Zhifeng Dai

2.6k total citations · 1 hit paper
79 papers, 1.9k citations indexed

About

Zhifeng Dai is a scholar working on Economics and Econometrics, Management Science and Operations Research and Finance. According to data from OpenAlex, Zhifeng Dai has authored 79 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Economics and Econometrics, 29 papers in Management Science and Operations Research and 25 papers in Finance. Recurrent topics in Zhifeng Dai's work include Market Dynamics and Volatility (35 papers), Stock Market Forecasting Methods (23 papers) and Financial Markets and Investment Strategies (18 papers). Zhifeng Dai is often cited by papers focused on Market Dynamics and Volatility (35 papers), Stock Market Forecasting Methods (23 papers) and Financial Markets and Investment Strategies (18 papers). Zhifeng Dai collaborates with scholars based in China, United States and Iran. Zhifeng Dai's co-authors include Fenghua Wen, Haoyang Zhu, Xiaotong Zhang, Xinhua Zhang, Shaoyi He, Xiaohong Chen, Zhujia Yin, Rui Tang, Jie Kang and Peng Yong-xin and has published in prestigious journals such as Physical Review Letters, Expert Systems with Applications and Energy Economics.

In The Last Decade

Zhifeng Dai

74 papers receiving 1.9k citations

Hit Papers

Climate policy uncertaint... 2023 2026 2024 2023 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhifeng Dai China 28 1.1k 505 367 355 271 79 1.9k
Hélyette Geman United Kingdom 30 2.5k 2.1× 4.3k 8.6× 690 1.9× 160 0.5× 206 0.8× 88 5.3k
Álvaro Cartea United Kingdom 24 959 0.8× 1.2k 2.4× 427 1.2× 90 0.3× 77 0.3× 119 1.9k
Mark Broadie United States 35 1.5k 1.3× 4.7k 9.3× 909 2.5× 376 1.1× 41 0.2× 80 5.6k
Huifu Xu United Kingdom 25 302 0.3× 146 0.3× 1.1k 3.1× 211 0.6× 23 0.1× 95 1.8k
John C. Hull Canada 22 1.1k 0.9× 2.7k 5.4× 344 0.9× 43 0.1× 23 0.1× 53 3.2k
Michael J. Klass United States 14 950 0.8× 1.2k 2.3× 403 1.1× 58 0.2× 42 0.2× 58 1.8k
Arun J. Prakash United States 17 401 0.3× 610 1.2× 338 0.9× 67 0.2× 10 0.0× 101 1.5k
Michael Zabarankin United States 20 464 0.4× 724 1.4× 993 2.7× 34 0.1× 8 0.0× 70 1.8k
Sandra Paterlini Italy 19 354 0.3× 506 1.0× 371 1.0× 12 0.0× 14 0.1× 88 1.3k
Majid Soleimani-damaneh Iran 20 260 0.2× 69 0.1× 810 2.2× 318 0.9× 48 0.2× 110 1.4k

Countries citing papers authored by Zhifeng Dai

Since Specialization
Citations

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

Fields of papers citing papers by Zhifeng Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhifeng Dai

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

All Works

20 of 20 papers shown
1.
Dai, Zhifeng, et al.. (2025). Climate policy uncertainty and corporate ESG performance: evidence from Chinese listed companies. China Finance Review International. 15(3). 578–607. 4 indexed citations
2.
Dai, Zhifeng, et al.. (2025). A “parallel” combined Transformer-CNN model using secondary decomposition for crude oil forecasting. Expert Systems with Applications. 299. 129968–129968.
3.
Dai, Zhifeng, et al.. (2025). Systemic Risk Spillover of Oil, Gold to China Financial Market: New Evidence From a Copula-CoVaR-MODWT Approach. Evaluation Review. 193841X251394455–193841X251394455.
4.
Dai, Zhifeng, et al.. (2025). Stock return predictability in the frequency domain. International Journal of Forecasting. 41(3). 1126–1147.
5.
Chen, Yaling, et al.. (2025). The impact of climate policy uncertainty on the correlations between green bond and green stock markets. International Review of Financial Analysis. 102. 104046–104046. 3 indexed citations
6.
Dai, Zhifeng, et al.. (2024). G20 systemic risk: Are structural oil price shocks driving factors?. Expert Systems with Applications. 260. 125430–125430. 2 indexed citations
7.
Dai, Zhifeng & Rui Tang. (2024). The impact of oil price shocks on systematic risk of G7 stock markets. Expert Systems with Applications. 248. 123408–123408. 9 indexed citations
8.
Dai, Zhifeng & Tong Wu. (2024). The Impact of Oil Shocks on Systemic Risk of the Commodity Markets. Journal of Systems Science and Complexity. 37(6). 2697–2720. 28 indexed citations
9.
Dai, Zhifeng, et al.. (2024). Climate policy uncertainty and urban green total factor productivity: Evidence from China. International Review of Financial Analysis. 96. 103593–103593. 26 indexed citations
10.
Dai, Zhifeng, Xiaotong Zhang, & Zhujia Yin. (2023). Extreme time-varying spillovers between high carbon emission stocks, green bond and crude oil: Evidence from a quantile-based analysis. Energy Economics. 118. 106511–106511. 55 indexed citations
11.
Dai, Zhifeng, Rui Tang, & Xiaotong Zhang. (2023). A new multilayer network for measuring interconnectedness among the energy firms. Energy Economics. 124. 106880–106880. 12 indexed citations
12.
Dai, Zhifeng, Rui Tang, & Xinhua Zhang. (2023). Multilayer network analysis for measuring the inter-connectedness between the oil market and G20 stock markets. Energy Economics. 120. 106639–106639. 25 indexed citations
13.
Dai, Zhifeng, Zhuang Luo, & Chang Liu. (2023). Dynamic volatility spillovers and investment strategies between crude oil, new energy, and resource related sectors. Resources Policy. 83. 103681–103681. 13 indexed citations
14.
Zhu, Haoyang, et al.. (2023). Forecasting commodity prices returns: The role of partial least squares approach. Energy Economics. 125. 106825–106825. 4 indexed citations
15.
Dai, Zhifeng & Xiaotong Zhang. (2023). Climate policy uncertainty and risks taken by the bank: Evidence from China. International Review of Financial Analysis. 87. 102579–102579. 124 indexed citations breakdown →
16.
Dai, Zhifeng, Xiaotong Zhang, & Tingyu Li. (2022). Forecasting stock return volatility in data-rich environment: A new powerful predictor. The North American Journal of Economics and Finance. 64. 101845–101845. 4 indexed citations
17.
Dai, Zhifeng, et al.. (2021). Bond yield and crude oil prices predictability. Energy Economics. 97. 105205–105205. 35 indexed citations
18.
Dai, Zhifeng, et al.. (2020). A Modified Hestenes-Stiefel-Type Derivative-Free Method for Large-Scale Nonlinear Monotone Equations. Mathematics. 8(2). 168–168. 53 indexed citations
19.
Wen, Fenghua, Zhifang He, Zhifeng Dai, & Xu Gong. (2012). The Effect of Disposition Effect on Stock Price Volatility. 390–393.
20.
Dai, Zhifeng & Fenghua Wen. (2011). A modified CG-DESCENT method for unconstrained optimization. Journal of Computational and Applied Mathematics. 235(11). 3332–3341. 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.

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