![Anqi Liu](https://profiles-cardiff.imgix.net/attachments/191?w=200&h=200&auto=format&crop=faces&fit=crop&q=90")
Dr Anqi Liu
Uwch Ddarlithydd mewn Mathemateg Ariannol
- Ar gael fel goruchwyliwr ôl-raddedig
Trosolwyg
Research Group
Operational Research Group
Research Interests
- Market microstructure
- Irrational trading behaviour
- Application of Hawkes process in financial markets
- Noise trading risk modeling
- Investor sentiment in portfolio management
Cyhoeddiad
2024
- Wu, F., Liu, A., Chen, J. and Li, Y. 2024. Analysing network dynamics: The contagion effects of SVB's collapse on the US tech industry. Journal of Risk and Financial Management 17(10), article number: 427. (10.3390/jrfm17100427)
- Zhang, J., Wang, H., Chen, J. and Liu, A. 2024. Cryptocurrency price bubble detection using log-periodic power law model and wavelet analysis. IEEE Transactions on Engineering Management 71, pp. 11796-1812. (10.1109/TEM.2024.3427647)
- Leonenko, N., Liu, A. and Shchestyuk, N. 2024. Student models for a risky asset with dependence: Option pricing and Greeks. Austrian Journal of Statistics 54(1), pp. 138–165.
2023
- Liu, A., Jahanshahloo, H., Chen, J. and Eshraghi, A. 2023. Trading patterns in the Bitcoin market. European Journal of Finance (10.1080/1351847X.2023.2241883)
2021
- Chen, J. and Liu, A. 2021. Information transition in trading and its effect on market efficiency: an entropy approach. Presented at: 1st International Forum on Financial Mathematics and FinTech, Beijing, China, 29 June - 2 July 2019Proceeding of the First International Academic Forum on Financial Mathematics and Financial Technology. Financial Mathematics and Fintech Springer pp. 59-77.
2020
- Liu, A., Chen, J., Yang, S. Y. and Hawkes, A. G. 2020. The flow of information in trading: an entropy approach to market regimes. Entropy 22(9), article number: 1064. (10.3390/e22091064)
- Liu, A., Paddrik, M., Yang, S. Y. and Zhang, X. 2020. Interbank contagion: an agent-based model approach to endogenously formed networks. Journal of Banking and Finance 112, article number: 105191. (10.1016/j.jbankfin.2017.08.008)
2018
- Liu, A., Mo, C. Y. J., Paddrik, M. E. and Yang, S. Y. 2018. An agent-based approach to interbank market lending decisions and risk implications. Information 9(6), pp. 1-18., article number: 132. (10.3390/info9060132)
- Yang, S. Y., Liu, A., Chen, J. and Hawkes, A. G. 2018. Applications of multi-variate Hawkes process to joint modelling of sentiment and market return events. Quantitative Finance 18(2), pp. 295-310. (10.1080/14697688.2017.1403156)
2017
- Yang, S. Y., Mo, S. Y. K., Liu, A. and Kirilenko, A. A. 2017. Genetic programming optimization for a sentiment feedback strength based trading strategy. Neurocomputing 264, pp. 29-41. (10.1016/j.neucom.2016.10.103)
- Song, Q., Liu, A. and Yang, S. 2017. Stock portfolio selection using learning-to-rank algorithms with news sentiment. Neurocomputing 264, pp. 20-28. (10.1016/j.neucom.2017.02.097)
2016
- Mo, S. Y. K., Liu, A. and Yang, S. Y. 2016. News sentiment to market impact and its feedback effect. Environment Systems and Decisions 36(2), pp. 158-166. (10.1007/s10669-016-9590-9)
- Song, Q., Liu, A., Yang, S. Y., Deane, A. and Datta, K. 2016. An extreme firm-specific news sentiment asymmetry based trading strategy. Presented at: 2015 IEEE Symposium on Computational Intelligence, Cape Town, South Africa, 7-10 December 20152015 IEEE Symposium Series on Computational Intelligence. IEEE pp. 898., (10.1109/SSCI.2015.132)
2015
- Yang, S. Y., Mo, S. Y. K. and Liu, A. 2015. Twitter financial community sentiment and its predictive relationship to stock market movement. Quantitative Finance 15(10), pp. 1637-1656. (10.1080/14697688.2015.1071078)
2014
- Yang, S. Y., Liu, A. and Mo, S. Y. K. 2014. Twitter financial community modeling using agent based simulation. Presented at: 2014 Computational Intelligence for Financial Engineering & Economics (CIFEr), London, UK, 27-28 March 20142014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr). IEEE, (10.1109/CIFEr.2014.6924055)
Articles
- Wu, F., Liu, A., Chen, J. and Li, Y. 2024. Analysing network dynamics: The contagion effects of SVB's collapse on the US tech industry. Journal of Risk and Financial Management 17(10), article number: 427. (10.3390/jrfm17100427)
- Zhang, J., Wang, H., Chen, J. and Liu, A. 2024. Cryptocurrency price bubble detection using log-periodic power law model and wavelet analysis. IEEE Transactions on Engineering Management 71, pp. 11796-1812. (10.1109/TEM.2024.3427647)
- Leonenko, N., Liu, A. and Shchestyuk, N. 2024. Student models for a risky asset with dependence: Option pricing and Greeks. Austrian Journal of Statistics 54(1), pp. 138–165.
- Liu, A., Jahanshahloo, H., Chen, J. and Eshraghi, A. 2023. Trading patterns in the Bitcoin market. European Journal of Finance (10.1080/1351847X.2023.2241883)
- Liu, A., Chen, J., Yang, S. Y. and Hawkes, A. G. 2020. The flow of information in trading: an entropy approach to market regimes. Entropy 22(9), article number: 1064. (10.3390/e22091064)
- Liu, A., Paddrik, M., Yang, S. Y. and Zhang, X. 2020. Interbank contagion: an agent-based model approach to endogenously formed networks. Journal of Banking and Finance 112, article number: 105191. (10.1016/j.jbankfin.2017.08.008)
- Liu, A., Mo, C. Y. J., Paddrik, M. E. and Yang, S. Y. 2018. An agent-based approach to interbank market lending decisions and risk implications. Information 9(6), pp. 1-18., article number: 132. (10.3390/info9060132)
- Yang, S. Y., Liu, A., Chen, J. and Hawkes, A. G. 2018. Applications of multi-variate Hawkes process to joint modelling of sentiment and market return events. Quantitative Finance 18(2), pp. 295-310. (10.1080/14697688.2017.1403156)
- Yang, S. Y., Mo, S. Y. K., Liu, A. and Kirilenko, A. A. 2017. Genetic programming optimization for a sentiment feedback strength based trading strategy. Neurocomputing 264, pp. 29-41. (10.1016/j.neucom.2016.10.103)
- Song, Q., Liu, A. and Yang, S. 2017. Stock portfolio selection using learning-to-rank algorithms with news sentiment. Neurocomputing 264, pp. 20-28. (10.1016/j.neucom.2017.02.097)
- Mo, S. Y. K., Liu, A. and Yang, S. Y. 2016. News sentiment to market impact and its feedback effect. Environment Systems and Decisions 36(2), pp. 158-166. (10.1007/s10669-016-9590-9)
- Yang, S. Y., Mo, S. Y. K. and Liu, A. 2015. Twitter financial community sentiment and its predictive relationship to stock market movement. Quantitative Finance 15(10), pp. 1637-1656. (10.1080/14697688.2015.1071078)
Conferences
- Chen, J. and Liu, A. 2021. Information transition in trading and its effect on market efficiency: an entropy approach. Presented at: 1st International Forum on Financial Mathematics and FinTech, Beijing, China, 29 June - 2 July 2019Proceeding of the First International Academic Forum on Financial Mathematics and Financial Technology. Financial Mathematics and Fintech Springer pp. 59-77.
- Song, Q., Liu, A., Yang, S. Y., Deane, A. and Datta, K. 2016. An extreme firm-specific news sentiment asymmetry based trading strategy. Presented at: 2015 IEEE Symposium on Computational Intelligence, Cape Town, South Africa, 7-10 December 20152015 IEEE Symposium Series on Computational Intelligence. IEEE pp. 898., (10.1109/SSCI.2015.132)
- Yang, S. Y., Liu, A. and Mo, S. Y. K. 2014. Twitter financial community modeling using agent based simulation. Presented at: 2014 Computational Intelligence for Financial Engineering & Economics (CIFEr), London, UK, 27-28 March 20142014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr). IEEE, (10.1109/CIFEr.2014.6924055)
Ymchwil
Anqi’s research interests include behavioural finance, sentiment analysis and Hawkes process in finance. She has been collaborating with a number of financial researchers in the area of quantitative finance and computational finance, and has published a series of papers in international journals and conferences. The overall goal of this research line is to improve the existing pricing and risk modelling framework for financial markets. She believes that interpretations to irrational trading behaviour will provide insights to market inefficiency. Recently, she mainly focuses on Hawkes process of modelling interactions between price and investor sentiment jumps.
Addysgu
Finance II (2018 Spring)
Bywgraffiad
Dr Anqi Liu holds BSc in Mathematics and Applied Mathematics from the Northwest University, China; MSc and PhD in Financial Engineering from Stevens Institute of Technology, USA. She received Stevens Innovation and Entrepreneurship Scholarship for 4 years during her PhD.
Anqi’s research interests include behavioural finance, sentiment analysis and Hawkes process in finance. She has been collaborating with a number of financial researchers in the area of quantitative finance and computational finance, and has published a series of papers in international journals and conferences. The overall goal of this research line is to improve the existing pricing and risk modelling framework for financial markets. She believes that interpretations to irrational trading behaviour will provide insights to market inefficiency. Recently, she mainly focuses on Hawkes process of modelling interactions between price and investor sentiment jumps.
Meysydd goruchwyliaeth
- Cryptocurrency market microstructure.
- Hawkes processes applications in Finance.
- Agent-based modelling in behavioural finance.
Contact Details
LiuA5@caerdydd.ac.uk
+44 29208 70908
Abacws, Ystafell Abacws/4.49, Ffordd Senghennydd, Cathays, Caerdydd, CF24 4AG
+44 29208 70908
Abacws, Ystafell Abacws/4.49, Ffordd Senghennydd, Cathays, Caerdydd, CF24 4AG
