Tae Yoon Kim
- Management Science and Operations Research top 1%
- Economics and Econometrics top 5%
- Finance top 2%
- Artificial Intelligence top 5%
- Statistics and Probability top 2%
- Co-authors
- Kyong Joo OhJae Joon AhnChiho KimSun Young HwangDennis D. CoxDong Ha KimJeong‐Soo ParkSung-Hwan Min
- Topics
- Statistical Methods and Inference (27 papers)Financial Risk and Volatility Modeling (19 papers)Stock Market Forecasting Methods (17 papers)
- Journals
- Expert Systems with ApplicationsJournal of Banking & FinanceTechnological Forecasting and Social Change
- Partner nations
- South KoreaUnited StatesEthiopia
In The Last Decade
Tae Yoon Kim
67 papers receiving 952 citations
Peers
Comparison fields: 5 of 100
- Management Science and Operations Research 463
- Economics and Econometrics 303
- Finance 285
- Artificial Intelligence 225
- Statistics and Probability 199
Countries citing papers authored by Tae Yoon Kim
This map shows the geographic impact of Tae Yoon Kim'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 Tae Yoon Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tae Yoon Kim more than expected).
Fields of papers citing papers by Tae Yoon Kim
This network shows the impact of papers produced by Tae Yoon Kim. 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 Tae Yoon Kim. The network helps show where Tae Yoon Kim may publish in the future.
Co-authorship network of co-authors of Tae Yoon Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Tae Yoon Kim. A scholar is included among the top collaborators of Tae Yoon Kim 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 Tae Yoon Kim. Tae Yoon Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 3 | |
| 7 | 20 | |
| 8 | Credibility estimation via kernel mixed effects model | 0 |
| 9 | 13 | |
| 10 | Group-wise Analysis of the Relations Between High School GPA, SAT Score and Grade at College | 1 |
| 11 | Using Support Vector Machine to Development Early Warning System for Financial Crisis | 2 |
| 12 | 76 | |
| 13 | 5 | |
| 14 | 13 | |
| 15 | 26 | |
| 16 | 1 | |
| 17 | 3 | |
| 18 | 9 | |
| 19 | 17 | |
| 20 | 16 |
About Tae Yoon Kim
Tae Yoon Kim is a scholar working on Statistics and Probability, Finance and Management Science and Operations Research, having authored 79 papers that have together received 1.0k indexed citations. Recurring topics across this work include Statistical Methods and Inference (27 papers), Financial Risk and Volatility Modeling (19 papers) and Stock Market Forecasting Methods (17 papers). The work is most often cited by research in Management Science and Operations Research (463 citations), Finance (285 citations) and Statistics and Probability (199 citations). Tae Yoon Kim has collaborated with scholars based in South Korea, United States and Ethiopia. Frequent co-authors include Kyong Joo Oh, Jae Joon Ahn, Chiho Kim, Sun Young Hwang, Dennis D. Cox, Dong Ha Kim, Jeong‐Soo Park, Sung-Hwan Min, Suk Jun Lee and Byeong U. Park. Their work appears in journals such as Expert Systems with Applications, Journal of Banking & Finance and Technological Forecasting and Social Change.
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.