearTitle of citing document
2023Active labour market policies for the long-term unemployed: New evidence from causal machine learning. (2021). Goller, Daniel ; Wolff, Joachim ; Lechner, Michael ; Harrer, Tamara. In: Papers. RePEc:arx:papers:2106.10141.

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2024Maximally Machine-Learnable Portfolios. (2023). Goebel, Maximilian ; Coulombe, Philippe Goulet. In: Papers. RePEc:arx:papers:2306.05568.

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2023Non-linear dimension reduction in factor-augmented vector autoregressions. (2023). Klieber, Karin. In: Papers. RePEc:arx:papers:2309.04821.

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2023.

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2023S&P 500 volatility, volatility regimes, and economic uncertainty. (2023). Chatrath, Arjun ; Adrangi, Bahram ; Raffiee, Kambiz. In: Bulletin of Economic Research. RePEc:bla:buecrs:v:75:y:2023:i:4:p:1362-1387.

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2023Machine learning advances for time series forecasting. (2023). Mendes, Eduardo F ; Medeiros, Marcelo C ; Masini, Ricardo P. In: Journal of Economic Surveys. RePEc:bla:jecsur:v:37:y:2023:i:1:p:76-111.

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2024Assessing and addressing the coronavirus-induced economic crisis: Evidence from 1.5 billion sales invoices. (2024). Liu, LU ; Liao, LI ; Chen, Zhuo ; Wang, Zhengwei. In: China Economic Review. RePEc:eee:chieco:v:85:y:2024:i:c:s1043951x24000336.

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2024Non-linear dimension reduction in factor-augmented vector autoregressions. (2024). Klieber, Karin. In: Journal of Economic Dynamics and Control. RePEc:eee:dyncon:v:159:y:2024:i:c:s0165188923002063.

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2024Does energy consumption play a key role? Re-evaluating the energy consumption-economic growth nexus from GDP growth rates forecasting. (2024). Hu, Shiyang ; Ma, Feng ; Lu, Fei. In: Energy Economics. RePEc:eee:eneeco:v:129:y:2024:i:c:s0140988323007661.

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2023Behavioral asset pricing under expected feedback mode. (2023). Xu, Shaojun. In: International Review of Financial Analysis. RePEc:eee:finana:v:86:y:2023:i:c:s1057521923000248.

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2023Chinese agricultural futures volatility: New insights from potential domestic and global predictors. (2023). Huang, Dengshi ; Su, Yuandong ; Lu, Xinjie. In: International Review of Financial Analysis. RePEc:eee:finana:v:89:y:2023:i:c:s1057521923003022.

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2024Do industries predict stock market volatility? Evidence from machine learning models. (2024). Demirer, Riza ; Suleman, Muhammad Tahir ; Niu, Zibo ; Zhu, Xuehong ; Zhang, Hongwei. In: Journal of International Financial Markets, Institutions and Money. RePEc:eee:intfin:v:90:y:2024:i:c:s1042443123001713.

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2023Improving variance forecasts: The role of Realized Variance features. (2023). Papantonis, Ioannis ; Tzavalis, Elias ; Rompolis, Leonidas. In: International Journal of Forecasting. RePEc:eee:intfor:v:39:y:2023:i:3:p:1221-1237.

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2023Forecasting GDP growth rates in the United States and Brazil using Google Trends. (2023). Clements, Michael ; Urquhart, Andrew ; Bantis, Evripidis. In: International Journal of Forecasting. RePEc:eee:intfor:v:39:y:2023:i:4:p:1909-1924.

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2023Does climate policy uncertainty affect Chinese stock market volatility?. (2023). Weng, Chen ; Zhang, LI ; Chen, Zhonglu. In: International Review of Economics & Finance. RePEc:eee:reveco:v:84:y:2023:i:c:p:369-381.

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2024Addressing Google Trends inconsistencies. (2024). Domenech, Josep ; Cebrian, Eduardo. In: Technological Forecasting and Social Change. RePEc:eee:tefoso:v:202:y:2024:i:c:s0040162524001148.

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2024Prediction of Live Bulb Weight for Field Vegetables Using Functional Regression Models and Machine Learning Methods. (2024). Na, Myung Hwan ; Cho, Wanhyun ; Kim, Dahyun. In: Agriculture. RePEc:gam:jagris:v:14:y:2024:i:5:p:754-:d:1393235.

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2023.

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2023When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage. (2022). Simoni, Anna ; Ferrara, Laurent. In: Post-Print. RePEc:hal:journl:hal-03919944.

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2024Measuring the Race, Ethnic, and Gender Composition of Company Workforces Using LinkedIn Data. (2024). Neumark, David ; Maloney, Elizabeth ; Berry, Alexander. In: NBER Chapters. RePEc:nbr:nberch:14962.

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2023Do extreme shocks help forecast oil price volatility? The augmented GARCH?MIDAS approach. (2023). Lang, Qiaoqi ; Liu, Guoshan ; Ma, Feng ; Wang, LU. In: International Journal of Finance & Economics. RePEc:wly:ijfiec:v:28:y:2023:i:2:p:2056-2073.

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2023Two are better than one: Volatility forecasting using multiplicative component GARCH?MIDAS models. (2020). Conrad, Christian ; Kleen, Onno. In: Journal of Applied Econometrics. RePEc:wly:japmet:v:35:y:2020:i:1:p:19-45.

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2023Policy uncertainty and stock market volatility revisited: The predictive role of signal quality. (2023). Salisu, Afees ; Demirer, Riza ; Gupta, Rangan. In: Journal of Forecasting. RePEc:wly:jforec:v:42:y:2023:i:8:p:2307-2321.

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Works by Daniel Borup:


YearTitleTypeCited
2017Statistical tests for equal predictive ability across multiple forecasting methods In: CREATES Research Papers.
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paper1
2019Assessing predictive accuracy in panel data models with long-range dependence In: CREATES Research Papers.
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paper0
2019In search of a job: Forecasting employment growth using Google Trends In: CREATES Research Papers.
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paper12
2022In Search of a Job: Forecasting Employment Growth Using Google Trends.(2022) In: Journal of Business & Economic Statistics.
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This paper has nother version. Agregated cites: 12
article
2020Targeting predictors in random forest regression In: CREATES Research Papers.
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paper17
2020Targeting predictors in random forest regression.(2020) In: Papers.
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This paper has nother version. Agregated cites: 17
paper
2023Targeting predictors in random forest regression.(2023) In: International Journal of Forecasting.
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This paper has nother version. Agregated cites: 17
article
2020Predicting bond return predictability In: CREATES Research Papers.
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paper0
2021Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data In: CREATES Research Papers.
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paper0
2021Stock market volatility and public information flow: A non-linear perspective In: Economics Letters.
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article0
2019Asset pricing model uncertainty In: Journal of Empirical Finance.
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article3
2022Asset pricing with data revisions In: Journal of Financial Markets.
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article2
2023Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data In: International Journal of Forecasting.
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article2
2022The Anatomy of Out-of-Sample Forecasting Accuracy In: FRB Atlanta Working Paper.
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paper4
2024The Anatomy of Out-of-Sample Forecasting Accuracy.(2024) In: FRB Atlanta Working Paper.
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This paper has nother version. Agregated cites: 4
paper
2019Capturing volatility persistence: a dynamically complete realized EGARCH-MIDAS model In: Quantitative Finance.
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article15

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