Professor Charalampos Stasinakis

  • Professor of Finance (Accounting & Finance)

telephone: 0141 330 7591 / Room 678C
email: Charalampos.Stasinakis@glasgow.ac.uk

Adam Smith Business School, Accounting and Finance, Room 678C

Import to contacts

ORCID iDhttps://orcid.org/0000-0003-1017-5173

Biography

Charalampos is a Professor of Finance at the Adam Smith Business School, department of Accounting and Finance. He joined the department as a Lecturer in 2014. His academic career started in 2013 in the department of Accounting, Finance and Economics of Bournemouth University. In terms of his studies, he received a BSc and an MSc in Computer and Electrical Engineering from the National Technical University of Athens in 2010 and a PhD in Quantitative Finance from Adam Smith Business School, Economics, University of Glasgow in 2013.

Research interests

Charalampos is a member of the School's Finance research cluster.

Areas of research:

  • Quantitative finance and operational research
  • Artificial intelligence, neural networks, heuristics, machine learning, big data
  • Financial forecasting and risk management
  • Portfolio optimisation, technical analysis and banking efficiency
  • Financial technology

Publications

List by: Type | Date

Jump to: 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012
Number of items: 29.

2024

Feng, X., von Mettenheim, H.-J., Sermpinis, G. and Stasinakis, C. (2024) Sustainable portfolio construction via machine learning: ESG, SDG, and sentiment. European Financial Management, (doi: 10.1111/eufm.12531) (Early Online Publication)

Wei, M., Kyriakou, I., Sermpinis, G. and Stasinakis, C. (2024) Cryptocurrencies and Lucky Factors: the value of technical and fundamental analysis. International Journal of Finance and Economics, 29(4), pp. 4073-4104. (doi: 10.1002/ijfe.2863)

Sun, X., Stasinakis, C. and Sermpinis, G. (2024) Decentralization illusion in decentralized finance: evidence from tokenized voting in MakerDAO polls. Journal of Financial Stability, 73, 101286. (doi: 10.1016/j.jfs.2024.101286)

Da Silva Fernandes, F., Sermpinis, G. , Stasinakis, C. and Zhao, Y. (2024) Corporate social responsibility and firm survival: evidence from Chinese listed firms. British Journal of Management, 35(2), pp. 1014-1039. (doi: 10.1111/1467-8551.12750)

2023

Wei, M., Sermpinis, G. and Stasinakis, C. (2023) Forecasting and trading Bitcoin with machine learning techniques and a hybrid volatility/sentiment leverage. Journal of Forecasting, 42(4), pp. 852-871. (doi: 10.1002/for.2922)

Nguyen, D. K., Sermpinis, G. and Stasinakis, C. (2023) Big data, artificial intelligence, and machine learning: a transformative symbiosis in favour of financial technology. European Financial Management, 29(2), pp. 517-548. (doi: 10.1111/eufm.12365)

2022

Shi, Y. , Stasinakis, C. , Xu, Y., Yan, C. and Zhang, X. (2022) Stock price default boundary: A Black-Cox model approach. International Review of Financial Analysis, 83, 102284. (doi: 10.1016/j.irfa.2022.102284)

Andreev, B., Sermpinis, G. and Stasinakis, C. (2022) Modelling financial markets during times of extreme volatility: evidence from the GameStop short squeeze. Forecasting, 4(3), pp. 654-673. (doi: 10.3390/forecast4030035)

Shi, Y. , Stasinakis, C. , Xu, Y. and Yan, C. (2022) Market co-movement between credit default swap curves and option volatility surfaces. International Review of Financial Analysis, 82, 102192. (doi: 10.1016/j.irfa.2022.102192)

Li, Y., Stasinakis, C. and Yeo, W. M. (2022) A hybrid XGBoost-MLP model for credit risk assessment on Digital Supply Chain Finance. Forecasting, 4(1), pp. 184-207. (doi: 10.3390/forecast4010011)

2021

Hassanniakalager, A., Sermpinis, G. and Stasinakis, C. (2021) Trading the foreign exchange market with technical analysis and Bayesian statistics. Journal of Empirical Finance, 63, pp. 230-251. (doi: 10.1016/j.jempfin.2021.07.006)

Sermpinis, G. , Hassanniakalager, A., Stasinakis, C. and Psaradellis, I. (2021) Technical analysis profitability and persistence: a discrete false discovery approach on MSCI indices. Journal of International Financial Markets, Institutions and Money, 73, 101353. (doi: 10.1016/j.intfin.2021.101353)

2020

Hassanniakalager, A., Sermpinis, G. , Stasinakis, C. and Verousis, T. (2020) A conditional fuzzy inference approach in forecasting. European Journal of Operational Research, 283(1), pp. 196-216. (doi: 10.1016/j.ejor.2019.11.006)

2019

Da Silva Fernandes, F., Stasinakis, C. and Zekaite, Z. (2019) Forecasting government bond spreads with heuristic models: evidence from the Eurozone periphery. Annals of Operations Research, 282(1-2), pp. 87-118. (doi: 10.1007/s10479-018-2808-0)

Zhao, Y., Stasinakis, C. , Sermpinis, G. and Da Silva Fernandes, F. (2019) Revisiting Fama-French factors’ predictability with Bayesian modelling and copula-based portfolio optimization. International Journal of Finance and Economics, 24(42), pp. 1443-1463. (doi: 10.1002/ijfe.1742)

2018

Fernandes, F. D. S., Stasinakis, C. and Bardarova, V. (2018) Two-stage DEA-Truncated Regression: Application in banking efficiency and financial development. Expert Systems with Applications, 96, pp. 284-301. (doi: 10.1016/j.eswa.2017.12.010)

Zhao, Y., Stasinakis, C. , Sermpinis, G. and Shi, Y. (2018) Neural network copula portfolio optimization for exchange traded funds. Quantitative Finance, 18(5), pp. 761-775. (doi: 10.1080/14697688.2017.1414505)

2017

Sermpinis, G. , Stasinakis, C. and Hassanniakalager, A. (2017) Reverse adaptive krill herd locally weighted support vector regression for forecasting and trading exchange traded funds. European Journal of Operational Research, 263(2), pp. 540-558. (doi: 10.1016/j.ejor.2017.06.019)

Sermpinis, G. , Stasinakis, C. , Rosillo, R. and de la Fuente, D. (2017) European exchange trading funds trading with locally weighted support vector regression. European Journal of Operational Research, 258(1), pp. 372-384. (doi: 10.1016/j.ejor.2016.09.005)

2016

Stasinakis, C. , Sermpinis, G. , Psaradellis, I. and Verousis, T. (2016) Krill herd support vector regression and heterogeneous autoregressive leverage: evidence from forecasting and trading commodities. Quantitative Finance, 16(102), pp. 1901-1915. (doi: 10.1080/14697688.2016.1211800)

Stasinakis, C. , Sermpinis, G. , Theofilatos, K. and Karathanasopoulos, A. (2016) Forecasting US unemployment with radial basis neural networks, kalman filters and support vector regressions. Computational Economics, 47(4), pp. 569-587. (doi: 10.1007/s10614-014-9479-y)

Karathanasopoulos, A., Theofilatos, K. A., Sermpinis, G. , Dunis, C., Mitra, S. and Stasinakis, C. (2016) Stock market prediction using evolutionary support vector machines: an application to the ASE20 index. European Journal of Finance, 22(12), pp. 1145-1163. (doi: 10.1080/1351847X.2015.1040167)

2015

Sermpinis, G. , Stasinakis, C. , Theofilatos, K. and Karathanasopoulos, A. (2015) Modeling, forecasting and trading the EUR exchange rates with hybrid rolling genetic algorithms: support vector regression forecast combinations. European Journal of Operational Research, 247(3), pp. 831-846. (doi: 10.1016/j.ejor.2015.06.052)

2014

Sermpinis, G. , Stasinakis, C., Theofilatos, K. and Karathanasopoulos, A. (2014) Inflation and unemployment forecasting with genetic support vector regression. Journal of Forecasting, 33(6), pp. 471-487. (doi: 10.1002/for.2296)

Sermpinis, G. , Stasinakis, C. and Dunis, C. (2014) Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects. Journal of International Financial Markets, Institutions and Money, 30(1), pp. 21-54. (doi: 10.1016/j.intfin.2014.01.006)

Stasinakis, C. and Sermpinis, G. (2014) Financial forecasting and trading strategies: a survey. In: Dunis, C., Likothanassis, S., Karathanasopoulos, A., Sermpinis, G. and Theofilatos, K. (eds.) Computational Intelligence Techniques for Trading and Investment. Routledge: Abindgon, pp. 22-36. ISBN 9780415636803

2013

Sermpinis, G. , Stasinakis, C. and Karathanasopoulos, A. (2013) Kalman filter and SVR combinations in forecasting US unemployment. Artificial Intelligence Applications and Innovations, 412, pp. 506-515. (doi: 10.1007/978-3-642-41142-7_51)

2012

Sermpinis, G. , Dunis, C., Laws, J. and Stasinakis, C. (2012) Forecasting and trading the EUR/USD exchange rate with stochastic Neural Network combination and time-varying leverage. Decision Support Systems, 54(1), pp. 316-329. (doi: 10.1016/j.dss.2012.05.039)

Sermpinis, G. , Dunis, C., Laws, J. and Stasinakis, C. (2012) Kalman filters and neural networks in forecasting and trading. In: Jayne, C., Yue, S. and Iliadis, L. (eds.) Engineering Applications of Neural Networks, 13th International Conference EANN 2012 Proceedings, EANN 2012, CCIS 311. Series: Communications in Computer and Information Science (311). Springer Berlin Heidelberg: Berlin Heidelberg, pp. 433-442. ISBN 9783642329081 (doi: 10.1007/978-3-642-32909-8_44)

This list was generated on Wed Nov 20 21:28:39 2024 GMT.
Jump to: Articles | Book Sections
Number of items: 29.

Articles

Feng, X., von Mettenheim, H.-J., Sermpinis, G. and Stasinakis, C. (2024) Sustainable portfolio construction via machine learning: ESG, SDG, and sentiment. European Financial Management, (doi: 10.1111/eufm.12531) (Early Online Publication)

Wei, M., Kyriakou, I., Sermpinis, G. and Stasinakis, C. (2024) Cryptocurrencies and Lucky Factors: the value of technical and fundamental analysis. International Journal of Finance and Economics, 29(4), pp. 4073-4104. (doi: 10.1002/ijfe.2863)

Sun, X., Stasinakis, C. and Sermpinis, G. (2024) Decentralization illusion in decentralized finance: evidence from tokenized voting in MakerDAO polls. Journal of Financial Stability, 73, 101286. (doi: 10.1016/j.jfs.2024.101286)

Da Silva Fernandes, F., Sermpinis, G. , Stasinakis, C. and Zhao, Y. (2024) Corporate social responsibility and firm survival: evidence from Chinese listed firms. British Journal of Management, 35(2), pp. 1014-1039. (doi: 10.1111/1467-8551.12750)

Wei, M., Sermpinis, G. and Stasinakis, C. (2023) Forecasting and trading Bitcoin with machine learning techniques and a hybrid volatility/sentiment leverage. Journal of Forecasting, 42(4), pp. 852-871. (doi: 10.1002/for.2922)

Nguyen, D. K., Sermpinis, G. and Stasinakis, C. (2023) Big data, artificial intelligence, and machine learning: a transformative symbiosis in favour of financial technology. European Financial Management, 29(2), pp. 517-548. (doi: 10.1111/eufm.12365)

Shi, Y. , Stasinakis, C. , Xu, Y., Yan, C. and Zhang, X. (2022) Stock price default boundary: A Black-Cox model approach. International Review of Financial Analysis, 83, 102284. (doi: 10.1016/j.irfa.2022.102284)

Andreev, B., Sermpinis, G. and Stasinakis, C. (2022) Modelling financial markets during times of extreme volatility: evidence from the GameStop short squeeze. Forecasting, 4(3), pp. 654-673. (doi: 10.3390/forecast4030035)

Shi, Y. , Stasinakis, C. , Xu, Y. and Yan, C. (2022) Market co-movement between credit default swap curves and option volatility surfaces. International Review of Financial Analysis, 82, 102192. (doi: 10.1016/j.irfa.2022.102192)

Li, Y., Stasinakis, C. and Yeo, W. M. (2022) A hybrid XGBoost-MLP model for credit risk assessment on Digital Supply Chain Finance. Forecasting, 4(1), pp. 184-207. (doi: 10.3390/forecast4010011)

Hassanniakalager, A., Sermpinis, G. and Stasinakis, C. (2021) Trading the foreign exchange market with technical analysis and Bayesian statistics. Journal of Empirical Finance, 63, pp. 230-251. (doi: 10.1016/j.jempfin.2021.07.006)

Sermpinis, G. , Hassanniakalager, A., Stasinakis, C. and Psaradellis, I. (2021) Technical analysis profitability and persistence: a discrete false discovery approach on MSCI indices. Journal of International Financial Markets, Institutions and Money, 73, 101353. (doi: 10.1016/j.intfin.2021.101353)

Hassanniakalager, A., Sermpinis, G. , Stasinakis, C. and Verousis, T. (2020) A conditional fuzzy inference approach in forecasting. European Journal of Operational Research, 283(1), pp. 196-216. (doi: 10.1016/j.ejor.2019.11.006)

Da Silva Fernandes, F., Stasinakis, C. and Zekaite, Z. (2019) Forecasting government bond spreads with heuristic models: evidence from the Eurozone periphery. Annals of Operations Research, 282(1-2), pp. 87-118. (doi: 10.1007/s10479-018-2808-0)

Zhao, Y., Stasinakis, C. , Sermpinis, G. and Da Silva Fernandes, F. (2019) Revisiting Fama-French factors’ predictability with Bayesian modelling and copula-based portfolio optimization. International Journal of Finance and Economics, 24(42), pp. 1443-1463. (doi: 10.1002/ijfe.1742)

Fernandes, F. D. S., Stasinakis, C. and Bardarova, V. (2018) Two-stage DEA-Truncated Regression: Application in banking efficiency and financial development. Expert Systems with Applications, 96, pp. 284-301. (doi: 10.1016/j.eswa.2017.12.010)

Zhao, Y., Stasinakis, C. , Sermpinis, G. and Shi, Y. (2018) Neural network copula portfolio optimization for exchange traded funds. Quantitative Finance, 18(5), pp. 761-775. (doi: 10.1080/14697688.2017.1414505)

Sermpinis, G. , Stasinakis, C. and Hassanniakalager, A. (2017) Reverse adaptive krill herd locally weighted support vector regression for forecasting and trading exchange traded funds. European Journal of Operational Research, 263(2), pp. 540-558. (doi: 10.1016/j.ejor.2017.06.019)

Sermpinis, G. , Stasinakis, C. , Rosillo, R. and de la Fuente, D. (2017) European exchange trading funds trading with locally weighted support vector regression. European Journal of Operational Research, 258(1), pp. 372-384. (doi: 10.1016/j.ejor.2016.09.005)

Stasinakis, C. , Sermpinis, G. , Psaradellis, I. and Verousis, T. (2016) Krill herd support vector regression and heterogeneous autoregressive leverage: evidence from forecasting and trading commodities. Quantitative Finance, 16(102), pp. 1901-1915. (doi: 10.1080/14697688.2016.1211800)

Stasinakis, C. , Sermpinis, G. , Theofilatos, K. and Karathanasopoulos, A. (2016) Forecasting US unemployment with radial basis neural networks, kalman filters and support vector regressions. Computational Economics, 47(4), pp. 569-587. (doi: 10.1007/s10614-014-9479-y)

Karathanasopoulos, A., Theofilatos, K. A., Sermpinis, G. , Dunis, C., Mitra, S. and Stasinakis, C. (2016) Stock market prediction using evolutionary support vector machines: an application to the ASE20 index. European Journal of Finance, 22(12), pp. 1145-1163. (doi: 10.1080/1351847X.2015.1040167)

Sermpinis, G. , Stasinakis, C. , Theofilatos, K. and Karathanasopoulos, A. (2015) Modeling, forecasting and trading the EUR exchange rates with hybrid rolling genetic algorithms: support vector regression forecast combinations. European Journal of Operational Research, 247(3), pp. 831-846. (doi: 10.1016/j.ejor.2015.06.052)

Sermpinis, G. , Stasinakis, C., Theofilatos, K. and Karathanasopoulos, A. (2014) Inflation and unemployment forecasting with genetic support vector regression. Journal of Forecasting, 33(6), pp. 471-487. (doi: 10.1002/for.2296)

Sermpinis, G. , Stasinakis, C. and Dunis, C. (2014) Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects. Journal of International Financial Markets, Institutions and Money, 30(1), pp. 21-54. (doi: 10.1016/j.intfin.2014.01.006)

Sermpinis, G. , Stasinakis, C. and Karathanasopoulos, A. (2013) Kalman filter and SVR combinations in forecasting US unemployment. Artificial Intelligence Applications and Innovations, 412, pp. 506-515. (doi: 10.1007/978-3-642-41142-7_51)

Sermpinis, G. , Dunis, C., Laws, J. and Stasinakis, C. (2012) Forecasting and trading the EUR/USD exchange rate with stochastic Neural Network combination and time-varying leverage. Decision Support Systems, 54(1), pp. 316-329. (doi: 10.1016/j.dss.2012.05.039)

Book Sections

Stasinakis, C. and Sermpinis, G. (2014) Financial forecasting and trading strategies: a survey. In: Dunis, C., Likothanassis, S., Karathanasopoulos, A., Sermpinis, G. and Theofilatos, K. (eds.) Computational Intelligence Techniques for Trading and Investment. Routledge: Abindgon, pp. 22-36. ISBN 9780415636803

Sermpinis, G. , Dunis, C., Laws, J. and Stasinakis, C. (2012) Kalman filters and neural networks in forecasting and trading. In: Jayne, C., Yue, S. and Iliadis, L. (eds.) Engineering Applications of Neural Networks, 13th International Conference EANN 2012 Proceedings, EANN 2012, CCIS 311. Series: Communications in Computer and Information Science (311). Springer Berlin Heidelberg: Berlin Heidelberg, pp. 433-442. ISBN 9783642329081 (doi: 10.1007/978-3-642-32909-8_44)

This list was generated on Wed Nov 20 21:28:39 2024 GMT.

Supervision

Charalampos is interested in supervising students in the above mentioned areas of research.

Current doctoral supervision

  • Arora, Manish
    Deep Learning Calibration Framework for detecting Asset Price Bubbles from Option Prices.
  • Feng, Xin
    ESG investment with machine learning
  • Li, Yaohua
    Three essays on financial analysts
  • Liu, Chen
    Manager characteristics and narrative disclosure quality
  • Syzdykov, Abylay
    The role of key stakeholders of Fintech ecosystem.
  • WANG, RUBING
    The Study of FinTech and Shadow Banking Based on the Micro Perspective

Teaching

Current courses

  • Advances of Machine Learning in Finance (PG)
  • Foundations of Financial Technology (PG)

Previously taught courses

  • Artificial Intelligence in Finance (PG)
  • Contemporary business issues (PG)
  • Corporate finance (PG)
  • International financial management (PG)
  • International investment management (PG)
  • Issues in accounting research (PG)
  • Management accounting (UG)
  • Quantitative economic applications (UG)
  • Statistical analysis and methods (UG)
  • Strategic management accounting (UG)

Additional information

  • Fellow of Higher Education Academy
  • Guest Editor: Annals of Operations Research, Forecasting Journal
  • External Examiner: Cass Business School (BSc Investment & Financial Risk Management)
  • Member of the Operational Research Society, Forecasting Financial Markets Association
  • Advisor of studies, Assessment Officer

Personal website: Dr Charalampos Stasinakis


Profile photo of Dr Charalampos Stasinakis, Lecturer in Accounting and Finance