Qin Shao
- Finance top 5%
- Financial Risk and Volatility Modeling 12
- Statistics and Probability top 5%
- Statistical Methods and Inference 11
- Advanced Statistical Methods and Models 7
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- Monetary Policy and Economic Impact 4
- Economics and Econometrics top 10%
- Complex Systems and Time Series Analysis 4
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- COVID-19 epidemiological studies 3
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- Forecasting Techniques and Applications 3
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- Control Systems and Identification 3
- Co-authors
- Gene Hsin ChangLijian YangRobert LundI. V. BasawaKhew‐Voon ChinMark M. MeerschaertQinbao SongGang Liu
- Journals
- SHILAP Revista de lepidopterología (3 papers)Journal of the Royal Statistical Society Series B (Statistical Methodology) (1 paper)Journal of the Optical Society of America B (1 paper)
- Partner nations
- United StatesChinaIndia
In The Last Decade
Qin Shao
29 papers receiving 283 citations
Peers
Comparison fields: 5 of 76
- Finance 130
- Statistics and Probability 101
- General Economics, Econometrics and Finance 77
- Economics and Econometrics 72
- Statistics, Probability and Uncertainty 15
Countries citing papers authored by Qin Shao
This map shows the geographic impact of Qin Shao'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 Qin Shao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qin Shao more than expected).
Fields of papers citing papers by Qin Shao
This network shows the impact of papers produced by Qin Shao. 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 Qin Shao. The network helps show where Qin Shao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Qin Shao, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 2 | |
| 5 | 2023 | 4 | |
| 6 | 2023 | 3 | |
| 7 | 2021 | 1 | |
| 8 | 2021 | 1 | |
| 9 | COVID-19 Risk Factor Identification based on Ohio Data | 2020 | 2 |
| 10 | 2020 | 2 | |
| 11 | 2016 | 1 | |
| 12 | 2016 | 19 | |
| 13 | 2014 | 2 | |
| 14 | 2013 | 16 | |
| 15 | 2012 | 9 | |
| 16 | 2012 | 5 | |
| 17 | 2006 | 37 | |
| 18 | 2005 | 18 | |
| 19 | How Much is the Chinese Currency Undervalued? A Quantitative Estimation | 2004 | 4 |
| 20 | 2004 | 18 |
About Qin Shao
Qin Shao is a scholar working on Statistics and Probability, Finance and Modeling and Simulation, having authored 33 papers that have together received 298 indexed citations. Recurring topics across this work include Financial Risk and Volatility Modeling (12 papers), Statistical Methods and Inference (11 papers), Advanced Statistical Methods and Models (7 papers), Monetary Policy and Economic Impact (4 papers), Complex Systems and Time Series Analysis (4 papers), COVID-19 epidemiological studies (3 papers), Forecasting Techniques and Applications (3 papers) and Control Systems and Identification (3 papers). The work is most often cited by research in Finance (130 citations), Statistics and Probability (101 citations) and General Economics, Econometrics and Finance (77 citations). Qin Shao has collaborated with scholars based in United States, China and India. Frequent co-authors include Gene Hsin Chang, Lijian Yang, Robert Lund, I. V. Basawa, Khew‐Voon Chin, Mark M. Meerschaert, Qinbao Song, Gang Liu, Hien D. Nguyen and L. Y. Dong. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the Royal Statistical Society Series B (Statistical Methodology) and Journal of the Optical Society of America B.
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.