Cheoljun Eom

1.0k total citations
42 papers, 757 citations indexed

About

Cheoljun Eom is a scholar working on Economics and Econometrics, Finance and Management Science and Operations Research. According to data from OpenAlex, Cheoljun Eom has authored 42 papers receiving a total of 757 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Economics and Econometrics, 29 papers in Finance and 7 papers in Management Science and Operations Research. Recurrent topics in Cheoljun Eom's work include Complex Systems and Time Series Analysis (23 papers), Financial Markets and Investment Strategies (20 papers) and Financial Risk and Volatility Modeling (16 papers). Cheoljun Eom is often cited by papers focused on Complex Systems and Time Series Analysis (23 papers), Financial Markets and Investment Strategies (20 papers) and Financial Risk and Volatility Modeling (16 papers). Cheoljun Eom collaborates with scholars based in South Korea, United States and Japan. Cheoljun Eom's co-authors include Gabjin Oh, Seunghwan Kim, Woo‐Sung Jung, Taisei Kaizoji, Jong Won Park, Lukáš Pichl, Sunghoon Choi, Sang Hoon Kang, H. Eugene Stanley and Hawoong Jeong and has published in prestigious journals such as Physica A Statistical Mechanics and its Applications, The European Physical Journal B and International Review of Financial Analysis.

In The Last Decade

Cheoljun Eom

38 papers receiving 728 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cheoljun Eom South Korea 13 683 388 215 136 83 42 757
Taisei Kaizoji Japan 17 819 1.2× 421 1.1× 224 1.0× 167 1.2× 172 2.1× 55 969
Leonidas Sandoval Brazil 8 452 0.7× 183 0.5× 163 0.8× 79 0.6× 21 0.3× 10 527
Wei-Qiang Huang China 12 445 0.7× 179 0.5× 185 0.9× 67 0.5× 16 0.2× 37 565
Stacy Williams United Kingdom 8 301 0.4× 186 0.5× 99 0.5× 123 0.9× 15 0.2× 10 413
Kimmo Soramäki Germany 14 584 0.9× 564 1.5× 182 0.8× 51 0.4× 48 0.6× 34 859
Mark McDonald United Kingdom 7 282 0.4× 171 0.4× 99 0.5× 101 0.7× 15 0.2× 9 378
Kaushik Matia United States 11 585 0.9× 217 0.6× 278 1.3× 67 0.5× 6 0.1× 14 647
Claire G. Gilmore United States 15 755 1.1× 558 1.4× 168 0.8× 81 0.6× 7 0.1× 22 882
Paolo Barucca United Kingdom 13 237 0.3× 207 0.5× 144 0.7× 29 0.2× 23 0.3× 36 475
Petre Caraiani Romania 14 482 0.7× 216 0.6× 110 0.5× 54 0.4× 9 0.1× 75 588

Countries citing papers authored by Cheoljun Eom

Since Specialization
Citations

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

Fields of papers citing papers by Cheoljun Eom

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cheoljun Eom. 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 Cheoljun Eom. The network helps show where Cheoljun Eom may publish in the future.

Co-authorship network of co-authors of Cheoljun Eom

This figure shows the co-authorship network connecting the top 25 collaborators of Cheoljun Eom. A scholar is included among the top collaborators of Cheoljun Eom 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 Cheoljun Eom. Cheoljun Eom 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.
Eom, Cheoljun, et al.. (2024). State-dependent intra-day volatility pattern and its impact on price jump detection - Evidence from international equity indices. International Review of Financial Analysis. 95. 103412–103412. 1 indexed citations
2.
Eom, Cheoljun & Jong Won Park. (2023). Price behavior of small-cap stocks and momentum: A study using principal component momentum. Research in International Business and Finance. 65. 101908–101908. 1 indexed citations
3.
Eom, Cheoljun, et al.. (2023). Left-tail momentum and tail properties of return distributions: A case of Korea. International Review of Financial Analysis. 87. 102570–102570. 5 indexed citations
4.
Eom, Cheoljun, et al.. (2022). Left-Tail Momentum of Korean Stock Markets. Korean Journal of Financial Studies. 51(6). 693–728.
5.
Eom, Cheoljun, et al.. (2021). A Study on the Momentum Effect of the Korean Stock Markets Using Principal Component Analysis. 38(1). 103–148. 1 indexed citations
6.
Eom, Cheoljun, et al.. (2020). Investor Attention, Market Dynamics, and Momentum in the Korean Stock Market. Korean Journal of Financial Studies. 49(4). 589–641. 1 indexed citations
7.
Eom, Cheoljun & Jong Won Park. (2019). Effects of the fat-tail distribution on the relationship between prospect theory value and expected return. The North American Journal of Economics and Finance. 51. 101052–101052. 8 indexed citations
8.
Eom, Cheoljun. (2018). Cross-Sectional Mispricing and Idiosyncratic Volatility : A New Approach. Korean Journal of Financial Studies. 47(3). 471–503. 4 indexed citations
9.
Eom, Cheoljun & Jong Won Park. (2016). Effects of common factors on stock correlation networks and portfolio diversification. International Review of Financial Analysis. 49. 1–11. 23 indexed citations
10.
Eom, Cheoljun, et al.. (2014). A Study on the Relationship between Idiosyncratic Volatility and Stock Returns in the Korean Stock Markets. Korean Journal of Financial Studies. 43(4). 753–784. 8 indexed citations
11.
Oh, Gabjin, Cheoljun Eom, Shlomo Havlin, et al.. (2012). A multifractal analysis of Asian foreign exchange markets. The European Physical Journal B. 85(6). 72 indexed citations
12.
Eom, Cheoljun, Okyu Kwon, Woo‐Sung Jung, & Seunghwan Kim. (2010). The effect of a market factor on information flow between stocks using the minimal spanning tree. Physica A Statistical Mechanics and its Applications. 389(8). 1643–1652. 19 indexed citations
13.
Oh, Gabjin, Cheoljun Eom, F. Wang, et al.. (2010). Statistical properties of cross-correlation in the Korean stock market. The European Physical Journal B. 79(1). 55–60. 33 indexed citations
14.
Eom, Cheoljun, Woo‐Sung Jung, Taisei Kaizoji, & Seunghwan Kim. (2009). Effect of changing data size on eigenvalues in the Korean and Japanese stock markets. Physica A Statistical Mechanics and its Applications. 388(22). 4780–4786. 9 indexed citations
15.
Eom, Cheoljun, Woo‐Sung Jung, Sunghoon Choi, Gabjin Oh, & Seunghwan Kim. (2008). Effects of time dependency and efficiency on information flow in financial markets. Physica A Statistical Mechanics and its Applications. 387(21). 5219–5224. 9 indexed citations
16.
Eom, Cheoljun, Sunghoon Choi, Gabjin Oh, & Woo‐Sung Jung. (2008). Hurst exponent and prediction based on weak-form efficient market hypothesis of stock markets. Physica A Statistical Mechanics and its Applications. 387(18). 4630–4636. 81 indexed citations
17.
Eom, Cheoljun. (2007). An Empirical Study on the Properties of Stock Network in the Korean Stock Market using the Multifactor Model and Random Matrix Theory. Journal of Industrial Economics and Business. 20(5). 2055–2074.
18.
Oh, Gabjin, Seunghwan Kim, & Cheoljun Eom. (2007). Long-term memory and volatility clustering in high-frequency price changes. Physica A Statistical Mechanics and its Applications. 387(5-6). 1247–1254. 68 indexed citations
19.
Eom, Cheoljun, Gabjin Oh, & Seunghwan Kim. (2007). Deterministic factors of stock networks based on cross-correlation in financial market. Physica A Statistical Mechanics and its Applications. 383(1). 139–146. 26 indexed citations
20.
Eom, Cheoljun, et al.. (2006). Stock Network an Efficient Portfolio in Korean Stock Market. 5(2). 65–84. 1 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.

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