R. Deane Terrell

35 papers receiving 354 citations

Peers

R. Deane Terrell
Comparison fields: 5 of 55
  • General Economics, Econometrics and Finance 147
  • Finance 166
  • Statistics and Probability 94
  • Economics and Econometrics 194
  • Management Science and Operations Research 84
Replace Sergio G. Koreisha with:
Sergio G. Koreisha United States
Victoria Zinde‐Walsh Canada
Rolf Tschernig Germany
Carsten Jentsch Germany
Giorgio Calzolari Italy
Anders Rygh Swensen Norway
Gael M. Martin Australia
Abderrahim Taamouti Spain
Jack H.W. Penm Australia
Steven E. Posner United States
R. Deane Terrell relative to Sergio G. Koreisha United States Sergio G. Koreisha's profile →
Citations per field
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Sergio G. Koreisha · 1×
Citations per year

Countries citing papers authored by R. Deane Terrell

Since Specialization
Citations

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

Fields of papers citing papers by R. Deane Terrell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R. Deane Terrell. 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 R. Deane Terrell. The network helps show where R. Deane Terrell may publish in the future.

Co-authors

The 12 scholars most cited alongside R. Deane Terrell, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with R. Deane Terrell Line = papers co-authored together R. Deane Terrell links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200469
2 197065
3 197544
4 198232
5 198431
6 197323
7 196820
8 200417
9 199316
10 198414
11 199711
12 19929
13 20038
14 20057
15 20026
16 20006
17 19865
18 19955
19 20014
20 19974

About R. Deane Terrell

R. Deane Terrell is a scholar working on General Economics, Econometrics and Finance, Economics and Econometrics, Management Science and Operations Research, Finance and Control and Systems Engineering, having authored 41 papers that have together received 424 indexed citations. Recurring topics across this work include Monetary Policy and Economic Impact (16 papers), Forecasting Techniques and Applications (7 papers), Market Dynamics and Volatility (7 papers), Control Systems and Identification (6 papers), Complex Systems and Time Series Analysis (6 papers), Advanced Statistical Methods and Models (5 papers), Stock Market Forecasting Methods (5 papers) and Financial Risk and Volatility Modeling (4 papers). The work is most often cited by research in General Economics, Econometrics and Finance (147 citations), Finance (166 citations), Statistics and Probability (94 citations), Economics and Econometrics (194 citations) and Management Science and Operations Research (84 citations). R. Deane Terrell has collaborated with scholars based in Australia, United States and Singapore. Frequent co-authors include Jack H.W. Penm, E. J. Hannan, Wing‐Keung Wong, A. R. Pagan, D. F. Nicholls, Tim Brailsford, Soushan Wu, Andrew H. Chen, Terence J. O’Neill and Jason C.H. Chen. Their work appears in journals such as Journal of Time Series Analysis, International Economic Review, Econometrica, Journal of Applied Probability and Journal of Applied Sciences.

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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