Papers

Computational Finance & Economics Research Laboratory
University of Essex

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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, to appear

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 Computing, Accepted for publication, 2011

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 2011

M. Aloud, E.P.K.Tsang, R.Olsen & A. Dupuis, A Directional-Change Events Approach for Studying Financial Time Series, Economics, No. 2011-28, July 2011, e-journal http://www.economics-ejournal.org/economics/discussionpapers/2011-28

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

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

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 on Automation and Control, 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

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)

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, September, 2011

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

Kampouridis et al 2011a

12. M. Kampouridis, S-H. Chen & E.P.K. Tsang, Microstructure dynamics and agent-based financial markets: can dinosaurs return? Advances in Complex Systems, accepted for publication, September 2011

Kampouridis et al 2011b

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, A. Alsheddy & E.P.K. Tsang, On the investigation of hyper-heuristics on a financial forecasting problem, Annals of Mathematics and Artificial Intelligence, accepted for publication February 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

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

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

Li & Tsang 2000 LiTsa-LowRF-Cef2000.ps (754K) PDF (92K) (zip ps 110K)

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

Li 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

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 2012

S. Masry, A. Dupuis, R.B.Olsen & E.P.K. Tsang, Time Zone Normalisation of FX Seasonality, Quantitative Finance, accepted for publication, July 2012

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

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

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, to appear

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 on Automation and Control, 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)

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 2012

Tsang, E.P.K., Olsen, R. & Masry, S. A Formalization of Double Auction Market Dynamics, Quantitative Finance, accepted for publication, October 2012 (From early Working Paper WP038-10, revised 2012 with title changed)

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 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

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

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)