1. 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, (forthcoming).

  2. Stasinakis, C. and Sermpinis, G., 2020. Big Data, Artificial Intelligence and Machine Learning: A Transformative Symbiosis in Favour of Financial Technology – Working paper (available at SSRN)

  3. 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. 

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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. 

  12. 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. 

  13. 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. 

  14. 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.

  15. ​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

  16. 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. 

  17. 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.

*Updated in May 2021

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