David E. Rapach

9.6k total citations · 4 hit papers
73 papers, 5.8k citations indexed

About

David E. Rapach is a scholar working on Economics and Econometrics, Finance and General Economics, Econometrics and Finance. According to data from OpenAlex, David E. Rapach has authored 73 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Economics and Econometrics, 44 papers in Finance and 44 papers in General Economics, Econometrics and Finance. Recurrent topics in David E. Rapach's work include Monetary Policy and Economic Impact (44 papers), Financial Markets and Investment Strategies (31 papers) and Market Dynamics and Volatility (21 papers). David E. Rapach is often cited by papers focused on Monetary Policy and Economic Impact (44 papers), Financial Markets and Investment Strategies (31 papers) and Market Dynamics and Volatility (21 papers). David E. Rapach collaborates with scholars based in United States, Belgium and Singapore. David E. Rapach's co-authors include Guofu Zhou, Jack Strauss, Mark E. Wohar, Christopher J. Neely, Jun Tu, Matthew C. Ringgenberg, Jesper Rangvid, Christian E. Weber, Xi Dong and Yan Li and has published in prestigious journals such as The Journal of Finance, Journal of Financial Economics and Management Science.

In The Last Decade

David E. Rapach

73 papers receiving 5.5k citations

Hit Papers

Out-of-Sample Equity Premium Prediction: Combination Fore... 2009 2026 2014 2020 2009 2014 2013 2016 250 500 750 1000

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David E. Rapach United States 32 4.2k 3.8k 2.6k 1.4k 581 73 5.8k
Rossen Valkanov United States 26 3.5k 0.8× 3.7k 1.0× 1.7k 0.7× 718 0.5× 745 1.3× 59 5.0k
Christopher J. Neely United States 36 3.2k 0.8× 3.6k 0.9× 2.4k 0.9× 1.1k 0.8× 386 0.7× 151 4.8k
Jack Strauss United States 29 2.7k 0.7× 2.3k 0.6× 1.7k 0.7× 765 0.5× 430 0.7× 81 4.0k
Todd E. Clark United States 36 4.6k 1.1× 2.9k 0.8× 4.2k 1.6× 1.1k 0.8× 253 0.4× 114 6.3k
Tim Bollerslev United States 32 6.8k 1.6× 8.3k 2.2× 3.4k 1.3× 608 0.4× 706 1.2× 74 9.6k
Peter Christoffersen Canada 41 4.6k 1.1× 6.7k 1.7× 2.1k 0.8× 753 0.5× 334 0.6× 147 7.8k
Pedro Santa‐Clara United States 35 3.7k 0.9× 5.4k 1.4× 1.7k 0.7× 828 0.6× 1.2k 2.1× 53 6.4k
Ser‐Huang Poon United Kingdom 22 3.3k 0.8× 3.8k 1.0× 1.1k 0.4× 539 0.4× 332 0.6× 97 4.6k
Michael W. Brandt United States 32 3.2k 0.8× 5.1k 1.3× 1.7k 0.7× 623 0.4× 1.0k 1.7× 75 5.9k
George Kapetanios United Kingdom 34 4.5k 1.1× 1.9k 0.5× 3.3k 1.3× 582 0.4× 229 0.4× 220 5.8k

Countries citing papers authored by David E. Rapach

Since Specialization
Citations

This map shows the geographic impact of David E. Rapach'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 David E. Rapach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David E. Rapach more than expected).

Fields of papers citing papers by David E. Rapach

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David E. Rapach. 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 David E. Rapach. The network helps show where David E. Rapach may publish in the future.

Co-authorship network of co-authors of David E. Rapach

This figure shows the co-authorship network connecting the top 25 collaborators of David E. Rapach. A scholar is included among the top collaborators of David E. Rapach 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 David E. Rapach. David E. Rapach is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Rapach, David E. & Guofu Zhou. (2023). Forecasting Stock Returns. SSRN Electronic Journal. 2 indexed citations
2.
Coulombe, Philippe Goulet, et al.. (2023). The Anatomy of Machine Learning-Based Portfolio Performance. SSRN Electronic Journal. 2 indexed citations
3.
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
4.
Dong, Xi, Yan Li, David E. Rapach, & Guofu Zhou. (2021). Anomalies and the Expected Market Return. The Journal of Finance. 77(1). 639–681. 86 indexed citations
5.
Rapach, David E., et al.. (2019). The Rise and Fall of the Carry Trade: Links to Exchange Rate Predictability. SSRN Electronic Journal. 3 indexed citations
6.
Rapach, David E. & Guofu Zhou. (2019). Time-Series and Cross-Sectional Stock Return Forecasting: New Machine Learning Methods. SSRN Electronic Journal. 5 indexed citations
7.
Neely, Christopher J., David E. Rapach, Jun Tu, & Guofu Zhou. (2014). Forecasting the Equity Risk Premium: The Role of Technical Indicators. Management Science. 60(7). 1772–1791. 712 indexed citations breakdown →
8.
Neely, Christopher J. & David E. Rapach. (2011). International comovements in inflation rates and country characteristics. Journal of International Money and Finance. 30(7). 1471–1490. 118 indexed citations
9.
Rapach, David E. & Jack Strauss. (2011). Forecasting US state-level employment growth: An amalgamation approach. International Journal of Forecasting. 28(2). 315–327. 26 indexed citations
10.
Neely, Christopher J., David E. Rapach, Jun Tu, & Guofu Zhou. (2011). Forecasting the Equity Risk Premium: The Role of Technical Indicators. SSRN Electronic Journal. 86 indexed citations
11.
Rapach, David E. & Jack Strauss. (2010). Bagging or Combining (or Both)? An Analysis Based on Forecasting U.S. Employment Growth. Econometric Reviews. 29(5-6). 511–533. 47 indexed citations
12.
Rapach, David E. & Mark E. Wohar. (2008). Structural Breaks and Predictive Regression Models of Aggregate U.S. Stock Returns. SSRN Electronic Journal. 6 indexed citations
13.
Owyang, Michael T., David E. Rapach, & Howard J. Wall. (2008). States and the business cycle. Journal of Urban Economics. 65(2). 181–194. 43 indexed citations
14.
Owyang, Michael T., David E. Rapach, & Howard J. Wall. (2008). States and the Business Cycle. SSRN Electronic Journal. 7 indexed citations
15.
Rapach, David E. & Jack Strauss. (2006). The Long-Run Relationship Between Consumption and Housing Wealth in the Eighth District States. RePEc: Research Papers in Economics. 140–147. 13 indexed citations
16.
Rapach, David E. & Mark E. Wohar. (2006). The out-of-sample forecasting performance of nonlinear models of real exchange rate behavior. International Journal of Forecasting. 22(2). 341–361. 64 indexed citations
17.
Rapach, David E. & Mark E. Wohar. (2005). In-sample vs. out-of-sample tests of stock return predictability in the context of data mining. Journal of Empirical Finance. 13(2). 231–247. 179 indexed citations
18.
Rapach, David E. & Jack Strauss. (2005). Forecasting Employment Growth in Missouri with Many Potentially Relevant Predictors: An Analysis of Forecast Combining Methods. RePEc: Research Papers in Economics. 97–112. 11 indexed citations
19.
Rapach, David E., Mark E. Wohar, & Jesper Rangvid. (2004). Macro variables and international stock return predictability. International Journal of Forecasting. 21(1). 137–166. 235 indexed citations
20.
Rapach, David E. & Christian E. Weber. (2004). Are real interest rates really nonstationary? New evidence from tests with good size and power. Journal of Macroeconomics. 26(3). 409–430. 112 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026