Publications
Journal articles, conference papers, book chapters and theses on machine learning and evolutionary computation for finance, business and the public sector.
96 publications, newest first. Download all as BibTeX
2026
Christodoulaki, E., Kampouridis, M. (2026). Strongly-typed genetic programming with an active trading operator for algorithmic trading using fundamental, sentiment, and technical analysis. Applied Soft Computing, Elsevier.
Barnor, N., Kampouridis, M., Kanellopoulos, P. (2026). Machine Learning for Temperature Forecasting in Weather Derivatives. Artificial Intelligence Review, Springer.
Salman, O., Melissourgos, T., Kampouridis, M. (2026). A genetic algorithm for the optimization of multi-threshold trading strategies in the directional changes paradigm. Artificial Intelligence Review, Vol 59:2, Springer.
Kolluri, G.P.K.B., Kampouridis, M., Shekhar, R. (2026). On the Role of Encoder Depth: Pruning Whisper and LoRA Fine-Tuning in SLAM-ASR. SPEAKABLE workshop at LREC 2026.
Kolluri, G.P.K.B., Zhang, Y., Kampouridis, M., Shekhar, R. (2026). CARD: Cross-component Audio Representation Distillation for Encoder-Free Audio Captioning. IEEE Spoken Language Technology SLT 2026.
2025
Long, X., Kampouridis, M., Papastylianou, T. (2025). Multi-Objective Genetic Programming-based Algorithmic Trading, using Directional Changes and a Modified Sharpe Ratio Score for Identifying Optimal Trading Strategies. Artificial Intelligence Review, Springer.
Long, X., Kampouridis, M., Kanellopoulos, P. (2025). An In-Depth Investigation of Genetic Programming Under Physical Time and Directional Change Frameworks for Algorithmic Trading. IEEE Access.
Christodoulaki, E., Kampouridis, M., Kyropoulou, M. (2025). A novel strongly-typed Genetic Programming algorithm for combining sentiment and technical analysis for algorithmic trading. Knowledge-Based Systems 311, 113054, Elsevier.
Habbab, F.Z., Kampouridis, M., Papastylianou, T. (2025). Improving Real Estate Investment Trusts (REITs) Time-Series Prediction Accuracy Using Machine Learning and Technical Analysis Indicators. Artificial Intelligence Review, Springer. Volume 58:70.
Rayment, G. (2025). Deep reinforcement learning for trading strategy development on high-frequency currency data using directional changes sampling. PhD Thesis, University of Essex.
Evdokimov, I. (2025). Innovations to fundamental stock valuations: Estimating future earnings per share and free cash flows using statistical and machine learning methods. PhD Thesis, University of Essex.
Long, X. (2025). Financial forecasting with the combination of Physical and Event-based time using Genetic Programming. PhD Thesis, University of Essex.
2024
Gonzalez-Nunez, E., Trejo, L. A., Kampouridis, M. (2024). Expanding a Machine Learning Class Towards its Application to the Stock Market Forecast. Applied Intelligence, Springer.
Gonzalez Nunez, E., Trejo, L. A., Kampouridis, M. (2024). A Comparative Study for Stock Market Forecast Based on a New Machine Learning Model. Big Data and Cognitive Computing, MDPI.
Habbab, F.Z., Kampouridis, M. (2024). An in-depth investigation of five machine learning algorithms for optimizing mixed-asset portfolios including REITs. Expert Systems with Applications, Volume 235, 121102 Elsevier.
Sapkota, M.S., Doctor, F., Herrera, H., Kampouridis, M., Yang, X. (2024). Machine Learning to Predict Surgery Duration: Towards Implementing AI and Digital Twin for Effective Scheduling. IEEE International Conference on Medical Artificial Intelligence (MedAI).
Rayment, G., Kampouridis, M. (2024). Enhancing High-Frequency Trading with Deep Reinforcement Learning using Advanced Positional Awareness Under a Directional Changes Paradigm. International Conference on Machine Learning and Applications.
Long, X., Kampouridis, M. (2024). Alpha-dominance two-objective Optimization Genetic Programming for Algorithmic Trading under a Directional Changes Environment. IEEE Symposium on Computational Intelligence for Financial Engineering & Risk (CIFEr).
Salman, O. (2024). Trading Strategies Optimization Using a Genetic Algorithm under The Directional Changes Paradigm. PhD Thesis, University of Essex.
Habbab, F. Z. (2024). Machine Learning to Investigate the Role of Real Estate in a Mixed-Asset Portfolio. PhD Thesis, University of Essex.
Christodoulaki, E.P. (2024). Fundamental, Sentiment and Technical analysis for Algorithmic Trading using Novel Genetic Programming algorithms. PhD Thesis, University of Essex.
2023
Evdokimov, I., Kampouridis, M., Papastylianou, T. (2023). Application Of Machine Learning Algorithms to Free Cash Flows Growth Rate Estimation. International Neural Network Society Workshop on Deep Learning Innovations and Applications (INNS DLIA), Procedia Computer Science, Elsevier (2023).
Habbab, F., Kampouridis, M. (2023). Optimising a Prediction-based, Mixed-asset portfolio including REITs. IEEE Symposium on Computational Intelligence for Financial Engineering & Risk (CIFEr).
Rayment, G., Kampouridis, M., Adegboye, A. (2023). Predicting Directional Change Reversal Points with Machine Learning Regression Models. IEEE Symposium on Computational Intelligence for Financial Engineering & Risk (CIFEr).
Rayment, G., Kampouridis, M. (2023). High Frequency Trading with Deep Reinforcement Learning Agents Under a Directional Changes Sampling Framework. IEEE Symposium on Computational Intelligence for Financial Engineering & Risk (CIFEr).
Christodoulaki, E., Kampouridis, M. (2023). Fundamental, Technical and Sentiment Analysis for Algorithmic Trading with Genetic Programming. IEEE Symposium on Computational Intelligence for Financial Engineering & Risk (CIFEr).
Salman, O., Melissourgos, T., Kampouridis, M. (2023). Optimization of Trading Strategies using a Genetic Algorithm under the Directional Changes Paradigm with Multiple Thresholds. IEEE Congress on Evolutionary Computation (CEC).
Long, X., Kampouridis, M., Kanellopoulos, P. (2023). Multi-objective optimisation and genetic programming for trading by combining directional changes and technical indicators. IEEE Congress on Evolutionary Computation (CEC).
Habbab, F.Z., Kampouridis, M., Papastylianou, T. (2023). Improving REITs Time Series Prediction Using ML and Technical Analysis Indicators. IEEE International Joint Conference on Neural Networks (IJCNN), Queensland, Australia.
Christodoulaki, E., Kampouridis, M., Kyropoulou, M. (2023). Enhanced Strongly typed Genetic Programming for Algorithmic Trading. Genetic and Evolutionary Computation Conference (GECCO), Lisbon, Portugal.
2022
Adegboye, A., Kampouridis, M., Otero, F. (2022). Algorithmic trading with directional changes. Artificial Intelligence Review, Springer (2022).
Kampouridis, M., Kanellopoulos, P., Kyropoulou, M., Melissourgos, T., Voudouris, A.A. (2022). Multi-Agent Systems for Computational Economics and Finance. AI Communications, IOS Press (2022).
Christodoulaki, E., Kampouridis, M. (2022). Combining Technical and Sentiment Analysis under a Genetic Programming algorithm. The 21st UK Workshop on Computational Intelligence (UKCI).
Habbab, F.Z., Kampouridis, M. (2022). Machine Learning for Real Estate Time Series Prediction. The 21st UK Workshop on Computational Intelligence (UKCI).
Long, X., Kampouridis, M., Kanellopoulos, P. (2022). Genetic programming for combining directional changes indicators in international stock markets. In: Rudolph, G., Kononova, A.V., Aguirre, H., Kerschke, P., Ochoa, G., Tušar, T. (eds) Parallel Problem Solving from Nature – PPSN XVII. PPSN 2022. Lecture Notes in Computer Science, vol 13399. Springer.
Habbab, F.Z., Kampouridis, M. (2022). Optimizing Mixed-Asset Portfolio With Real Estate: Why Price Predictions? IEEE Congress on Evolutionary Computation (CEC).
Salman, O., Kampouridis, M., Jarchi, D. (2022). Trading Strategies Optimization by Genetic Algorithm under the Directional Changes Paradigm. IEEE Congress on Evolutionary Computation (CEC).
Long, X., Kampouridis, M., Jarchi, D. (2022). An in-depth investigation of genetic programming and nine other machine learning algorithms in a financial forecasting problem. IEEE Congress on Evolutionary Computation (CEC).
Christodoulaki, E., Kampouridis, M. (2022). Using strongly typed genetic programming to combine technical and sentiment analysis for algorithmic trading. IEEE Congress on Evolutionary Computation (CEC).
Christodoulaki, E., Kampouridis, M., Kanellopoulos, P. (2022). Technical and Sentiment Analysis in Financial Forecasting with Genetic Programming. IEEE Symposium on Computational Intelligence for Financial Engineering & Economics (CIFEr).
Habbab, F., Kampouridis, M., Voudouris, A. (2022). Optimizing Mixed-Asset Portfolios Involving REITs. IEEE Symposium on Computational Intelligence for Financial Engineering & Risk (CIFEr).
Adegboye, A. (2022). Estimating Directional Changes Trend Reversal in Forex Using Machine Learning. PhD Thesis, University of Kent.
2021
Adegboye, A., Kampouridis, M., Otero, F. (2021). Improving trend reversal estimation in Forex markets under a directional changes paradigm with classification algorithms. International Journal of Intelligent Systems, Wiley (2021).
Adegboye, A., Kampouridis, M. (2021). Machine Learning Classification and Regression Models for Predicting Directional Changes Trend Reversal in FX Markets. Expert Systems with Applications, Vol. 173, Elsevier, pp. 114645.
2020
Brabazon, A., Kampouridis, M., O'Neill, M. (2020). Applications of Genetic Programming to Finance and Economics: Past, Present, Future. Genetic Programming and Evolvable Machines (Invited Article), Vol. 21, Springer, pp. 33-53.
2019
Cramer, S., Kampouridis, M., Freitas, A.A., Alexandridis, A. (2019). Stochastic Model Genetic Programming: Deriving Pricing Equations for Rainfall Weather Derivatives. Swarm and Evolutionary Computation (46), Elsevier, pp. 184-200.
2018
Cramer, S., Kampouridis, M., Freitas, A.A. (2018). Decomposition Genetic Programming: An Extensive Evaluation on Rainfall Prediction in the Context of Weather Derivatives. Applied Soft Computing, Elsevier, Vol. 70C, pp. 208-224.
2017
Cramer, S., Kampouridis, M., Freitas, A.A., Alexandridis, A. (2017). An Extensive Evaluation of Seven Machine Learning Methods for Rainfall Prediction in Weather Derivatives. Expert Systems with Applications, Elsevier, Vol. 85, pp. 169-181.
Kampouridis, M., Otero, F.E.B. (2017). Evolving Trading Strategies Using Directional Changes. Expert Systems with Applications, Elsevier, Vol. 73, pp. 145-160.
Alexandridis, A., Kampouridis, M., Cramer, S. (2017). A Comparison between Wavelet Networks and Genetic Programming in the Context of Temperature Derivatives. International Journal of Forecasting, Elsevier, Vol. 33 (1), pp. 21-47.
Kampouridis, M., Otero, F. E. B. (2017). Heuristic procedures for improving the predictability of a genetic programming financial forecasting algorithm. Soft Computing, Springer, Vol. 21 (2), pp. 295-310.
Adegboye, A. N., Kampouridis, M., Johnson, C. G. (2017). Regression Genetic Programming for Predicting Trend End in Foreign Exchange Market. IEEE Computational Intelligence for Financial Engineering & Economics, Symposium Series on Computational Intelligence, Hawaii, USA.
Kampouridis, M., Adegboye, A. N., Johnson, C. G. (2017). Evolving Directional Based Trading Strategies with a New Event-based Indicator. in Yuhui, Shi et al. (Eds.): Proceedings of SEAL 2017, Lecture Notes in Computer Science (LNCS) 10593.
Cramer, S., Kampouridis, M., Freitas, A.A., Alexandridis, A. (2017). Pricing Rainfall Based Futures Using Genetic Programming. EvoApplications 2017, Lecture Notes in Computer Science (LNCS) 10199, pp. 17-33.
Cramer, S. (2017). New Genetic Programming Methods for Rainfall Prediction and Rainfall Derivatives Pricing. PhD Thesis, University of Kent.
2016
Vastardis, N., Kampouridis, M., Yang, K. (2016). A user behaviour-driven smart-home gateway for energy management. Journal of Ambient Intelligence and Smart Environments, IOS Press, Vol. 8 (6), pp. 583-602.
Cramer, S., Kampouridis, M., Freitas, A.A. (2016). A Genetic Decomposition Algorithm for Predicting Rainfall within Financial Weather Derivatives. Genetic and Evolutionary Computation Conference (GECCO), Denver, Colorado, USA.
Cramer, S., Kampouridis, M., Freitas, A.A. (2016). Feature Engineering for Improving Financial Derivatives-based Rainfall Prediction. IEEE World Congress on Computational Intelligence, Vancouver, Canada.
2015
Cramer, S., Kampouridis, M., Freitas, A.A., Alexandridis, A. (2015). Predicting Rainfall in the Context of Rainfall Derivatives Using Genetic Programming. IEEE Computational Intelligence for Financial Engineering & Economics, Symposium Series on Computational Intelligence, Cape Town, South Africa.
Cramer, S., Kampouridis, M. (2015). Guided Local Search for the Intelligent Deployment of Fibre Optic Networks. IEEE Congress on Evolutionary Computation, Sendai, Japan.
Gypteau, J., Otero, F., Kampouridis, M. (2015). Generating Directional Change Based Trading Strategies with Genetic Programming. A.M. Mora and G.Squillero (Eds.): EvoApplications 2015, Lecture Notes in Computer Science (LNCS) 9028, Chapter 22, pp. 1-12.
2014
Brookhouse, J., Otero, F., Kampouridis, M. (2014). Working with OpenCL to Speed Up a Genetic Programming Financial Forecasting Algorithm: Initial Results. EvoSoft, GECCO, Vancouver, Canada.
Kattan, A., Kampouridis, M., Ong, Y.-S., Mehamdi, K. (2014). Transformation of Input Space using Statistical Moments: EA-Based Approach. IEEE World Congress on Evolutionary Computation (WCCI), Beijing, China.
Kattan, A., Kampouridis, M., Agapitos, A. (2014). Generalisation Enhancement via Input Space Transformation: A GP Approach. EuroGP, EvoStar, Granada, Spain.
Otero, F., Kampouridis, M. (2014). A Comparative Study on the Use of Classification Algorithms in Financial Forecasting. EvoFin, EvoStar, Granada, Spain.
Shao, M., Smonou, D., Kampouridis, M., Tsang, E. (2014). Guided Fast Local Search for Speeding Up a Financial Forecasting Algorithm. IEEE Computational Intelligence for Financial Engineering & Economics (CIFEr), London, UK.
Aluko, B., Smonou, D., Kampouridis, M., Tsang, E. (2014). Combining Different Meta-heuristics to Improve the Predictability of a Financial Forecasting Algorithm. IEEE Computational Intelligence for Financial Engineering & Economics (CIFEr), London, UK.
2013
Kampouridis, M., Alsheddy, A., Tsang, E. (2013). On the investigation of hyper-heuristics on a financial forecasting problem. Annals of Mathematics and Artificial Intelligence, Springer, Vol. 68 (4), pp. 225-246.
Kampouridis, M., Otero, F. (2013). Using attribute construction to improve the predictability of a GP financial forecasting algorithm. Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, Taipei, Taiwan.
Alexandridis, A., Kampouridis, M. (2013). Temperature Forecasting in the Concept of Weather Derivatives: A Comparison between Wavelet Networks and Genetic Programming. in L. Iliadis, H. Papadopoulos, and C. Jayne (Eds.): Engineering Applications of Neural Networks (EANN) 2013, Part I, Communications in Computer and Information Science (CCIS) 383, pp. 12--21, Springer, Heidelberg.
Kampouridis, M. (2013). An Initial Investigation of Choice Function Hyper-Heuristics for the Problem of Financial Forecasting. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Cancun, Mexico.
Smonou, D., Kampouridis, M., Tsang, E. (2013). Metaheuristics Application on a Financial Forecasting Problem. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Cancun, Mexico.
Kampouridis, M., Sim, K.M. (2013). A GP approach for Price-Speed Optimizing Negotiation. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Cancun, Mexico.
Rais Shaghaghi, A., Glover, T., Kampouridis, M., Tsang, E. (2013). Guided Local Search for Optimal GPON/FTTP Network Design. In Chaki, N., Meghanathan, N., Nagamalai, D. (Eds.): Proceedings of the Fourth International Conference on Networks & Communications, Lecture Notes in Electrical Engineering, Vol. 131, Springer.
Kampouridis, M. (2013). An application of Genetic Programming to Financial Forecasting. IEEE Congress on Evolutionary Computation (CEC), Cancun, Mexico.
My research on EDDIE is featured in the following article: Cox, A. (2013). Sex, death and the quest for algorithmic glory. Automated Trader magazine, Issue 28 Q2.
2012
Kampouridis, M., Tsang, E. (2012). Investment Opportunities Forecasting: Extending the Grammar of a GP-based Tool. International Journal of Computational Intelligence Systems, Vol. 5 (3), pp. 530-541.
Kampouridis, M., Chen, S.-H., Tsang, E. (2012). Microstructure Dynamics and Agent-Based Financial Markets: Can Dinosaurs Return? Advances in Complex Systems, Vol. 15, No. 5.
Alsheddy, A., Kampouridis, M. (2012). Off-line Parameter Tuning for Guided Local Search Using Genetic Programming. Proceedings of the IEEE World Congress on Computational Intelligence (WCCI) 2012, Brisbane, Australia.
Kampouridis, M., Glover, T., Rais Shaghaghi, A., Tsang, E. (2012). Using a Genetic Algorithm as a Decision Support Tool for the Deployment of Fiber Optic Networks. Proceedings of the IEEE World Congress on Computational Intelligence (WCCI) 2012, Brisbane, Australia.
2011
Kampouridis, M., Chen, S.-H., Tsang, E. (2011). Market Fraction Hypothesis: A Proposed Test. International Review of Financial Analysis, Vol. 23, pp. 41-54.
Kampouridis, M., Chen, S.-H., Tsang, E. (2011). Investigating the Effect of Different GP Algorithms on the Non-Stationary Behavior of Financial Markets. IEEE Symposium on Computational Intelligence for Financial Engineering & Economics, 11-15 April 2011, Paris, France.
Kampouridis, M., Chen, S.-H., Tsang, E. (2011). Market Microstructure: Can Dinosaurs Return? A Self-Organizing Map Approach under an Evolutionary Framework. in C. Di Chio et al. (Eds.): EvoApplications 2011, Part II, LNCS 6625, pp. 91--100. Springer, Heidelberg.
Kampouridis, M., Tsang, E. (2011). Using Hyperheuristics under a GP framework for Financial Forecasting. C.A. Coello Coello (Ed.): LION 5, LNCS 6683, pp. 16--30. Springer, Heidelberg.
Kampouridis, M., Chen, S.-H., Tsang, E. (2011). Market Microstructure: A Self-Organizing Map Approach to Investigate Behavior Dynamics Under an Evolutionary Environment. in Natural Computing in Computational Finance, Volume 4, Studies in Computational Intelligence Series, Springer.
Kampouridis, M., Chen, S.-H., Tsang, E. (2011). The Market Fraction Hypothesis under different GP algorithms. Information Systems for Global Financial Markets: Emerging Developments and Effects, IGI Global, 2011, pp. 37-54. (earlier version available as a technical report ).
Kampouridis, M. (2011). Computational Intelligence in Financial Forecasting and Agent-Based Modeling: Applications of Genetic Programming and Self-Organizing Maps. PhD Thesis, University of Essex.
2010
Kampouridis, M., Tsang, E. (2010). EDDIE for Investment Opportunities Forecasting: Extending the Search Space of the GP. Proceedings of the IEEE Congress on Evolutionary Computation, Barcelona, Spain, 18-23 July 2010, p. 2019-2026.
Kampouridis, M., Chen, S.-H., Tsang, E. (2010). Testing the Dinosaur Hypothesis under Empirical Datasets. In R. Schaefer et al. (Eds.): PPSN XI, Part II, LNCS 6239, pp. 199--208. Springer, Heidelberg.
Chen, S.-H., Kampouridis, M., Tsang, E. (2010). Microstructure Dynamics and Agent-Based Financial Markets. in Tibor Bosse, Armando Geller, Catholijn M. Jonker (eds.), Proceedings on Eleventh International Workshop on Multi-Agent-Based Simulation (MABS’2010), Toronto, Canada, pp. 117-128.
Kampouridis, M., Chen, S.-H., Tsang, E. (2010). Testing the Dinosaur Hypothesis Under Different GP Algorithms. Proceedings of the UK Computational Intelligence (UKCI) Workshop, Essex, IEEE Xplore.
Kampouridis, M., Chen, S.-H., Tsang, E. (2010). The Market Fraction Hypothesis: A proposed test. Econophysics Colloquium 2010, Taipei, Taiwan.
2009
Kampouridis, M., Chen, S.-H., Tsang, E. (2009). Market fraction hypothesis: A proposed test. Proceedings of the 9th Asia-Pacific Complex Systems Conference, Tokyo.
Kampouridis, M., Chen, S.-H., Tsang, E. (2009). Market fraction hypothesis: A proposed test. The 6th International Conference on Computational Management Science, Geneva.
2008
Kampouridis, M., Tsang, E. (2008). Hyper-Heuristics for Investment Opportunities Forecasting. The 5th International Conference on Computational Management Science, London.
2006
Kampouridis, M. (2006). An Intelligent Tutoring System for Java. MSc Thesis, University of Essex.