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.
TESTING FOR MULTIPLE BUBBLES: HISTORICAL EPISODES OF EXUBERANCE AND COLLAPSE IN THE S&P 500
2015743 citationsPeter C.B. Phillips, Shuping Shi et al.profile →
EXPLOSIVE BEHAVIOR IN THE 1990s NASDAQ: WHEN DID EXUBERANCE ESCALATE ASSET VALUES?*
2011738 citationsPeter C.B. Phillips, Jun Yu et al.profile →
Testing for multiple bubbles: limit theory of real-time detectors: Testing for multiple bubbles
2015314 citationsPeter C.B. Phillips, Shuping Shi et al.ePrints Soton (University of Southampton)profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Jun Yu'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 Jun Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Yu more than expected).
This network shows the impact of papers produced by Jun Yu. 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 Jun Yu. The network helps show where Jun Yu may publish in the future.
Co-authorship network of co-authors of Jun Yu
This figure shows the co-authorship network connecting the top 25 collaborators of Jun Yu.
A scholar is included among the top collaborators of Jun Yu 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 Jun Yu. Jun Yu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Yu, Jun, et al.. (2020). Econometric methods and data Science techniques: A review of two strands of literature and an introduction to hybrid methods. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 1.1 indexed citations
11.
Phillips, Peter C.B., Shuping Shi, & Jun Yu. (2015). Testing for multiple bubbles: limit theory of real-time detectors: Testing for multiple bubbles. ePrints Soton (University of Southampton).314 indexed citations breakdown →
12.
Chen, Chunsheng, et al.. (2015). Bayesian and Empirical Bayesian Forests. International Conference on Machine Learning. 967–976.8 indexed citations
13.
Liu, Qianqiu, et al.. (2007). Realized Daily Variance of S&P 500 Cash Index: A Revaluation of Stylized Facts *. Annals of economics and finance. 8(1). 33–56.7 indexed citations
14.
Gouriéroux, Christian, Peter C.B. Phillips, & Jun Yu. (2006). Indirect Inference for Dynamic Panel Models. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University).10 indexed citations
15.
Phillips, Peter C.B. & Jun Yu. (2006). Realized Variance and Market Microstructure Noise - Comment. Journal of Business and Economic Statistics. 24(2). 202–208.9 indexed citations
16.
Phillips, Peter C.B. & Jun Yu. (2005). A Two-Stage Realized Volatility Approach to the Estimation for Diffusion Processes from Discrete Observations. SSRN Electronic Journal.3 indexed citations
Yu, Jun & Peter C.B. Phillips. (2001). Gaussian Estimation of Continuous Time Models of the Short Term Interest Rate. SSRN Electronic Journal.1 indexed citations
19.
Shao, Qi-Man, Yu Hao, & Jun Yu. (2001). Do Stock Returns Follow a Finite Variance Distribution. Annals of economics and finance. 2(2). 467–486.8 indexed citations
20.
Yu, Jun. (2000). Genesis and Significance of Quartz Cement in Sandstones.2 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.