Jun Tu

4.2k total citations · 2 hit papers
50 papers, 2.8k citations indexed

About

Jun Tu is a scholar working on Finance, Economics and Econometrics and General Economics, Econometrics and Finance. According to data from OpenAlex, Jun Tu has authored 50 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Finance, 29 papers in Economics and Econometrics and 15 papers in General Economics, Econometrics and Finance. Recurrent topics in Jun Tu's work include Financial Markets and Investment Strategies (41 papers), Market Dynamics and Volatility (18 papers) and Monetary Policy and Economic Impact (15 papers). Jun Tu is often cited by papers focused on Financial Markets and Investment Strategies (41 papers), Market Dynamics and Volatility (18 papers) and Monetary Policy and Economic Impact (15 papers). Jun Tu collaborates with scholars based in Singapore, China and United States. Jun Tu's co-authors include Guofu Zhou, Fuwei Jiang, David E. Rapach, Christopher J. Neely, Dashan Huang, Yongmiao Hong, Jeremy Goh, Jack Strauss, Feng Shi and Guo Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Finance and Journal of Financial Economics.

In The Last Decade

Jun Tu

46 papers receiving 2.7k citations

Hit Papers

align trajectories

What are hit papers?

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.

Investor Sentiment Aligned: A Powerful Predictor of Stock Returns

2014 753 citations Jun Tu, Guofu Zhou et al. profile →
Forecasting the Equity Risk Premium: The Role of Technical Indicators

2014 712 citations Christopher J. Neely, David E. Rapach et al. Management Science profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jun Tu Singapore	17	2.2k	1.8k	1.0k	624	409	50	2.8k
Fuwei Jiang China	17	1.5k 0.7×	1.4k 0.8×	639 0.6×	393 0.6×	548 1.3×	79	2.2k
Christopher J. Neely United States	36	3.6k 1.6×	3.2k 1.8×	1.1k 1.0×	2.4k 3.8×	386 0.9×	151	4.8k
Yiuman Tse United States	32	2.9k 1.3×	3.0k 1.6×	375 0.4×	1.3k 2.1×	612 1.5×	144	3.8k
Yangru Wu United States	26	1.9k 0.8×	2.3k 1.3×	364 0.4×	1.2k 2.0×	519 1.3×	86	3.1k
Simón Sosvilla‐Rivero Spain	28	1.2k 0.6×	2.2k 1.2×	404 0.4×	1.3k 2.1×	187 0.5×	252	3.0k
Ray Yeutien Chou Taiwan	16	3.6k 1.6×	3.2k 1.8×	398 0.4×	1.4k 2.2×	281 0.7×	34	4.3k
Hao Zhou United States	24	4.1k 1.8×	2.5k 1.4×	225 0.2×	1.0k 1.6×	601 1.5×	86	4.6k
Rossen Valkanov United States	26	3.7k 1.6×	3.5k 1.9×	718 0.7×	1.7k 2.7×	745 1.8×	59	5.0k
Thomas C. Chiang United States	28	2.8k 1.3×	3.1k 1.7×	342 0.3×	958 1.5×	634 1.6×	107	3.8k
Barbara Ostdiek United States	16	2.7k 1.2×	2.2k 1.2×	339 0.3×	900 1.4×	237 0.6×	30	3.1k

Countries citing papers authored by Jun Tu

Since Specialization

Citations

This map shows the geographic impact of Jun Tu'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 Tu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Tu more than expected).

Fields of papers citing papers by Jun Tu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Tu. 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 Tu. The network helps show where Jun Tu may publish in the future.

Co-authorship network of co-authors of Jun Tu

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Tu. A scholar is included among the top collaborators of Jun Tu 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 Tu. Jun Tu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Bu, Hui, et al.. (2025). Corporate Default Prediction through News Insights. SSRN Electronic Journal.

2.

Tu, Jun, et al.. (2025). Media Climate Change Concern and Stock Returns. Financial Management.

3.

Tu, Jun, et al.. (2024). Institutional ownership and cost of equity of Chinese firms. China Finance Review International. 16(1). 97–124. 8 indexed citations

4.

Guo, Li, et al.. (2024). Cross-cryptocurrency return predictability. Journal of Economic Dynamics and Control. 163. 104863–104863. 1 indexed citations

5.

Chen, Ying, et al.. (2023). Topic tones of analyst reports and stock returns: A deep learning approach. International Review of Finance. 23(4). 831–858. 3 indexed citations

6.

He, Xue‐Zhong, et al.. (2022). Investor Sentiment and Paradigm Shifts in Equity Return Forecasting. Management Science. 68(6). 4301–4325. 16 indexed citations

7.

Gonzalez, Angelica, et al.. (2022). Internal capital markets and predictability in complex ownership firms. Journal of Corporate Finance. 74. 102219–102219. 2 indexed citations

8.

Guo, Li, et al.. (2021). Cross-Cryptocurrency Return Predictability. SSRN Electronic Journal. 4 indexed citations

9.

Tu, Jun, et al.. (2021). Concept links and return momentum. Journal of Banking & Finance. 134. 106329–106329.

10.

Guo, Li, et al.. (2021). Media connection and return comovement. Journal of Economic Dynamics and Control. 130. 104191–104191. 1 indexed citations

11.

He, Xue‐Zhong, et al.. (2019). Investor Sentiment and Paradigm Shifts in Equity Return Forecasting. SSRN Electronic Journal. 2 indexed citations

12.

Fan, Jianqing, et al.. (2014). When Everyone Misses on the Same Side: Debiased Earnings Surprises and Stock Returns. SSRN Electronic Journal. 1 indexed citations

13.

Neely, Christopher J., David E. Rapach, Jun Tu, & Guofu Zhou. (2014). Forecasting the Equity Risk Premium: The Role of Technical Indicators. Management Science. 60(7). 1772–1791. 712 indexed citations breakdown →

14.

Tu, Jun, et al.. (2013). Multi-attribute Decision Making Based on BOCR and Choquet Integral in Reverse Auction. 16(6). 54. 1 indexed citations

15.

Neely, Christopher J., David E. Rapach, Jun Tu, & Guofu Zhou. (2011). Forecasting the Equity Risk Premium: The Role of Technical Indicators. SSRN Electronic Journal. 86 indexed citations

16.

Tu, Jun & Guofu Zhou. (2010). Incorporating Economic Objectives into Bayesian Priors: Portfolio Choice under Parameter Uncertainty. Journal of Financial and Quantitative Analysis. 45(4). 959–986. 57 indexed citations

17.

Tu, Jun. (2010). Is Regime Switching in Stock Returns Important in Portfolio Decisions?. SSRN Electronic Journal. 6 indexed citations

18.

Tu, Jun & Guofu Zhou. (2008). Incorporating Economic Objectives into Bayesian Priors: Portfolio Choice Under Parameter Uncertainty. SSRN Electronic Journal. 14 indexed citations

19.

Tu, Jun & Guofu Zhou. (2008). Being Naive about Naive Diversification: Can Investment Theory be Consistently Useful. SSRN Electronic Journal. 4 indexed citations

20.

Tu, Jun & Guofu Zhou. (2003). Data-generating process uncertainty: What difference does it make in portfolio decisions?. Journal of Financial Economics. 72(2). 385–421. 100 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.

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