Xue‐Zhong He
- Finance top 0.5%
- Financial Markets and Investment Strategies 57
- Financial Risk and Volatility Modeling 22
- Modeling and Simulation top 1%
- Economics and Econometrics top 0.5%
- Complex Systems and Time Series Analysis 71
- Economic theories and models 18
- Market Dynamics and Volatility 16
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- Mathematical and Theoretical Epidemiology and Ecology Models 17
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- Stock Market Forecasting Methods 16
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- Nonlinear Differential Equations Analysis 11
In The Last Decade
Xue‐Zhong He
111 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 97
- Finance 958
- Computer Networks and Communications 1.1k
- Statistical and Nonlinear Physics 559
- Modeling and Simulation 198
- Economics and Econometrics 1.2k
Countries citing papers authored by Xue‐Zhong He
This map shows the geographic impact of Xue‐Zhong He'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 Xue‐Zhong He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xue‐Zhong He more than expected).
Fields of papers citing papers by Xue‐Zhong He
This network shows the impact of papers produced by Xue‐Zhong He. 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 Xue‐Zhong He. The network helps show where Xue‐Zhong He may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xue‐Zhong He, 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 | 2024 | 1 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 0 | |
| 4 | 2023 | 0 | |
| 5 | 2021 | 4 | |
| 6 | Investor Sentiment and Paradigm Shifts in Equity Return Forecasting | 2019 | 2 |
| 7 | Heterogeneous Agent Models in Finance | 2018 | 8 |
| 8 | A Behavioral Model of Investor Sentiment in Limit Order Markets | 2016 | 1 |
| 9 | Learning and Information Dissemination in Limit Order Markets | 2013 | 0 |
| 10 | Asymmetry of technical analysis and market price volatility | 2009 | 1 |
| 11 | Power-Law Behaviour , Heterogeneity, and Trend Chasing | 2009 | 5 |
| 12 | A Framework for CAPM with Heterogenous Beliefs | 2009 | 1 |
| 13 | Heterogeneity, Convergence, and Autocorrelations | 2008 | 1 |
| 14 | Long Memory, Heterogeneity, and Trend Chasing | 2005 | 3 |
| 15 | A dynamic analysis of moving average rules$ | 2004 | 119 |
| 16 | Fading Memory Learning in the Cobweb Model with Risk Averse Heterogeneous Producers | 2003 | 4 |
| 17 | 1997 | 85 | |
| 18 | 1996 | 109 | |
| 19 | 1993 | 32 | |
| 20 | 1991 | 62 |
About Xue‐Zhong He
Xue‐Zhong He is a scholar working on Finance, Economics and Econometrics and Numerical Analysis, having authored 121 papers that have together received 3.3k indexed citations. Recurring topics across this work include Complex Systems and Time Series Analysis (71 papers), Financial Markets and Investment Strategies (57 papers), Financial Risk and Volatility Modeling (22 papers), Economic theories and models (18 papers), Mathematical and Theoretical Epidemiology and Ecology Models (17 papers), Market Dynamics and Volatility (16 papers), Stock Market Forecasting Methods (16 papers) and Nonlinear Differential Equations Analysis (11 papers). The work is most often cited by research in Finance (958 citations), Computer Networks and Communications (1.1k citations) and Statistical and Nonlinear Physics (559 citations). Xue‐Zhong He has collaborated with scholars based in Australia, China and Italy. Frequent co-authors include K. Gopalsamy, Carl Chiarella, Kai Li, Youwei Li, Shigui Ruan, Cars Hommes, Roberto Dieci, Jibin Li, Min Zheng and Frank Westerhoff.
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.