This map shows the geographic impact of Shu‐Heng Chen'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 Shu‐Heng Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shu‐Heng Chen more than expected).
This network shows the impact of papers produced by Shu‐Heng Chen. 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 Shu‐Heng Chen. The network helps show where Shu‐Heng Chen may publish in the future.
Co-authorship network of co-authors of Shu‐Heng Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Shu‐Heng Chen.
A scholar is included among the top collaborators of Shu‐Heng Chen 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 Shu‐Heng Chen. Shu‐Heng Chen is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Chen, Shu‐Heng, et al.. (2004). Behavior Finance and Agent-Based Computational Finance: Toward an Integrating Framework. 8(8).5 indexed citations
9.
Yeh, Chia-Hsuan & Shu‐Heng Chen. (2001). Market Diversity and Market Efficiency: The Approach Based on Genetic Programming. 1(1).10 indexed citations
10.
Chen, Shu‐Heng, et al.. (2001). Trading Strategies on Trial: A Comprehensive Review of 21 Practical Trading Strategies over 56 Listed Stocks. Computational intelligence. 66.1 indexed citations
11.
Yeh, Chia-Hsuan & Shu‐Heng Chen. (2001). The Influence of Market Size in an Artificial Stock Market: The Approach Based on Genetic Programming.3 indexed citations
12.
Chen, Shu‐Heng, et al.. (1999). Towards an agent-based foundation of financial econometrics: an approach based on genetic-programming artificial markets. Genetic and Evolutionary Computation Conference. 966–966.3 indexed citations
13.
Chen, Shu‐Heng, Thomas Lux, & Michele Marchesi. (1999). Testing for Non-Linear Structure in an Artificial Financial Market. RePEc: Research Papers in Economics.2 indexed citations
14.
Chen, Shu‐Heng, et al.. (1999). Forecasting High-Frequency Financial Time Series with Evolutionary Neural Trees: The Case of Heng-Sheng Stock Index.. International Conference on Artificial Intelligence. 437–443.7 indexed citations
15.
Chen, Shu‐Heng, et al.. (1999). Testing for Granger Causality in the Stock Price-Volume Relation: A Perspective from the Agent-Based Model of Stock Markets.. International Conference on Artificial Intelligence. 374–380.
16.
Chen, Shu‐Heng, et al.. (1999). Genetic algorithms, trading strategies and stochastic processes: some new evidence from Monte Carlo simulations. Genetic and Evolutionary Computation Conference. 114–121.1 indexed citations
17.
Chen, Shu‐Heng, et al.. (1999). Discovering Trading Rules with Genetic Algorithms: An Empirical Study Based on GARCH Time Series.. International Conference on Artificial Intelligence. 430–436.2 indexed citations
18.
Chen, Shu‐Heng, et al.. (1997). Option Pricing with Genetic Algorithms: The Case of European-Style Options.. international conference on Genetic algorithms. 704–711.7 indexed citations
19.
Chen, Shu‐Heng & Chia-Hsuan Yeh. (1996). Genetic Programming in Computable Financial Economics. Computers and Their Applications.1 indexed citations
20.
Chen, Shu‐Heng, John Duffy, & Chia-Hsuan Yeh. (1996). Genetic Programming in the Coordination Game with a Chaotic Best-Response Function. 277–286.10 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.