Jae Joon Ahn
Impact in
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- Stock Market Forecasting Methods
- Forecasting Techniques and Applications
- Finance top 10%
- Financial Markets and Investment Strategies
Papers in
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- Stock Market Forecasting Methods 10
- Forecasting Techniques and Applications 5
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- Technology and Data Analysis 4
- Co-authors
- Kyong Joo Oh (14 shared papers)Tae Yoon Kim (12 shared papers)Dong Ha Kim (3 shared papers)Keunje Yoo (2 shared papers)Sudheer Kumar Shukla (1 shared paper)Joonhong Park (1 shared paper)Suk Jun Lee (2 shared papers)Hyunchul Ahn (3 shared papers)
- Journals
- Expert Systems with Applications (5 papers)Nuclear Engineering and Technology (4 papers)Applied Intelligence (2 papers)Applied Sciences (1 paper)PLoS ONE (1 paper)
- Partner nations
- South KoreaEthiopiaPuerto Rico
In The Last Decade
Jae Joon Ahn
38 papers receiving 469 citations
Peers
Comparison fields: 5 of 106
- Management Science and Operations Research 184
- Finance 63
- Economics and Econometrics 129
- Geochemistry and Petrology 28
- Environmental Engineering 58
Countries citing papers authored by Jae Joon Ahn
This map shows the geographic impact of Jae Joon Ahn'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 Jae Joon Ahn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jae Joon Ahn more than expected).
Fields of papers citing papers by Jae Joon Ahn
This network shows the impact of papers produced by Jae Joon Ahn. 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 Jae Joon Ahn. The network helps show where Jae Joon Ahn may publish in the future.
Co-authors
The 25 scholars most cited alongside Jae Joon Ahn, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 77 | |
| 2 | 2012 | 72 | |
| 3 | 2016 | 56 | |
| 4 | 2010 | 38 | |
| 5 | 2010 | 28 | |
| 6 | 2008 | 27 | |
| 7 | 2014 | 22 | |
| 8 | 2020 | 22 | |
| 9 | 2012 | 19 | |
| 10 | 2011 | 18 | |
| 11 | 2022 | 13 | |
| 12 | 2009 | 10 | |
| 13 | 2021 | 8 | |
| 14 | 2021 | 8 | |
| 15 | 2023 | 8 | |
| 16 | 2020 | 8 | |
| 17 | 2018 | 5 | |
| 18 | 2019 | 5 | |
| 19 | 2022 | 5 | |
| 20 | 2011 | 5 |
About Jae Joon Ahn
Jae Joon Ahn is a scholar working on Management Science and Operations Research, Information Systems, Economics and Econometrics, Marketing and Radiation, having authored 41 papers that have together received 496 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (10 papers), Forecasting Techniques and Applications (5 papers), Advanced X-ray and CT Imaging (4 papers), Technology and Data Analysis (4 papers), Customer Service Quality and Loyalty (4 papers), Customer churn and segmentation (4 papers), Energy Load and Power Forecasting (3 papers) and Financial Risk and Volatility Modeling (3 papers). The work is most often cited by research in Management Science and Operations Research (184 citations), Finance (63 citations), Economics and Econometrics (129 citations), Geochemistry and Petrology (28 citations) and Environmental Engineering (58 citations). Jae Joon Ahn has collaborated with scholars based in South Korea, Ethiopia and Puerto Rico. Frequent co-authors include Kyong Joo Oh, Tae Yoon Kim, Dong Ha Kim, Keunje Yoo, Sudheer Kumar Shukla, Joonhong Park, Suk Jun Lee, Hyunchul Ahn, Y.-M. Kim and Joonhong Park. Their work appears in journals such as Expert Systems with Applications, Nuclear Engineering and Technology, Applied Intelligence, Applied Sciences and PLoS ONE.
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.