Hung‐Chun Liu

801 total citations
39 papers, 559 citations indexed

About

Hung‐Chun Liu is a scholar working on Economics and Econometrics, Finance and Information Systems. According to data from OpenAlex, Hung‐Chun Liu has authored 39 papers receiving a total of 559 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Economics and Econometrics, 22 papers in Finance and 15 papers in Information Systems. Recurrent topics in Hung‐Chun Liu's work include Market Dynamics and Volatility (26 papers), Blockchain Technology Applications and Security (14 papers) and Financial Markets and Investment Strategies (13 papers). Hung‐Chun Liu is often cited by papers focused on Market Dynamics and Volatility (26 papers), Blockchain Technology Applications and Security (14 papers) and Financial Markets and Investment Strategies (13 papers). Hung‐Chun Liu collaborates with scholars based in Taiwan, China and United States. Hung‐Chun Liu's co-authors include Jui‐Cheng Hung, Ming‐Chih Lee, Jying‐Nan Wang, Yuan‐Teng Hsu, Yen‐Hsien Lee, J. Jimmy Yang, Justin Yang, Chun‐Hua Hsu, Jeng Chang and Hung‐Yun Lin and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Virology and Expert Systems with Applications.

In The Last Decade

Hung‐Chun Liu

34 papers receiving 530 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hung‐Chun Liu Taiwan 14 399 287 110 102 79 39 559
Ahamuefula E. Ogbonna Nigeria 16 596 1.5× 188 0.7× 117 1.1× 138 1.4× 56 0.7× 46 688
Oğuzhan Çepni Denmark 12 498 1.2× 232 0.8× 43 0.4× 91 0.9× 53 0.7× 40 581
Jui‐Cheng Hung Taiwan 13 472 1.2× 387 1.3× 47 0.4× 176 1.7× 86 1.1× 36 603
Nektarios Aslanidis Spain 14 610 1.5× 287 1.0× 130 1.2× 121 1.2× 35 0.4× 40 706
Onur Polat Türkiye 13 555 1.4× 186 0.6× 80 0.7× 93 0.9× 54 0.7× 48 681
Jan Jakub Szczygielski South Africa 12 427 1.1× 212 0.7× 58 0.5× 50 0.5× 44 0.6× 37 536
Tomáš Výrost Slovakia 12 604 1.5× 331 1.2× 37 0.3× 85 0.8× 71 0.9× 35 717
Gbenga Ibikunle United Kingdom 13 426 1.1× 293 1.0× 60 0.5× 26 0.3× 121 1.5× 54 639
Hachmi Ben Ameur France 15 496 1.2× 247 0.9× 53 0.5× 90 0.9× 76 1.0× 52 648
Adrián Fernández-Pérez New Zealand 14 593 1.5× 335 1.2× 52 0.5× 184 1.8× 57 0.7× 65 685

Countries citing papers authored by Hung‐Chun Liu

Since Specialization
Citations

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

Fields of papers citing papers by Hung‐Chun Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hung‐Chun Liu. 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 Hung‐Chun Liu. The network helps show where Hung‐Chun Liu may publish in the future.

Co-authorship network of co-authors of Hung‐Chun Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Hung‐Chun Liu. A scholar is included among the top collaborators of Hung‐Chun Liu 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 Hung‐Chun Liu. Hung‐Chun Liu 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.
Wang, Jying‐Nan, Hung‐Chun Liu, & Yuan‐Teng Hsu. (2025). Do AI incidents and hazards matter for AI-themed cryptocurrency returns?. Finance research letters. 74. 106777–106777.
2.
Hsieh, Chia‐Hsun, et al.. (2025). State transitions and momentum effect in cryptocurrency market. Finance research letters. 86. 108356–108356. 1 indexed citations
3.
Dong, Xiaohong, et al.. (2025). The impact of customer risk on Enterprises' strategic change: Evidence from China. International Review of Financial Analysis. 100. 103981–103981. 2 indexed citations
4.
Chiu, Ya-Ling, et al.. (2025). Financial literacy of ChatGPT: Evidence through financial news. Finance research letters. 78. 107088–107088.
5.
Wang, Jying‐Nan, Samuel A. Vigne, Hung‐Chun Liu, & Yuan‐Teng Hsu. (2024). Divergent jump characteristics in brown and green cryptocurrencies: The role of energy-related uncertainty. Energy Economics. 138. 107847–107847. 5 indexed citations
6.
Liu, Hung‐Chun, et al.. (2024). ESG risk, economic policy uncertainty, and the downside risk: Evidence from US firms. The North American Journal of Economics and Finance. 75. 102293–102293. 11 indexed citations
7.
Lee, Yen‐Hsien, et al.. (2024). Exploring the unpredictable nature of climate policy uncertainty: An empirical analysis of its impact on commodity futures returns in the United States. Journal of Futures Markets. 44(7). 1277–1292. 3 indexed citations
8.
Hung, Jui‐Cheng, Hung‐Chun Liu, & J. Jimmy Yang. (2024). The economic value of Bitcoin: A volatility timing perspective with portfolio rebalancing. The North American Journal of Economics and Finance. 74. 102260–102260.
9.
Wang, Jying‐Nan, Hung‐Chun Liu, & Yuan‐Teng Hsu. (2023). A U-shaped relationship between the crypto fear-greed index and the price synchronicity of cryptocurrencies. Finance research letters. 59. 104763–104763. 10 indexed citations
10.
Wang, Jying‐Nan, Yen‐Hsien Lee, Hung‐Chun Liu, & Yuan‐Teng Hsu. (2023). Dissecting returns of non-fungible tokens (NFTs): Evidence from CryptoPunks. The North American Journal of Economics and Finance. 65. 101892–101892. 17 indexed citations
11.
Wang, Jying‐Nan, Hung‐Chun Liu, Yen‐Hsien Lee, & Yuan‐Teng Hsu. (2023). FoMO in the Bitcoin market: Revisiting and factors. The Quarterly Review of Economics and Finance. 89. 244–253. 15 indexed citations
12.
Hung, Jui‐Cheng, Hung‐Chun Liu, & Jie Yang. (2022). Does the tail risk index matter in forecasting downside risk?. International Journal of Finance & Economics. 28(3). 3451–3466. 1 indexed citations
13.
Hung, Jui‐Cheng, Hung‐Chun Liu, & J. Jimmy Yang. (2021). Trading activity and price discovery in Bitcoin futures markets. Journal of Empirical Finance. 62. 107–120. 35 indexed citations
14.
Wang, Jying‐Nan, et al.. (2020). How does the informed trading impact Bitcoin returns and volatility?. Applied Economics. 53(28). 3223–3233. 14 indexed citations
15.
Wang, Jying‐Nan, et al.. (2019). On the predictive power of ARJI volatility forecasts for Bitcoin. Applied Economics. 51(44). 4849–4855. 20 indexed citations
16.
Wang, Jying‐Nan, Hung‐Chun Liu, & Yuan‐Teng Hsu. (2019). Time-of-day periodicities of trading volume and volatility in Bitcoin exchange: Does the stock market matter?. Finance research letters. 34. 101243–101243. 27 indexed citations
17.
Liu, Hung‐Chun, et al.. (2017). The role of SGT distribution in Value-at-Risk estimation: evidence from the WTI crude oil market. Investment Management and Financial Innovations. 6(1). 1 indexed citations
18.
Wang, Jying‐Nan, et al.. (2017). On Forecasting Taiwanese Stock Index Option Prices: The Role of Implied Volatility Index. International Journal of Economics and Finance. 9(9). 133–133. 2 indexed citations
19.
Wang, Jying‐Nan, Yuan‐Teng Hsu, & Hung‐Chun Liu. (2014). How useful are the Various Volatility Estimators for Improving GARCH-based Volatility Forecasts? Evidence from the Nasdaq-100 Stock Index. International Journal of Economics and Financial Issues. 4(3). 651–656. 3 indexed citations
20.
Liu, Hung‐Chun, et al.. (2009). Value-at-Risk-based risk management on exchange traded funds: the Taiwanese experience. SHILAP Revista de lepidopterología.

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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