Dr Michael Kampouridis
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Email
mkampo@essex.ac.uk -
Location
1NW.3.17, Colchester Campus
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Academic support hours
Please email me first to arrange a meeting.
Profile
Biography
I hold a PhD in Computer Science, which I obtained from the School of Computer Science and Electronic Engineering, University of Essex. I also hold an MSc in Computer Studies, also from the University of Essex, and a BSc in Economic Sciences, from the Department of Economic Sciences from the University of Athens, Greece. Prior appointments before coming to Essex include a lectureship at the School of Computing at the University of Kent, and research visits to AI-Econ Center, Department of Economics, at National Cheng Chi University of Taiwan. My research focuses on the use of Machine Learning to Business applications, particularly to Finance and Economics. I am particularly interested in evolutionary algorithms and financial forecasting. My students have done research on different financial areas such as algorithmic trading, directional changes, volatility forecasting, future cash flow growth, sentiment analysis for the stock market, real estate investment trusts, temperature and rainfall weather derivatives. If you are interested in joining my team as a PhD student in the above or any similar areas, feel free to contact me. I am also heavily involved on a number of industrial projects (see Grants and Funding section below), as well as projects from public sector organisations, such as the East Suffolk and North Essex NHS Foundation Trust (ESNEFT) and the General Lighthouse Authorities of the UK and Ireland. Outside the University of Essex, I am a senior member of the IEEE, a member of the IEEE Computational Intelligence Society, and a Fellow of the Higher Education Academy. I was also the Chair of the IEEE Computational Finance and Economics Technical Committee for 2020 and 2021.
Qualifications
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Postgraduate Certificate in Higher Education University of Kent, (2012)
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PhD Computer Science University of Essex, (2011)
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MSc in Computer Studies University of Essex, (2006)
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BSc in Economics National and Kapodistrian University of Athens, (2005)
Appointments
University of Essex
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Faculty Dean (Postgraduate), Science and Health, University of Essex (1/8/2024 - present)
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Director, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex (1/9/2023 - 31/7/2024)
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Deputy Director of Education, School of Computer Science and Electronic Engineering, University of Essex (1/9/2023 - 31/7/2024)
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Reader, School of Computer Science and Electronic Engineering, University of Essex (1/10/2023 - present)
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Senior Lecturer, School of Computer Science and Electronic Engineering, University of Essex (1/10/2021 - 30/9/2023)
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Lecturer, School of Computer Science and Electronic Engineering, University of Essex (1/4/2020 - 30/9/2021)
Research and professional activities
Research interests
Applications of machine learning to finance
Financial forecasting & algorithmic trading
Weather derivatives
Evolutionary algorithms
Teaching and supervision
Current supervision
Previous supervision
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 3/10/2024
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 15/8/2024
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 3/7/2024
Publications
Publications (1)
Kampouridis, M., Kanellopoulos, P., Kyropoulou, M., Melissourgos, T. and Voudouris, AA., (2022). Multi-Agent Systems for Computational Economics and Finance
Journal articles (24)
Gonzalez-Nunez, E., Trejo, LA. and Kampouridis, M., Expanding a Machine Learning Class Towards its Application to the Stock Market Forecast. Applied Intelligence
Habbab, F., Kampouridis, M. and Papastylianou, T., Improving Real Estate Investment Trust (REITs) time-series prediction accuracy using Machine Learning and Technical Analysis indicators. Artificial Intelligence Review
Habbab, FZ. and Kampouridis, M., (2024). An in-depth investigation of five machine learning algorithms for optimizing mixed-asset portfolios including REITs. Expert Systems with Applications. 235, 121102-121102
González-Núñez, E., Kampouridis, M. and Trejo, LA., (2024). A Comparative Study for Stock Market Forecast Based on a New Machine Learning Model. Big Data and Cognitive Computing. 8 (4), 34-34
Kampouridis, M., Evdokimov, I. and Papastylianou, T., (2023). Application Of Machine Learning Algorithms to Free Cash Flows Growth Rate Estimation. Procedia Computer Science. 222, 529-538
Kampouridis, M., Kanellopoulos, P., Kyropoulou, M., Melissourgos, T. and Voudouris, A., (2022). Multi-Agent Systems for Computational Economics and Finance. AI Communications: the European journal on artificial intelligence. 35 (4), 369-380
Adegboye, A., Kampouridis, M. and Otero, F., (2022). Algorithmic trading with directional changes. Artificial Intelligence Review. 56 (6), 5619-5644
Kampouridis, M., Kanellopoulos, P., Kyropoulou, M., Melissourgos, T. and Voudouris, AA., (2022). Multi-Agent Systems for Computational Economics and Finance.. CoRR. abs/2210.03540
Adegbgoye, A. and Kampouridis, M., (2021). Machine Learning Classification and Regression Models for Predicting Directional Changes Trend Reversal in FX Markets. Expert Systems with Applications. 173, 114645-114645
Adegboye, A., Kampouridis, M. and Otero, F., (2021). Improving trend reversal estimation in Forex markets under a directional changes paradigm with classification algorithms. International Journal of Intelligent Systems. 36 (12), 7609-7640
Brabazon, A., Kampouridis, M. and O’Neill, M., (2020). Applications of genetic programming to finance and economics: past, present, future. Genetic Programming and Evolvable Machines. 21 (1-2), 33-53
Cramer, S., Kampouridis, M., Freitas, AA. and Alexandridis, A., (2019). Stochastic model genetic programming: Deriving pricing equations for rainfall weather derivatives. Swarm and Evolutionary Computation. 46, 184-200
Cramer, S., Kampouridis, M. and Freitas, AA., (2018). Decomposition genetic programming: An extensive evaluation on rainfall prediction in the context of weather derivatives. Applied Soft Computing. 70, 208-224
Cramer, S., Kampouridis, M., Freitas, AA. and Alexandridis, AK., (2017). An extensive evaluation of seven machine learning methods for rainfall prediction in weather derivatives. Expert Systems with Applications. 85, 169-181
Alexandridis, AK., Kampouridis, M. and Cramer, S., (2017). A comparison of wavelet networks and genetic programming in the context of temperature derivatives. International Journal of Forecasting. 33 (1), 21-47
Kampouridis, M. and Otero, FEB., (2017). Heuristic procedures for improving the predictability of a genetic programming financial forecasting algorithm. Soft Computing. 21 (2), 295-310
Kampouridis, M. and Otero, FEB., (2017). Evolving trading strategies using directional changes. Expert Systems with Applications. 73, 145-160
Vastardis, N., Kampouridis, M. and Yang, K., (2016). A user behaviour-driven smart-home gateway for energy management. Journal of Ambient Intelligence and Smart Environments. 8 (6), 583-602
Brabazon, A. and Kampouridis, M., (2016). Foreword: special issue on computational finance and economics. Evolutionary Intelligence. 9 (4), 111-112
Kim, Y-H., Kattan, A., Kampouridis, M. and Yoon, Y., (2016). Discrete Dynamics in Evolutionary Computation and Its Applications. Discrete Dynamics in Nature and Society. 2016, 1-2
Kampouridis, M., Alsheddy, A. and Tsang, E., (2013). On the investigation of hyper-heuristics on a financial forecasting problem. Annals of Mathematics and Artificial Intelligence. 68 (4), 225-246
Kampouridis, M. and Tsang, E., (2012). Investment Opportunities Forecasting: Extending the Grammar of a GP-based Tool. International Journal of Computational Intelligence Systems. 5 (3), 530-530
KAMPOURIDIS, M., CHEN, S-H. and TSANG, E., (2012). MICROSTRUCTURE DYNAMICS AND AGENT-BASED FINANCIAL MARKETS: CAN DINOSAURS RETURN?. Advances in Complex Systems. 15 (supp02), 1250060-1250060
Kampouridis, M., Chen, S-H. and Tsang, E., (2012). Market fraction hypothesis: A proposed test. International Review of Financial Analysis. 23, 41-54
Books (4)
Sim, K., Kaufmann, P., Ascheid, G., Bacardit, J., Cagnoni, S., Cotta, C., D’Andreagiovanni, F., Divina, F., Esparcia-Alcázar, AI., Vega, FFD., Glette, K., Hubert, J., Hidalgo, JI., Iacca, G., Kampouridis, M., Kramer, O., Mavrovouniotis, M., Mora García, AM., Nguyen, TT., Otero, F., Schaefer, R., Silva, S., Tonda, A., Urquhart, N. and Zhang, M., (2018). Preface
Squillero, G., Sim, K., Ascheid, G., Bacardit, J., Brabazon, A., Burelli, P., Cagnoni, S., Coler, M., Cotta, C., D’Andreagiovanni, F., Divina, F., Esparcia-Alcázar, AI., de Vega, FF., Glette, K., Haasdijk, E., Heinerman, J., Hidalgo, JI., Hu, T., Iacca, G., Kampouridis, M., Kaufmann, P., Mavrovouniotis, M., Mora Garcia, AM., Schaefer, R., Silva, S., Tarantino, E., Nguyen, TT., Tonda, A., Urquhart, N. and Zhang, M., (2017). Preface
Squillero, G., Bacardit, J., Cagnoni, S., Falco, ID., Divina, F., Esparcia-Alcázar, AI., Glette, K., Hidalgo, JI., Kampouridis, M., Mavrovouniotis, M., Nguyen, TT., Sim, K., Urquhart, N., Burelli, P., Brabazon, A., Cotta, C., Cioppa, AD., Eiben, AE., De Vega, FF., Haasdijk, E., Hu, T., Kaufmann, P., Mora Garcia, AM., Schaefer, R., Tarantino, E. and Zhang, M., (2016). Preface
Squillero, G., Bacardit, J., Cagnoni, S., De Falco, I., Divina, F., Esparcia-Alcázar, AI., Glette, K., Hidalgo, JI., Kampouridis, M., Mavrovouniotis, M., Nguyen, TT., Sim, K., Urquhart, N., Burelli, P., Brabazon, A., Cotta, C., Cioppa, AD., Eiben, AE., de Vega, FF., Haasdijk, E., Hu, T., Kaufmann, P., Garcia, AMM., Schaefer, R., Tarantino, E. and Zhang, M., (2016). Preface
Book chapters (1)
Kampouridis, M., Chen, S-H. and Tsang, E., (2011). Market Microstructure: A Self-Organizing Map Approach to Investigate Behavior Dynamics under an Evolutionary Environment. In: Studies in Computational Intelligence. Editors: . Springer Berlin Heidelberg. 181- 197. 9783642233357
Conferences (52)
Habbab, F. and Kampouridis, M., Optimising a Prediction-based, Mixed-asset portfolio including REITs
Rayment, G., Kampouridis, M. and Adegboye, A., Predicting Directional Change Reversal Points with Machine Learning Regression Models
Rayment, G. and Kampouridis, M., Enhancing High-Frequency Trading with Deep Reinforcement Learning using Advanced Positional Awareness Under a Directional Changes Paradigm
Long, X. and Kampouridis, M., α-dominance two-objective Optimization Genetic Programming for Algorithmic Trading under a Directional Changes Environment
Christodoulaki, E. and Kampouridis, M., (2024). Combining Technical and Sentiment Analysis under a Genetic Programming algorithm
Habbab, FZ. and Kampouridis, M., (2024). Machine Learning for Real Estate Time Series Prediction
Habbab, F., Kampouridis, M. and Papastylianou, T., (2023). Improving REITs Time Series Prediction Using ML and Technical Analysis Indicators
Christodoulaki, E., Kampouridis, M. and Kyropoulou, M., (2023). Enhanced Strongly typed Genetic Programming for Algorithmic Trading
Long, X., Kampouridis, M. and Kanellopoulos, P., (2023). Multi-objective optimisation and genetic programming for trading by combining directional changes and technical indicators
Salman, O., Melissourgos, T. and Kampouridis, M., (2023). Optimization of Trading Strategies using a Genetic Algorithm under the Directional Changes Paradigm with Multiple Thresholds
Rayment, G. and Kampouridis, M., (2023). High Frequency Trading with Deep Reinforcement Learning Agents Under a Directional Changes Sampling Framework
Christodoulaki, E. and Kampouridis, M., (2023). Fundamental, Technical and Sentiment Analysis for Algorithmic Trading with Genetic Programming
Christodoulaki, E., Kampouridis, M. and Kanellopoulos, P., (2022). Technical and Sentiment Analysis in Financial Forecasting with Genetic Programming
Habbab, F., Kampouridis, M. and Voudouris, A., (2022). Optimizing Mixed-Asset Portfolios Involving REITs
Christodoulaki, E. and Kampouridis, M., (2022). Using strongly typed genetic programming to combine technical and sentiment analysis for algorithmic trading
(2022). Preface
Habbab, FZ. and Kampouridis, M., (2022). Optimizing Mixed-Asset Portfolio With Real Estate: Why Price Predictions?
Long, X., Kampouridis, M. and Jarchi, D., (2022). An in-depth investigation of genetic programming and nine other machine learning algorithms in a financial forecasting problem
Salman, O., Kampouridis, M. and Jarchi, D., (2022). Trading Strategies Optimization by Genetic Algorithm under the Directional Changes Paradigm
Long, X., Kampouridis, M. and Kanellopoulos, P., (2022). Genetic programming for combining directional changes indicators in international stock markets
Adegboye, A., Kampouridis, M. and Johnson, CG., (2017). Regression genetic programming for estimating trend end in foreign exchange market
Kampouridis, M., Adegboye, A. and Johnson, C., (2017). Evolving Directional Changes Trading Strategies with a New Event-Based Indicator
Cramer, S., Kampouridis, M., Freitas, AA. and Alexandridis, AK., (2017). Pricing Rainfall Based Futures Using Genetic Programming
Cramer, S., Kampouridis, M. and Freitas, AA., (2016). Feature engineering for improving financial derivatives-based rainfall prediction
Cramer, S., Kampouridis, M. and Freitas, A., (2016). A Genetic Decomposition Algorithm for Predicting Rainfall within Financial Weather Derivatives
Squillero, G., Burelli, P., Bacardit, J., Brabazon, A., Cagnoni, S., Cotta, C., Falco, ID., Cioppa, AD., Divina, F., Eiben, AE., Esparcia-Alcàza, AI., de Vega, FF., Glette, K., Haasdijk, E., Hidalgo, JI., Hu, T., Kampouridis, M., Kaufmann, P., Mavrovouniotis, M., Mora García, AM., Nguyen, TT., Schaefer, R., Sim, K., Tarantino, E., Urquhart, N. and Zhang, M., (2016). Applications of evolutionary computation: 19th European conference, Evoapplications 2016 Porto, Portugal, March 30 – April 1, 2016 proceedings, part II
(2016). Applications of Evolutionary Computation
Cramer, S., Kampouridis, M., Freitas, AA. and Alexandridis, A., (2015). Predicting Rainfall in the Context of Rainfall Derivatives Using Genetic Programming
Cramer, S. and Kampouridis, M., (2015). Optimising the deployment of fibre optics using Guided Local Search
Gypteau, J., Otero, FEB. and Kampouridis, M., (2015). Generating Directional Change Based Trading Strategies with Genetic Programming
(2015). Applications of Evolutionary Computation
Shao, M., Smonou, D., Kampouridis, M. and Tsang, E., (2014). Guided Fast Local Search for speeding up a financial forecasting algorithm
Aluko, B., Smonou, D., Kampouridis, M. and Tsang, E., (2014). Combining different meta-heuristics to improve the predictability of a Financial Forecasting algorithm
Kattan, A., Kampouridis, M. and Agapitos, A., (2014). Generalisation Enhancement via Input Space Transformation: A GP Approach
Otero, FEB. and Kampouridis, M., (2014). A Comparative Study on the Use of Classification Algorithms in Financial Forecasting
Kattan, A., Kampouridis, M., Ong, Y-S. and Mehamdi, K., (2014). Transformation of input space using statistical moments: EA-based approach
Brookhouse, J., Otero, FEB. and Kampouridis, M., (2014). Working with OpenCL to speed up a genetic programming financial forecasting algorithm
Smonou, D., Kampouridis, M. and Tsang, E., (2013). Metaheuristics application on a financial forecasting problem
Shaghaghi, AR., Glover, T., Kampouridis, M. and Tsang, E., (2013). Guided Local Search for Optimal GPON/FTTP Network Design
Alexandiris, AK. and Kampouridis, M., (2013). Temperature Forecasting in the Concept of Weather Derivatives: A Comparison between Wavelet Networks and Genetic Programming
Kampouridis, M. and Sim, KM., (2013). A GP approach for price-speed optimizing negotiation
Kampouridis, M. and Otero, FEB., (2013). Using Attribute Construction to Improve the Predictability of a GP Financial Forecasting Algorithm
Kampouridis, M., (2013). An initial investigation of choice function hyper-heuristics for the problem of financial forecasting
Alsheddy, A. and Kampouridis, M., (2012). Off-line parameter tuning for Guided Local Search using Genetic Programming
Kampouridis, M., Glover, T., Shaghaghi, AR. and Tsang, E., (2012). Using a genetic algorithm as a decision support tool for the deployment of Fiber Optic Networks
Kampouridis, M. and Tsang, E., (2011). Using Hyperheuristics under a GP Framework for Financial Forecasting
Kampouridis, M., Chen, S-H. and Tsang, E., (2011). Market Microstructure: Can Dinosaurs Return? A Self-Organizing Map Approach under an Evolutionary Framework
Kampouridis, M., Chen, S-H. and Tsang, E., (2011). Investigating the effect of different GP algorithms on the non-stationary behavior of financial markets
Chen, S-H., Kampouridis, M. and Tsang, E., (2011). Microstructure Dynamics and Agent-Based Financial Markets
Kampouridis, M., Chen, S-H. and Tsang, E., (2010). Testing the Dinosaur Hypothesis under Empirical Datasets
Kampouridis, M. and Tsang, E., (2010). EDDIE for investment opportunities forecasting: Extending the search space of the GP
Kampouridis, M., Chen, S-H. and Tsang, E., (2010). Testing the Dinosaur Hypothesis under different GP algorithms
Grants and funding
2024
Trinity House (Harwich port) Consultancy Project
General Lighthouse Authorities of the UK and Ireland
Trinity House (Harwich port) Consultancy Project - v3
General Lighthouse Authorities of the UK and Ireland
Trinity House (Harwich port) Consultancy Project
General Lighthouse Authorities of the UK and Ireland
Improving the �Assistant Coach� function on a fantasy league game website
Voono Ltd
To explore and implement applications of natural language processing in commodities trading software, enabling operators to interact with their data in a conversational manner.
Innovate UK (formerly Technology Strategy Board)
2023
ESNEFT Waiting List Reduction
East Suffolk and North Essex NHS Foundation Trust
Iceni Projects Ltd
Innovate UK (formerly Technology Strategy Board)
IFE KTP Project Application: 'To design a custom transport management system using advanced machine learning techniques and data science for process automation and accurate prediction of vessel arrival times in the context of sea freight forwarding'.
Innovate UK (formerly Technology Strategy Board)
Project: Statement of Works � Applicability of Machine Learning Technology to GLA Services and Applications
Research and Development Directorate of the General Lighthouse Authorities of UK and Ireland
KTP with Hood Group: To embed the latest techniques in machine learning and natural language processing for automation of data collection, collation and provision in the form of a concierge style app for travel insurance customers.
Innovate UK (formerly Technology Strategy Board)
DOCME EDGE -project to carry out evaluation of running AI driven computations via App on personal devices instead of via cloud based systems
DOCME TECHNOLOGIES LTD
2022
Applicability of Machine Learning Technology to GLA Services and Applications (Phase 2)
Research and Development Directorate of the General Lighthouse Authorities of UK and Ireland
Automation of processes and in-house systems
PFE Express Limited
PFE Express Ltd KTP Application - 22_23 R3
PFE Express Limited
Applicability of Machine Learning Technology to GLA Services and Applications (Phase 2)
Research and Development Directorate of the General Lighthouse Authorities of UK and Ireland
2021
Horus Security KTP Application
Innovate UK (formerly Technology Strategy Board)
Shepherd Compello KTP
Innovate UK (formerly Technology Strategy Board)
Applicability of Machine Learning Technology to GLA Services and Applications
Research and Development Directorate of the General Lighthouse Authorities of UK and Ireland
2020
Can data mining analyse financial and behavioural information gathered through survey questions
Dom Education Limited
Contact
Academic support hours:
Please email me first to arrange a meeting.
