Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Dynamic correlation analysis of financial contagion: Evidence from Asian markets
2007642 citationsThomas C. Chiang, Bang Nam Jeon et al.Journal of International Money and Financeprofile →
An empirical analysis of herd behavior in global stock markets
2010626 citationsThomas C. Chiang, Dazhi Zhengprofile →
Herding behavior in Chinese stock markets: An examination of A and B shares
2007489 citationsLin Tan, Thomas C. Chiang et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Thomas C. Chiang
Since
Specialization
Citations
This map shows the geographic impact of Thomas C. Chiang'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 Thomas C. Chiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas C. Chiang more than expected).
Fields of papers citing papers by Thomas C. Chiang
This network shows the impact of papers produced by Thomas C. Chiang. 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 Thomas C. Chiang. The network helps show where Thomas C. Chiang may publish in the future.
Co-authorship network of co-authors of Thomas C. Chiang
This figure shows the co-authorship network connecting the top 25 collaborators of Thomas C. Chiang.
A scholar is included among the top collaborators of Thomas C. Chiang 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 Thomas C. Chiang. Thomas C. Chiang is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Chiang, Thomas C., et al.. (2017). Comovements of Stock Markets between Turkey and Global Countries. Czech Journal of Economics and Finance. 67(3). 250–275.2 indexed citations
8.
Chiang, Thomas C., Cathy W. S. Chen, & Mike K. P. So. (2015). Asymmetric Return and Volatility Responses to Composite News from Stock Markets. SSRN Electronic Journal.
9.
Chiang, Thomas C. & Dazhi Zheng. (2015). Liquidity and Stock Returns: Evidence from International Markets. SSRN Electronic Journal.
10.
Chiang, Thomas C., Jiandong Li, Lin Tan, & Edward Nelling. (2013). Dynamic Herding Behavior in Pacific-Basin Markets: Evidence and Implications. SSRN Electronic Journal.19 indexed citations
Chiang, Thomas C., et al.. (2009). Statistical Properties, Dynamic Conditional Correlation, Scaling Analysis of High-Frequency Intraday Stock Returns: Evidence from Dow-Jones and Nasdaq Indices. SSRN Electronic Journal.1 indexed citations
14.
Chiang, Thomas C., et al.. (2008). Dynamic Correlation Analysis of Financial Contagion: Evidence from Asian Countries. SSRN Electronic Journal.54 indexed citations
Chiang, Thomas C., Bang Nam Jeon, & Huimin Li. (2007). Dynamic correlation analysis of financial contagion: Evidence from Asian markets. Journal of International Money and Finance. 26(7). 1206–1228.642 indexed citations breakdown →
Chiang, Thomas C., et al.. (2000). Stock Return and Exchange Rate Risk: Evidence from Asian Stock Markets Based on A Bivariate GARCH Model. International Journal of Business. 5(2). 97.30 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.