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Dr Anqi Liu
- Ar gael fel goruchwyliwr ôl-raddedig
Timau a rolau for Anqi Liu
Uwch Ddarlithydd
Mathemateg
Uwch Ddarlithydd mewn Mathemateg Ariannol
Trosolwg
Grŵp Ymchwil
Grŵp Ymchwil Gweithredol
Diddordebau Ymchwil
- Proses Hawkes mewn cyllid.
- Rhwydweithiau ariannol.
- Technoleg ariannol (FinTech) fel cryptocurrencies, economi ddigidol, marchnadoedd newydd.
- Modelu cynnig Brownian geometrig amser gweithgaredd ffractal (FATGBM) ar gyfer prisio deilliadol.
- Microstrwythur y farchnad ac ymddygiad masnachu.
Grantiau Ymchwil
- Sefydlu Dangosydd Anwadalrwydd Cryptocurrency gyda Sentiment (CVIS). DP. Ariannwr: Ffrwd Ariannu Peilot UKFin+ £18,991. Ebrill 2025 - Gorffennaf 2025.
- Lliniaru Straen a Dryswch mewn Contractau Credyd gan ddefnyddio Dysgu Peiriant a Symleiddio. DP. Ariannwr: Ffrwd Ariannu Hyblyg UKFin+ £10,000. Chwefror 2025 - Mehefin 2025.
- Typoleg Masnachwyr Cryptocurrency: Dadansoddi Masnachu Cryptocurrency gan ddefnyddio Patrymau Ymddygiad Manwl. Cyd-I. Ariannwr: Prosiect Super Sbrint Cyflymydd Cenedl Data Cymru (WDNA) £27,599. Ionawr 2022 - Mawrth 2022.
Cyhoeddiad
2026
- Zhang, R. et al., 2026. Spatial-temporal dynamics for enhanced temporal link prediction in stock market crisis forecasting. Presented at: 2026 IEEE International Conference on Systems, Man, and Cybernetics (SMC) Bellevue, WA, USA 4-7 October 2026. SMC 2026 Conference Proceedings. IEEE.
2025
- Corcoran, P. et al. 2025. A spatial analysis of the use of Bitcoin as a medium of exchange. Financial Innovation 11 127. (10.1186/s40854-025-00871-z)
- Han, B. et al. 2025. Can machine learning models better volatility forecasting? A combined method. European Journal of Finance (10.1080/1351847X.2025.2553053)
- Leonenko, N. , Liu, A. and Shchestyuk, N. 2025. Student models for a risky asset with dependence: Option pricing and Greeks. Austrian Journal of Statistics 54 (1), pp.138-165. (10.17713/ajs.v54i1.1952)
2024
- Wu, F. et al. 2024. Analysing network dynamics: The contagion effects of SVB's collapse on the US tech industry. Journal of Risk and Financial Management 17 (10) 427. (10.3390/jrfm17100427)
- Zhang, J. et al., 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)
2023
- Liu, A. et al. 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 2019. Proceeding of the First International Academic Forum on Financial Mathematics and Financial Technology. Financial Mathematics and Fintech Springer. , pp.59-77. (10.1007/978-981-15-8373-5_4)
2020
- Liu, A. et al. 2020. The flow of information in trading: an entropy approach to market regimes. Entropy 22 (9) 1064. (10.3390/e22091064)
- Liu, A. et al. 2020. Interbank contagion: an agent-based model approach to endogenously formed networks. Journal of Banking and Finance 112 105191. (10.1016/j.jbankfin.2017.08.008)
2018
- Liu, A. et al. 2018. An agent-based approach to interbank market lending decisions and risk implications. Information 9 (6), pp.1-18. 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 2015. 2015 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 2014. 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr). IEEE(10.1109/CIFEr.2014.6924055)
Cynadleddau
- Zhang, R. et al., 2026. Spatial-temporal dynamics for enhanced temporal link prediction in stock market crisis forecasting. Presented at: 2026 IEEE International Conference on Systems, Man, and Cybernetics (SMC) Bellevue, WA, USA 4-7 October 2026. SMC 2026 Conference Proceedings. IEEE.
- 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 2019. Proceeding of the First International Academic Forum on Financial Mathematics and Financial Technology. Financial Mathematics and Fintech Springer. , pp.59-77. (10.1007/978-981-15-8373-5_4)
- 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 2015. 2015 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 2014. 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr). IEEE(10.1109/CIFEr.2014.6924055)
Erthyglau
- Corcoran, P. et al. 2025. A spatial analysis of the use of Bitcoin as a medium of exchange. Financial Innovation 11 127. (10.1186/s40854-025-00871-z)
- Han, B. et al. 2025. Can machine learning models better volatility forecasting? A combined method. European Journal of Finance (10.1080/1351847X.2025.2553053)
- Leonenko, N. , Liu, A. and Shchestyuk, N. 2025. Student models for a risky asset with dependence: Option pricing and Greeks. Austrian Journal of Statistics 54 (1), pp.138-165. (10.17713/ajs.v54i1.1952)
- Wu, F. et al. 2024. Analysing network dynamics: The contagion effects of SVB's collapse on the US tech industry. Journal of Risk and Financial Management 17 (10) 427. (10.3390/jrfm17100427)
- Zhang, J. et al., 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)
- Liu, A. et al. 2023. Trading patterns in the Bitcoin market. European Journal of Finance (10.1080/1351847X.2023.2241883)
- Liu, A. et al. 2020. The flow of information in trading: an entropy approach to market regimes. Entropy 22 (9) 1064. (10.3390/e22091064)
- Liu, A. et al. 2020. Interbank contagion: an agent-based model approach to endogenously formed networks. Journal of Banking and Finance 112 105191. (10.1016/j.jbankfin.2017.08.008)
- Liu, A. et al. 2018. An agent-based approach to interbank market lending decisions and risk implications. Information 9 (6), pp.1-18. 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)
- 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)
- 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)
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
Mae gan Dr Anqi Liu BSc mewn Mathemateg a Mathemateg Gymhwysol o Brifysgol y Gogledd-orllewin, Tsieina; ac MSc a PhD mewn Peirianneg Ariannol o Sefydliad Technoleg Stevens, UDA. Mae ei harbenigedd yn gorwedd mewn cyllid meintiol a chyfrifiadurol, gyda ffocws ymchwil sylfaenol ar farchnadoedd cryptocurrency. Mae ei diddordebau ymchwil ehangach yn cynnwys rhwydweithiau ariannol a modelu systemau, prosesau Hawkes mewn cyllid, modelau cyfres amser ariannol, ac efelychiadau ymddygiad masnachu. Mae hi wedi sefydlu sgiliau amlddisgyblaethol a record ymchwil gref mewn cyllid empirig a modelu ariannol sy'n cael ei yrru gan AI. Yn ystod y blynyddoedd diwethaf, mae hi wedi arwain a chyd-arwain prosiectau FinTech a ariennir gan Rwydwaith UKFin+ a Sefydliad Alan Turing, gan gyfrannu at ddatblygu cydweithrediadau academaidd-diwydiannol ystyrlon. Mae hi wedi bod yn Olygydd Cyswllt ar gyfer International Review of Economics and Finance, ac yn Olygydd Gwadd ar gyfer The Journal of Futures Markets.
Meysydd goruchwyliaeth
- Microstrwythur y farchnad cryptocurrency.
- Mae Hawkes yn prosesu ceisiadau mewn Cyllid.
- Rhwydweithiau ariannol a risgiau systemig.
Goruchwyliaeth gyfredol
News articles
Contact Details
[email protected]
+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
