Li, D., Li, Y., Stasinakis, C. and Zhao, Y., 2026. Diversifying Environmental, Social and Governance Portfolios: Evidence From China. International Journal of Finance & Economics (forthcoming).
Li, Y., Stasinakis, C., Yeo, W.M. and Fernandes, F.D.S., 2025. FinTech, financial development and banking efficiency: Evidence from Chinese commercial banks. European Journal of Finance, 31 (10), pp. 1-51.
Feng, X., von Mettenheim, H.J., Sermpinis, G. and Stasinakis, C., 2025. Sustainable portfolio construction via machine learning: ESG, SDG, and sentiment. European Financial Management, 31 (3), pp. 1148-1169.
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.
Fernandes, F.D.S., 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.
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 & Economics, 29(4), pp. 4073-4104.
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.
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.
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.
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, p.102284.
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, p.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.
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.
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.
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, p.101353.
Zhao, Y., Stasinakis, C., Sermpinis, G. and Fernandes, F.D.S. (2019). Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization. International Journal of Finance & Economics, 24 (4), 1443-1463.
Fernandes, F.D.S., Stasinakis, C. and Zekaite, Z. (2018). Forecasting government bond spreads with heuristic models: evidence from the Eurozone periphery. Annals of Operations Research, 1-32.
Fernandes, F.D.S., Stasinakis, C., & Bardarova, V. (2018). Two-stage DEA-Truncated Regression: Application in banking efficiency and financial development. Expert Systems with Applications, 96, 284-301.
Zhao, Y., Stasinakis, C., Sermpinis, G. and Shi, Y. (2018). Neural network copula portfolio optimization for exchange traded funds. Quantitative Finance, 18(5), 761-775.
Sermpinis, G., Stasinakis, C. and Hassanniakalager, A. (2017) Reverse Adaptive Krill Herd: Application with Locally Weighted Support Vector Regression for forecasting and trading Exchange Traded Funds. European Journal of Operational Research, 263 (2), 540-558.
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), 372-384.
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), 1901-1915.
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), 569-587.
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),1-846.
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), 1145-1163.
Sermpinis, G., Stasinakis, C., Theofilatos, K., and Karathanasopoulos, A. (2014) Inflation and unemployment forecasting with genetic support vector regression. Journal of Forecasting, 33(6), 471-487.
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, 22-36. ISBN 9780415636803
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), 21-54.
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), 316-329.
Wards grant (£3,000) - Organization of Finance and Business Analytics International Conference (x2)
Scottish Technology Ecosystem Review Fund (£5,000) – FinTech, Scottish Technology Sector and Higher Education
Wards grant (£3,000) – Organization of practitioners’ and academics’ workshop on Machine Learning and Financial Technology.
Wards grant (£2,955) - Basel III and Capital Market Union Plan: Evidence from banking performance and managerial sentiment
LKAS Collaborative Scholarships (£12,000) – Research project on Magnetomyography (MMG) Sensors
Grant (1950 euros) - workshop on Advances in Computational Finance, University of La Laguna, Tenerife
Erasmus teaching mobility grant (2,000 euros) promoting research led teaching in Leibniz University of Hannover, Germany- ‘International Investment Management: Computational Intelligent Techniques in Financial Forecasting Applications’