Dr Anqi Liu
Lecturer in Financial Mathematics
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
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.
2020
- Liu, A.et al. 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)
- Chen, J. and Liu, A. 2020. 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. Springer
2018
- Liu, A.et al. 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.et al. 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
- 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)
- Yang, S. Y.et al. 2017. Genetic programming optimization for a sentiment feedback strength based trading strategy. Neurocomputing 264, pp. 29-41. (10.1016/j.neucom.2016.10.103)
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.et al. 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)
Finance II (2018 Spring)
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.
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