Computational Finance & Economics Research Laboratory

Papers

Computational Finance & Economics Research Laboratory
University of Essex

Related works: constraint satisfaction and optimization (papers)


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Alexandrova et al 2005
Alexandrova-Kabadjova, B., Krause, A. & Tsang, E.P.K., An agent-based model of interactions in the payment card market, 10th Annual Workshop on Economic Heterogeneous Interacting Agent (WEHIA 2005), Colchester, UK, June 2005
Alexandrova et al 2005
Alexandrova-Kabadjova, B., Tsang, E.P.K. & Krause, A., Competition among payment cards, an agent-based approach, Agent-Based Models for Economic Policy Design 2005 (ACEPOL05), Bielefeld University, June 30 - July, 2, 2005
Alexandrova et al 2006
Alexandrova-Kabadjova, B., Krause, A. & Tsang, E.P.K., Competition among Payment Networks using Generalized Population Based Incremental Learning, 12th International Conference on Computing in Economics and Finance (CEF2006), Limassol, Cyprus, 22-24 June 2006
Alexandrova et al 2006
Alexandrova-Kabadjova, B., Krause, A. & Tsang, E.P.K., Market structure and information in payment card markets, Working Paper WP006-06, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, March 2006
Alexandrova et al 2007
Alexandrova-Kabadjova, B., Tsang, E.P.K. & Krause, A., The price structure and the demand sensitivity in the artificial payment card market, Proceedings, 13th International Conference on Computing in Economics and Finance (CEF2007), Society for Computational Economics, Montreal 14 to 16 June, 2007
Alexandrova 2007
Alexandrova-Kabadjova, B., Tsang, E.P.K. & Krause, A., Competition in an artificial payment card market, in A. Babrazon (ed.), Natural Computing in Computational Economics and Finance, Studies in Computational Intelligence Series, Springer, 2007, 233-252
Alexandrova 2007 Alexandrova-PhD2007.pdf (1.4MB)
Alexandrova-Kabadjova, B., Artificial payment card market - an agent based approach, PhD Thesis, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, 2007
Alexandrova et al 2007
Alexandrova-Kabadjova, B., Krause, A. & Tsang, E.P.K., An agent-based model of interactions in the payment card market, 8th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'07), Special Session on Agent-based Approach to Service Sciences, Birmingham, 16-19 December 2007
Alexandrova et al 2008a
B. Alexandrova-Kabadjova, E.P.K. Tsang and A. Krause, Finding Profit-Maximizing Strategies for the Articial Payment Card Market, CCFEA Working Paper WP016-08, University of Essex, Great Britain, 2008
Alexandrova et al 2008b
B. Alexandrova-Kabadjova, E.P.K. Tsang and A. Krause, Competition is bad for consumers: Analysis of an Artificial Payment Card Market, CCFEA Working Paper WP017-08, University of Essex, Great Britain, 2008
Alexandrova et al 2008c
B. Alexandrova-Kabadjova, E.P.K. Tsang and A. Krause, Evolutionary Learning of the Optimal Pricing Strategy in an Artificial Payment Card Market, CCFEA Working Paper WP018-08, University of Essex, Great Britain, 2008
Alexandrova 2009
B. Alexandrova-Kabadjova, Impact of interchange fees on a nonsaturated multi-agent payment card market, Intelligent Systems in Accounting, Finance and Management, Vol.16, 2009, 33-48
Alexandrova et al JACII 2011
B. Alexandrova-Kabadjova, E.P.K. Tsang & A. Krause, Competition is bad for consumers: analysis of an artificial payment card market, Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII), Fuji Technology Press, Vol.15, No.2, March 2011, 188-196
Alexandrova et al JILSA 2011
B. Alexandrova-Kabadjova, E.P.K. Tsang & A. Krause, Profit-maximizing strategies for an artificial payment card market, is learning possible? Journal of Intelligent Learning Systems and Applications, Vol.3, No.2, May 2011, 70-81
Alexandrova et al IJAC 2011
B. Alexandrova-Kabadjova, A. Krause & E.P.K. Tsang, Market structure and information in payment card markets, International Journal of Automation and Control (IJAC), Vol.8, No.3, 2011, 364-370
Alexandrova et al. Edited book 2012
B. Alexandrova-Kabadjova, S. Martinez-Jaramillo, A. L. Garcia-Almanza & E. Tsang (ed.), Simulation in Computational Finance and Economics: Tools and Emerging Applications, IGI Global, 2012
AlOud et al 2010
M. AlOud, M., R. Olsen & E.P.K. Tsang, Definitions of Directional-Change Events, Paper 17, Proceedings, 2010 2nd Computer Science and Electronic Engineering Conference (CEEC), IEEE Xplore, September 2010
AlOud et al 2012
M. Aloud, E.P.K.Tsang, R.Olsen & A. Dupuis, A Directional-Change Events Approach for Studying Financial Time Series, Economics: The Open-Access, Open-Assessment E-Journal, No. 2012-36, 7 September 2012, 1–17. http://dx.doi.org/10.5018/economics-ejournal.ja.2012-36 (cache)
AlOud et al 2012
M.AlOud, E.P.K.Tsang & R.Olsen, Modelling the FX market traders' behaviour: an agent-based approach, Chapter 15, Alexandrova-Kabadjova B., S. Martinez-Jaramillo, A. L. Garcia-Almanza & E. Tsang (ed.), Simulation in Computational Finance and Economics: Tools and Emerging Applications, IGI Global, 2012, 202-228
AlOud et al 2017
AlOud, M., Fasli, M., Tsang, E., Dupuis, A. & Olsen, R., Modelling the high frequency FX Market: an agent-based approach, Computational Intelligence, Vol.33, Issue 4, November 2017, 771-825 (early version)
Aluko et al 2014
B. Aluko, D. Smonou, M. Kampouridis & E. Tsang, Combining different meta-heuristics to improve the predictability of a financial forecasting algorithm, IEEE Computational Intelligence for Financial Engineering & Finance (CIFEr), London, UK, 27-28 March 2014 (early version)
Ao 2018
Han Ao, A Directional Changes based study on stock market, PhD Thesis, Centre for Computational Finance and Economic Agents, University of Essex, 2018
Ao 2019
Ao, H. & Tsang, E.P.K., Trading algorithms built with Direction Changes, IEEE Conference on Computational Intelligence for Financial Engineering and Economics (CIFEr) 2019 Conference, Shenzhen, China, 4th-5th May 2019
Bakhach et al 2016a
Bakhach, A., Tsang, E.P.K. & Jalalian, H., Forecasting Directional Changes in FX Markets, IEEE Symposium on Computational Intelligence for Financial Engineering & Economics (IEEE CIFEr'16), Athens, Greece, 6-9 December 2016
Bakhach et al 2016b
Bakhach, A., Tsang, E.P.K., Ng, W.L. & Raju Chinthalapati, V.L., Backlash Agent: A Trading Strategy Based On Directional change, IEEE Symposium on Computational Intelligence for Financial Engineering & Economics (IEEE CIFEr'16), Athens, Greece, 6-9 December 2016
Bakhach et al 2018b
A. Bakhach, V.L.R. Chinthalapati, E.P.K. Tsang & A.R. El Sayed, Intelligent Dynamic Backlash Agent: a trading strategy based on the directional change framework, Algorithms, Special Issue on Algorithms in Computational Finance, MDPI Open Access Publishing (ISSN 19994893), 11(11), 2018
Bakhach et al 2018a
Bakhach, A., Tsang, E.P.K. & Raju Chinthalapati, V.L., TSFDC: A trading strategy based on forecasting directional change, Intelligent Systems in Accounting, Finance and Management, Vol.25, Issue 3, May 2018
Bakhach PhD 2018
Bakhach, A., Developing trading strategies under the Directional Changes framework, with application in the FX market, PhD Thesis, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, 2018
Bernardo et al UKCI 2012
D. Bernardo, H. Hagras & E.P.K. Tsang, An interval Type-2 fuzzy logic based system for model generation and summarization of arbitrage opportunities in stock markets, 12th Annual UK Workshop on Computational Intelligence (UKCI), Edinburgh, UK, 5-7 September 2012, 1-7 (ISBN 978-1-4673-4391-6)
Bernardo et al AIS2012
D. Bernardo, H. Hagras & E.P.K. Tsang, An interval Type-2 fuzzy logic system for the modelling and prediction of financial applications, International Conference on Autonomous and Intelligent Systems (AIS), Aveiro, Portugal, 25-27 June 2012, 95-105 (ISBN 978-3-642-31368-4)
Bernardo et al FU-IEEE 2013
D. Bernardo, H. Hagras & E.P.K. Tsang, An Genetic Type-2 fuzzy logic based system for financial applications, modelling and prediction, Proceedings, IEEE International Conference on Fuzzy Systems (FU-IEEE), Hyderabad, India, 7-10 July 2013
Bernardo et al Soft Computing 2013
D. Bernardo, H. Hagras & E.P.K. Tsang, A genetic Type-2 fuzzy logic based system for the generation of summarised linguistic predictive models for financial applications, Soft Computing, 2013
Bisig et al 2012
Bisig, T., Dupuis, A., Impagliazzo, V & Olsen, R.B., The scale of market quakes, Quantitative Finance Vol.12, No.4, 2012, 501-508
Butler 2015
Butler, J., Programming for Betfair, BPT Publications, 2015. (ISBN 151143211X)
Butler 2016
Butler, J., Betfair Trading Techniques: Trading Models, Money Management, Machine Learning & Algo-Trading, CreateSpace Independent Publishing Platform, 2016 (ISBN-10: 1514286629; ISBN-13: 978-1514286623) {Anyone interested in machine learning for finance, forecasting and EDDIE should consult this book.}
Chen & Tsang 2018
J. Chen & E.P.K. Tsang, Classification of Normal and Abnormal Regimes in Financial Markets, Algorithms, Special Issue on Algorithms in Computational Finance, 11(12), 202, MDPI Open Access Publishing (ISSN 19994893), published online, December 2018
Chen & Tsang 2019
Chen, J. & Tsang, E.P.K., Tracking Regime Changes, IEEE Conference on Computational Intelligence for Financial Engineering and Economics (CIFEr) 2019 Conference, Shenzhen, China, 4th-5th May 2019
Chen & Tsang 2021
J. Chen & E.P.K.Tsang, Detecting Regime Change in Computational Finance, Data Science, Machine Learning and Algorithmic Trading, CRC Press, 2021
Chen et al 2011
S-H. Chen, M. Kampouridis & E.P.K. Tsang, Microstructure Dynamics and Agent-Based Financial Markets, in T. Bosse, A. Geller, and C.M. Jonker (Eds.), Proceedings on Eleventh International Workshop on Multi-Agent-Based Simulation (MABS 2010), LNAI 6532, Springer-Verlag Berlin Heidelberg, 2011, 121-135
Chinthalapati & Tsang 2019
V.L.R. Chinthalapati & E.P.K. Tsang, Editorial: Special Issue on Algorithms in Computational Finance, Algorithms, Special Issue on Algorithms in Computational Finance, 12(4), 69, MDPI Open Access Publishing (ISSN 19994893), March 2019
Dinarvand 2016
Dinarvand, P., Upward and Downward Conditional Probabilities in 28 Currency Exchange Rates, MSc Dissertation, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, 2016
Faleiro PhD 2018
Faleiro, J.M. Jr, Supporting Large Scale Collaboration and Crowd-based Investigation in Economics: A Computational Representation for Description and Simulation of Financial Models, PhD Thesis, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, 2018
Faleiro 2018 (a)
Faleiro, J.M. Jr, Enabling Scientific Crowds: The Theory of Enablers for Crowd-Based Scientific Investigation, Technical Report Archive arXiv:1809.07195, Cornel University, 2018 (cache)
Faleiro 2018 (b)
Faleiro, J.M. Jr, A Language for Large-Scale Collaboration in Economics: A Streamlined Computational Representation of Financial Models, Technical Report Archive arXiv:1809.06471, Cornel University, 2018 (cache)
Faleiro 2018 (c)
Faleiro, J.M. Jr, Automating Truth: The Case for Crowd-Powered Scientific Investigation in Economics, Technical Report Archive arXiv:1809.02671, Cornel University, 2018 (cache)
Faleiro & Tsang 2018 (a)
Faleiro, J.M. Jr & Tsang, E.P.K., Supporting Crowd-Powered Science in Economics: FRACTI, a Conceptual Framework for Large-Scale Collaboration and Transparent Investigation in Financial Markets, Technical Report Archive arXiv:1808.07959, Cornel University, 2018 (early version)
Faleiro & Tsang 2018 (b)
Faleiro, J.M. Jr & Tsang, E.P.K., Black Magic Investigation Made Simple: Monte Carlo Simulations and Historical Back Testing of Momentum Cross-Over Strategies Using FRACTI Patterns, Technical Report Archive arXiv:1808.07949, Cornel University, 2018 (early version)
Fu 2011
Fu, Q., Evaluation and extension of the Gann swing trading rules, MSc Dissertation, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, 2011
Garcia & Tsang 2006a
Garcia-Almanza, A.L. & Tsang, E.P.K., Simplifying Decision Trees Learned by Genetic Algorithms, Proceedings, Congress on Evolutionary Computation (CEC) 2006, 7906-7912
Garcia & Tsang 2006b
Garcia-Almanza, A.L. & Tsang, E.P.K., Forecasting stock prices using Genetic Programming and Chance Discovery, Proceedings, 12th International Conference on Computing in Economics and Finance (CEF2006), Limassol, Cyprus, 22-24 June 2006
Garcia & Tsang 2006c GarciaTsang-ChanceDiscovery-Kes2006.pdf
Garcia-Almanza, A.L. & Tsang, E.P.K., The Repository Method for Chance Discovery in Financial Forecasting, Proceedings, 10th International Conference on Knowledge-Based & Intelligent Information & Engineering Systems (KES2006), Bournemouth, UK, 9-11 October 2006
Garcia & Tsang, 2007
Garcia-Almanza, A.L. & Tsang, E.P.K., Detection of stock price movements using chance discovery and genetic programming, International Journal of Knowledge-based and Intelligent Engineering Systems, Vol.11, No.5, December 2007, 329-344 (early version, 488K)
Garcia & Tsang 2007 GarciaTsang-Repositorymethod-Cec2007.pdf (300K)
Garcia-Almanza, A.L. & Tsang, E.P.K., Repository Method to suit different investment strategies, Proceedings, Congress on Evolutionary Computation (CEC 2007), Singapore, 25-28 September 2007, 790-797
Garcia & Tsang 2007 (early version, 211K)
Garcia-Almanza, A.L. & Tsang, E.P.K., Evolving decision rules to predict investment opportunities, International Journal of Automation and Control (IJAC), Vol.5, No.1, January 2008, 22-31
Garcia-Almanza et al 2008
Garcia-Almanza, A.L., Tsang, E.P.K. & E Galvan-Lopez, Evolving Decision rules to discover patterns in financial data sets, in E. Kontoghiorghes, B. Rustem & P. Winker (ed), Computational Methods in Financial Engineering, Springer, Heidelberg, 2008, 239-255
Garcia-Almanza 2008
Garcia-Almanza, A.L., New classification methods for gathering patterns in the context of genetic programming, PhD Thesis, Department of Computing and Electronic Systems, University of Essex, July 2008 (Revised version published as research monograph, 2011)
Garcia-Almanza & Tsang 2011 (monograph)
Garcia-Almanza, A.L. & E.P.K. Tsang, Evolutionary Applications for Financial Prediction: Classification Methods to Gather Patterns Using Genetic Programming, VDM Verlag, 2011
Garcia-Almanza et al 2012
Garcia Almanza, A.L., Martinez Jaramillo, S., Alexandrova-Kabadjova, B. & Tsang, E.P.K., Using genetic programming systems as early warning to prevent bank failure, Chapter 14, in Yap, A.Y. (ed.), Information systems for global financial markets, IGI Global, 2012, 369-382
Glattfelder et al 2011
Glattfelder, J.B., Dupuis, A. & Olsen, R. Patterns in high-frequency FX data: discovery of 12 empirical scaling laws, Quantitative Finance, Volume 11 (4), 2011, 599-614
Gosling 2003 Gosling-SSCM-Cec2003.pdf (775K)
Gosling, T., The Simple Supply Chain Model and Evolutionary Computation, Proceedings, 2003 Congress on Evolutionary Computation, Canberra, Australia, December 2003, 2322-2329
Gosling et al 2005 GosJinTsa-Pbil_vs_Ga-Cec2005.pdf (167K)
Gosling, T., Jin, N. & Tsang, E.P.K., Population based incremental learning with guided mutation versus genetic algorithms: iterated prisoners dilemma, Proceedings, Congress on Evolutionary Computation, Edinburgh, 2-5 September 2005, 958-965
Gosling et al 2006 (Early Draft) (1.9MB)
Gosling, T., Jin, N. & Tsang, E.P.K., Games, supply chains and automatic strategy discovery using evolutionary computation, in J-P. Rennard (Eds.), Handbook of research on nature-inspired computing for economics and management, Vol II, Chapter XXXVIII, Idea Group Reference, 2007, 572-588
Gosling et al 2006 GoslingTsang-Sscm-Cec2006.pdf (334K)
Gosling, T. & Tsang, E.P.K., Tackling the simple supply chain model, Proceedings, 2006 Congress on Evolutionary Computation, Vancouver, Canada, 16-21 July 2006, 7943-7950
Gosling 2007 gosling-phd20070422.pdf (4.7MB)
Gosling, T., Evolving middlemen strategies for simple supply chains, PhD Thesis, Department of Computer Science, University of Essex, 2007
Jin & Tsang 2005 JinTsa-Bargaining-Cig2005.pdf (72K)
Jin, N. & Tsang, E.P.K., Co-evolutionary strategies for an alternating-offer bargaining problem, IEEE Symposium on Computational Intelligence and Games, Colchester, UK 4-6 April 2005
Jin 2005 Jin-IncompleteInfo-Cec2005.pdf (162K)
Jin, N., Equilibrium selection by co-evolution for bargaining problems under incomplete information about time preferences, Proceedings, Congress on Evolutionary Computation, Edinburgh, 2-5 September 2005, 2661-2668
Jin & Tsang 2006 (slight error found, paper unavailable at the moment)
Jin, N. & Tsang, E.P.K., Co-adaptive Strategies for Sequential Bargaining Problems with Discount Factors and Outside Options, Proceedings, Congress on Evolutionary Computation (CEC) 2006, 7913-7920
Jin 2007 Jin-Bargaining-PhD2007.pdf (908K)
Jin, N., Constraint-based co-evolutionary genetic programming for bargaining problems, PhD Thesis, Department of Computer Science, University of Essex, UK, 2007
Jin et al 2009 pdf (310K)
Jin, N., Tsang, E. & Li, J., A constraint-guided method with evolutionary algorithms for economic problems, Applied Soft Computing, Vol.9, Iss.3, June 2009, 924-935 (mirror)
John 2014
John, Portfolio Optimization by Heuristic Algorithms, PhD Thesis, School of Computer Science and Electronic Engineering, University of Essex, 2014
Jin & Tsang 2011 (doi:10.1016/j.asoc.2011.07.013)
Jin, N. & Tsang, E.P.K., Bargaining strategies designed by evolutionary algorithms, Applied Soft Computing, Vol. 11, Issue 8, December 2011, 4701-4712
Kampouridis & Tsang 2010
M. Kampouridis & E.P.K. Tsang, EDDIE for Investment Opportunities Forecasting: Extending the Search Space of the GP, Proceedings, Congress on Evolutionary Computation, Barcelona, Spain, 18-23 July, 2010, 2019-2026
Kampouridis & Tsang 2011
M. Kampouridis & E.P.K. Tsang, Using hyperheuristics under a GP framework for financial forecasting, Proceedings, Learning and Intelligent OptimizatioN (LIONs), Rome, Italy, 17-21 January 2011
Kampouridis et al 2010
M. Kampouridis, S-H. Chen & E.P.K. Tsang, Testing the Dinosaur Hypothesis Under Different GP Algorithms, Proceedings, UK Workshop on Computational Intelligence (UKCI 2010), Colchester, UK, IEEE Xplore, September 2010 (early version)
Kampouridis PhD 2011
Kampouridis, M., Computational Intelligence in Financial Forecasting and Agent-Based Modeling: Applications of Genetic Programming and Self-Organizing Maps, PhD Thesis, University of Essex, 2011
Kampouridis et al 2011
M. Kampouridis, S-H. Chen & E.P.K. Tsang, Market microstructure: a self-organizing map approach to investigate, Natural Computing in Computational Finance, Volume 4, 2011
Kampouridis et al 2012a
M. Kampouridis, S-H. Chen & E.P.K. Tsang, Microstructure dynamics and agent-based financial markets: can dinosaurs return? Advances in Complex Systems, Vol.15, No.5, 2012
Kampouridis et al 2012b
M. Kampouridis, S-H. Chen & E.P.K. Tsang, Market fraction hypothesis: a proposed test, International Review of Financial Analysis, Vol.23, 2012, 41-54
Kampouridis et al 2012c
M. Kampouridis & E.P.K. Tsang, Investment opportunities forecasting: extending the grammar of a GP-based tool, International Journal of Computational Intelligence Systems, Vol.5, No.3, 2012, 530-541
Kampouridis et al 2013
M. Kampouridis, A. Alsheddy & E.P.K. Tsang, On the investigation of hyper-heuristics on a financial forecasting problem, Annals of Mathematics and Artificial Intelligence, Vol.68, Issue 4, 2013,225-246
Jin Li & Tsang 1999a LiTsa-Improve-FLAIRS99.ps (509K) PDF (57K)
Li, J. & Tsang, E.P.K., Improving technical analysis predictions: an application of genetic programming, Proceedings, The 12th International FLAIRS Conference (FLAIRS-99), USA, 1999, 108-112
Jin Li & Tsang 1999b LiTsa-C45-Cec99.ps (560K) PDF (57K)
Li, J. & Tsang, E.P.K., Investment decision making using FGP: a case study, Proceedings, Congress on Evolutionary Computation, Washington DC, USA, 6-9 July 1999, 1253-1259
Jin Li & Tsang 2000 LiTsa-LowRF-Cef2000.ps (754K) PDF (92K)
Li, J. & Tsang, E.P.K., Reducing Failures in Investment Recommendations using Genetic Programming, Proceedings, 6th International Conference on Computing in Economics and Finance, Society for Computational Economics, Barcelona, July 2000
Jin Li PhD 2001 Li-FGP-PhD2000.pdf
Li, J., FGP: a genetic programming based tool for financial forecasting, PhD Thesis, University of Essex, Colchester, Essex CO4 3SQ, UK, 2001
Shengnan Li PhD, 2022 (3M)
Li, S., Relating Volatility and Jumps between two markets under Directional Change, PhD thesis, Centre for Computational Finance & Economic Agents, University of Essex, September 2022
LiTsOH 2022
S. Li, E.P.K. Tsang & J. O'Hara, Measuring relative volatility in high‐frequency data under the directional change approach, Intelligent Systems in Accounting, Finance and Management, 02 June 2022; http://dx.doi.org/10.1002/isaf.1510 (Our reference: LiTsOH-RelativeVolatility-ISAFM2022.pdf)
Markose et al 2001
S. Markose, E.P.K. Tsang, H. Er, & A. Salhi, Evolutionary arbitrage for FTSE index options and futures, Proceedings, Congress on Evolutionary Computation, CEC 2001 (Special Session on Time Series Analysis & Compumetric Forecasting), 2001, 275-282
Markose et al 2001
S. Markose, E.P.K. Tsang & H. Er, Evolutionary Decision Trees in FTSE-100 Index Options and Futures Arbitrage, in S-H. Chen (ed.), Genetic Algorithms and Programming in Computational Finance, Kluwer Series in Computational Finance, Chapter 14, 281-308
Markose 2001
S. Markose, The new evolutionary computational paradigm of complex adaptive systems, in S-H. Chen (ed.), Genetic Algorithms and Programming in Computational Finance, Kluwer Series in Computational Finance, Chapter 21, 443-484
Markose 2003a Markose-Computability-EconomicsDP574.pdf (324 K)
S. Markose, Computability and evolutionary complexity: market as complex adaptive systems (CAS), Discussion Paper 574, Economics Department, University of Essex, March 2003
Markose 2003b Markose-Surprise-EconomicsDP575.pdf (314 K)
S. Markose, Novelty and surprises in complex adaptive systems (CAS) dynamics: a computational theory of actor innovation, Invited talk: International Conference on Applications of Physics in Financial Analysis 4 (APFA4), Warsaw, 13-15 November 2003 (Also appear as Discussion Paper 575, Economics Department, University of Essex, November 2003)
Markose et al 2004 Markose-RedQueen-Wehia2004.pdf (2.5MB)
Markose, E.P.K. Tsang & S.Martinez-Jaramillo, The red queen principle and the emergence of efficient financial markets: an agent based approach, in: T.Lux, S.Reitz and E.Samanodou (Eds.) Nonlinear Dynamics and Heterogeneous Interacting Agents, Lecture Notes in Economics and Mathematical Systems 550, Springer, Berlin, Heidelberg, 2005 (Proceedings, 8th Workshop on economics and heterogeneous interacting agents (WEHIA), Kiel, Germany, Springer-Verlag, 2004)
Marquez & Martinez 2009 (Martinez-StressTesting-ISAF_2009.pdf 700K)
Marquez Diez Canedo, J & Martinez-Jaramillo, S., A network model of systemic risk: stress testing the banking system, Intelligent Systems in Accounting, Finance and Management, Vol.16, 2009, 87-110
Martinez 2007 (Martinez-PhD2007.pdf 6MB)
Martinez-Jaramillo, S., Artificial financial markets: an agent based approach to reproduce stylized facts and to study the Red Queen Effect, PhD Thesis, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, 2007
Martinez & Tsang 2009
Martinez-Jaramillo, S. & E.P.K. Tsang, Evolutionary Computation and Artificial Financial Markets, in A. Brabazon & M. O'Neill (eds.), Natural Computing in Computational Finance, Vol. 185, Springer-Verlag Berlin Heidelberg, 2009, 137-179
Martinez & Tsang 2009 (early version 1.5MB)
Martinez-Jaramillo, S. & Tsang, E.P.K., An heterogeneous, endogenous and co-evolutionary GP-based financial market, IEEE Transactions on Evolutionary Computation, Vol.13, No.1, 2009, 33-55
Masry et al 2010
S. Masry, M. AlOud, A. Dupuis, R. Olsen & E.P.K. Tsang, A novel approach for studying the high-frequency FOREX Market, Paper 15, Proceedings, 2010 2nd Computer Science and Electronic Engineering Conference (CEEC), IEEE Xplore, September 2010
Masry et al 2013
S. Masry, A. Dupuis, R.B.Olsen & E.P.K. Tsang, Time Zone Normalisation of FX Seasonality, Quantitative Finance, Vol.13, No.7, 2013, 1115-1123 (ISSN 1469-7688)
(Published on line by Taylor & Francis Online 9th June 2013)
Masry PhD 2013 (4MB)
S. Masry, Event-Based Microscopic Analysis of the FX Market, PhD Thesis, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, June 2013
Nazmy 2016
Nazmy, A., Value-at-Risk and Expected Shortfall for oil & gas related securities during the oil price slide, MSc Dissertation, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, 2016
Nolivari MSc 2015 (1.3MB)
M. Nolivari, Stress-testing SPEI: Policy recommendations about the Mexican Payment System simulating distressed liquidity scenarios, MSc Thesis, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, September 2015 (winner of the Best MSc Project Prize, 2015)
Ockenden 2016
Ockenden, A., Hedging Volatility Dispersion Portfolios: A Comparative Analysis, MSc Dissertation, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, 2016
Paniangtong MSc 2015 (2.2MB)
S. Paniangtong, The Evaluation of the Trend-Following Directional Change with the Trailing Stop and Major-Trend-Adjusted Strategies on Algorithmic Trading in the Foreign Exchange Markets, MSc Thesis, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, September 2015
Qi PhD 2011
J. Qi, Risk measurement with high-frequency data -- value-at-risk and scaling law methods, PhD Thesis, Centre for Computationa Finance and Economic Agents (CCFEA), University of Essex, 2012
Serguieva et al 2009
A. Serguieva, G.M. Caporale, E.P.K.Tsang & R. Yager, Editorial, Special issue on Risk Analysis in Complex Systems, Intelligent Systems in Accounting, Finance and Management, Vol.16, No.1-2, 2009, 1-3
Shao et al 2014
M. Shao, D. Smonou, M. Kampouridis & E. Tsang, Guided Fast Local Search for speeding up a financial forecasting algorithm, IEEE Computational Intelligence for Financial Engineering & Economics (CIFEr), London, UK, 27-28 March 2014 (early version)
Smonou et al 2013
D. Smonou, M. Kampouridis & E.P.K.Tsang, Metaheursitics application on a financial forecasting problem, Proceedings, IEEE Congress on Evolutionary Computation, Cancun, Mexico, 20-23 June 2013 (early version)
Tao PhD 2018
Tao, R., Using Directional Change for Information Extraction in Financial Market Data, PhD Thesis, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, 2018
Tsang, Butler & Li 1998 (An early version in pdf 171K)
Tsang, E.P.K., Butler, J.M. & Li, J., EDDIE beats the bookies, International Journal of Software, Practice & Experience, Wiley, Vol.28(10), August 1998, 1033-1043
Tsang et al 2000
zipped html version (32K) pdf version (150K) postscript version (478K)
Tsang, E.P.K., Li, J., Markose, S., Er, H., Salhi, A. & Iori, G., EDDIE In Financial Decision Making, Journal of Management and Economics , Vol.4, No.4, November 2000
Tsang & Li 2000 (early version 272K)
E.P.K. Tsang & J. Li, Combining Ordinal Financial Predictions With Genetic Programming, Proceedings, Second International Conference on Intelligent Data Engineering and Automated Learning (IDEAL-2000), Hong Kong, December 13-15, 2000, 532-537
pdf version (141K)
Tsang & Li 2002 TsangLi-FGP-Chen_CompFinance2002.pdf (271K, ignore chapter and page numbers)
E.P.K. Tsang & J. Li, EDDIE for financial forecasting, in S-H. Chen (ed.), Genetic Algorithms and Programming in Computational Finance, Kluwer Series in Computational Finance, 2002, Chapter 7, 161-174
Tsang & Gosling 2002 TsaGos-Negotiation-AAMAS2002.pdf (110K)
Tsang, E.P.K. & Gosling, T., Simple constrained bargaining game, First International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-2002), Bologna, Italy, July 15-19, 2002 (http://lia.deis.unibo.it/aamas2002/)
Tsang, Yung & Li 2004 (early version, 1.9MB)
E.P.K.Tsang, P.Yung & J.Li, EDDIE-Automation, a decision support tool for financial forecasting, Journal of Decision Support Systems, Special Issue on Data Mining for Financial Decision Making, Vol.37, No.4, 2004, 559-565
Tsang 2003 CSM-385.pdf (1.43M)
E.P.K. Tsang, Cooperation in competitions -- constraint propagation strategies in chain-bargaining, Technical Report CSM-385, Department of Computer Science, University of Essex, April 2003
Tsang & Martinez-Jaramillo 2004 TsangMartinez-CompFinance-Ieee_conneCtIonS2004.pdf (310K)
E.P.K. Tsang & S.Martinez-Jaramillo, Computational Finance, IEEE Computational Intelligence Society Newsletter, August 2004, 3-8
Tsang et al 2005 TGVVO-Reconnet-Mista2005.pdf (1.6MB)
E.P.K.Tsang, T.Gosling, B.Virginas, C.Voudouris & G.Owusu, Retractable contract network for distributed scheduling, Proceedings, 2nd Multidisciplinary International Conference on Scheduling: Theory & Applications (MISTA), New York, July 2005, 485-500
Tsang et al 2005 (early version, 115K)
Tsang, E.P.K., Markose, S. & Er, H., Chance discovery in stock index option and future arbitrage, New Mathematics and Natural Computation, World Scientific, Vo.1, No.3, 2005, 435-447
Tsang et al 2006 (TMEG-ChanceDiscovery-NMF2006.pdf, 207K)
Tsang, E.P.K., Markose, S., Er, H. & Garcia, A., EDDIE for discovering arbitrary opportunities, Post-conference Proceedings, Keynote Speech, Numerical Methods for Finance Conference, Dublin, Ireland, 14-15 June 2006 (extended abstract of the work above)
Tsang & Jin 2006
Tsang, E.P.K. & Jin, N., An Incentive Method to handle constraints in evolutionary algorithms with a case study, Proceedings, European Conference on Genetic Programming, 2006, Budapest, 10-12 April 2006, 133-144
Tsang 2006 (Abstract / Notes)
Tsang, E.P.K., Wind-tunnel Testing for strategy and market design, Invited Talk, Proceedings, Sixth IEEE International Conference on Intelligent System Design and Applications (ISDA06), Jinan, China, 16-18 October 2006, xxxvii-xxxvii
Tsang 2008, The CIDER Theory (SpringerLink)
Tsang, E.P.K., Computational intelligence determines effective rationality, International Journal of Automation and Control (IJAC), Vol.5, No.1, January 2008, 63-66 (mirror)
(Early version: Working Paper WP015-07, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, December 2007; SSRN)
Tsang 2008, IEEE TEC Editorial (draft)
Tsang, E.P.K. & Isasi, P., Editorial Introduction, Special Issue on Computational Finance and Economics, IEEE Transactions on Evolutionary Computation, Vol.13, No.1, February 2009, 1-2
Tsang 2009, Forecasting (project overview)
Tsang, E.P.K., Forecasting -- where computational intelligence meets the stock market, Frontiers of Computer Science in China, Springer, Vol.3, No.1, March 2009, 53-63
(also filed as Working Paper WP026-08, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, revised December 2008)
Tsang 2010 (Book Review)
Tsang, E.P.K. Book Review, on A.K. Kordon, Applying Computational Intelligence, Springer 2010, IEEE Computational Intellgience Magazine, May 2010, 108-109
Tsang, Olsen & Masry 2009-2010 (WP038-10)
Tsang, E.P.K. & Olsen, R., Event Calculus on high frequency finance, Workshop in Accounting, Finance and Management, BCS SGAI International Conference on Artificial Intelligence, Cambridge, UK 15 December 2009
(Revised paper filed as Working Paper WP038-10, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, 6 March 2012; further revised paper, with title changed, to appear in Quantitative Finance, see Tsang et al 2012)
Tsang CP2010
Tsang, E.P.K., Constraint-directed Search in Computational Finance and Economics, Extended Abstract, Invited Talk, in 16th International Conference on Principles and Practices of Constraint Programming, St Andrews, 7 September 2010
Tsang CCFEA 2010
Tsang, E.P.K., New ways to understand financial markets, Working Paper WP046-10, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, October 2010
Tsang CCFEA 2010
Tsang, E.P.K., Computation in finance: potentials and limitations, Working Paper WP047-10, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, November 2010
Tsang CCFEA 2010
Tsang, E.P.K., Directional changes, definitions, Working Paper WP050-10, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, November 2010
Tsang 2012
Tsang, E.P.K., Economic markets need warning system to avert crashes, New Scientist, 18 April 2012
Tsang et al 2013
Tsang, E.P.K., Olsen, R. & Masry, S., A Formalization of Double Auction Market Dynamics, Quantitative Finance, Vol.13, Iss.7, July 2013, 981-988 (From early Working Paper WP038-10, revised 2012 with title changed)
Tsang 2014
Tsang, E.P.K., Notations for Directional Change (DC) research, Research Note, 17 April 2014
Tsang et al 2017
Edward P K Tsang, Ran Tao, Antoaneta Serguieva and Shuai Ma, Profiling High Frequency Equity Price Movements in Directional Changes, Quantitative Finance, Vol.17, Issue 2, 2017, 217-225 (published on line: 07 June 2016)
(An earlier version of this paper appeared as Working Paper WP077-15, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, June 2015)
Tsang 2017
Tsang, E.P.K., Directional changes: a new way to look at price dynamics, In: Mandal J., Dutta P., Mukhopadhyay S. (eds) Computational Intelligence, Communications, and Business Analytics (CICBA), Communications in Computer and Information Science, Vol. 775, Springer, 2017, 45-55 (early version)
Tsang and Chen 2018
E.P.K.Tsang & J. Chen, Regime change detection using directional change indicators in the foreign exchange market to chart Brexit, IEEE Transactions in Emerging Technology in Computational Intelligence (TETCI), Vol.2, Issue 3, June 2018, pages 185-193 (DOI: 10.1109/TETCI.2017.2775235 / Electronic ISSN: 2471-285X)
Tsang 2021
E.P.K.Tsang, Directional change for handling tick-to-tick data, Journal of Chinese Economic and Business Studies, 2021 (DOI: 10.1080/14765284.2021.1989883) (early version)
Tsang 2023
E.P.K.Tsang, AI for Finance, CRC Press, June 2023
Tsang et al 2024
E.P.K.Tsang, S. Ma & V.L. Raju Chinthalapati, Nowcasting directional change in high frequency FX markets, Intelligent Systems in Accounting, Finance and Management, Wiley, March 2024
Voicu 2012
Voicu, S., Directional change trading trategies in the foreign exchange markets, MSc Thesis, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, 2012
Wang et al 2010
P. Wang, E.P.K. Tsang, T. Weise, K. Tang & X. Yao, Using GP to evolve decision rules for classification in financial data sets, The 9th IEEE International Conference on Cognitive Informatics (ICCI 2010), Beijing, 7-9 July 2010
Wang et al 2011
P. Wang, K. Tang, E.P.K. Tsang, X. Yao, A memetic genetic programming with decision tree-based local search for classification problems, in Proceedings of the 12th IEEE Congress on Evolutionary Computation (CEC’11), 2011, pp. 917–924 (mirror)
Wang et al 2012
P. Wang, K. Tang, T. Weise, E.P.K. Tsang & X. Yao, Multiobjective Genetic Programming for Maximizing ROC Performance, Neurocomputing, accepted for publication, July 2012 (mirror)
Yang 2011
Yang, Y., Technical analysis of trading rules in stock market within FTSE 100 stock data MSc Dissertation, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, 2011
Ye et al 2017
Ye, A., Chinthalapati, V.L.R., Serguieva, A. & Tsang, E., Developing sustainable trading strategies using directional changes with high frequency data, IEEE International Conference on Big Data, Boston, 11-14 December 2017
Zhang et al 2010
Zhang, Q., Li, H., Maringer, D. & Tsang, E.P.K., MOEA/D with NBI-style Tchebycheff approach for Portfolio Management, Proceedings, Congress on Evolutionary Computation, Barcelona, Spain, 18-23 July, 2010, 3008-3015 (IEEE Explore)


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