Tae‐Hwan Kim
-
- Monetary Policy and Economic Impact 15
- Finance top 1%
- Financial Risk and Volatility Modeling 14
- Financial Markets and Investment Strategies 3
- Economics and Econometrics top 1%
- Market Dynamics and Volatility 9
- Complex Systems and Time Series Analysis 5
- Italy: Economic History and Contemporary Issues 3
- General Energy top 5%
- Statistics and Probability top 5%
- Advanced Statistical Methods and Models 6
- Statistical Methods and Inference 5
Tae‐Hwan Kim
23 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 132
- General Economics, Econometrics and Finance 503
- Finance 597
- Economics and Econometrics 1.1k
- General Energy 19
- Statistics and Probability 116
Countries citing papers authored by Tae‐Hwan Kim
This map shows the geographic impact of Tae‐Hwan 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‐Hwan 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‐Hwan Kim more than expected).
Fields of papers citing papers by Tae‐Hwan Kim
This network shows the impact of papers produced by Tae‐Hwan 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‐Hwan Kim. The network helps show where Tae‐Hwan Kim may publish in the future.
Co-authorship network
The 15 scholars most cited alongside Tae‐Hwan Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 0 | |
| 2 | 2019 | 3 | |
| 3 | 2018 | 5 | |
| 4 | 2017 | 4 | |
| 5 | VAR for VaR: Measuring tail dependence using multivariate regression quantilesbreakdown → | 2015 | 254 |
| 6 | Quantile cointegration in the autoregressive distributed-lag modeling frameworkbreakdown → | 2015 | 386 |
| 7 | 2014 | 85 | |
| 8 | 2012 | 0 | |
| 9 | 2011 | 6 | |
| 10 | 2009 | 7 | |
| 11 | 2009 | 6 | |
| 12 | 2008 | 19 | |
| 13 | 2006 | 56 | |
| 14 | 2006 | 4 | |
| 15 | 2005 | 1 | |
| 16 | 2004 | 353 | |
| 17 | 2004 | 30 | |
| 18 | 2003 | 10 | |
| 19 | 2002 | 89 | |
| 20 | 2001 | 42 |
About Tae‐Hwan Kim
Tae‐Hwan Kim is a scholar working on General Economics, Econometrics and Finance, Finance and Statistics and Probability, having authored 26 papers that have together received 1.6k indexed citations. Recurring topics across this work include Monetary Policy and Economic Impact (15 papers), Financial Risk and Volatility Modeling (14 papers), Market Dynamics and Volatility (9 papers), Advanced Statistical Methods and Models (6 papers), Statistical Methods and Inference (5 papers), Complex Systems and Time Series Analysis (5 papers), Financial Markets and Investment Strategies (3 papers) and Italy: Economic History and Contemporary Issues (3 papers). The work is most often cited by research in General Economics, Econometrics and Finance (503 citations), Finance (597 citations) and Economics and Econometrics (1.1k citations). Tae‐Hwan Kim has collaborated with scholars based in South Korea, United Kingdom and United States. Frequent co-authors include Halbert White, Yongcheol Shin, Jin Seo Cho, Paul Newbold, Simone Manganelli, Stephen J. Leybourne, Yunmi Kim, Robert Taylor, Paul Mizen and Thanaset Chevapatrakul. Their work appears in journals such as Journal of Econometrics, Economics Letters and Finance research letters.
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.