Books and Edited Volumes

Articles and Other Contributions

  • Ben Craig, Dietmar Maringer, and Sandra Paterlini. “Creating (Parsimonious) Banking Networks”. In: 11th Conference on Computational and Financial Econometrics (CFE 2017) and 10th International Conference of the ERCIM (European Research Consortium for Informatics and Mathematics) Working Group on Computational and Methodological Statistics (CMStatistics 2017). 2017.
  • Wolfgang Aussenegg, Louisa Chen, Ranko Jelic, and Dietmar Maringer. “Time Varying Illiquidity of European Corporate Bonds”. In: 20th European Financial Management Association (EFMA) Annual Meeting 2016. Basel, 2016.
  • Dietmar Maringer and Susan Kriete-Dodds. “Overconfidence in the Credit Card Market”. In: Analyzing the Economics of Financial Market Infrastructures. Ed. by Martin Diehl, Biliana Alexandrova-Kabadjova, Richard Heuver, and Serafín Martínez-Jaramillo. IGI Global, 2016, pp. 150–168.
  • Christian Oesch and Dietmar Maringer. “A Neutral Mutation Operator in Grammatical Evolution”. In: Intelligent Systems’2014. Ed. by P. Angelov, K.T. Atanassov, L. Doukovska, M. Hadjiski, V. Jotsov, J. Kacprzyk, N. Kasabov, S. Sotirov, E. Szmidt, and S. Zadroz˙ny. Cham: Springer International Publishing, 2015, pp. 439–449.
  • Dietmar Maringer and Jin Zhang. “Transition Variable Selection for Regime Switching Recurrent Reinforcement Learning”. In: 2014 IEEE Conference on Computational Intelligence for Financial Engineering Economics (CIFEr). 2014, pp.   407–413.   doi:   10.1109/CIFEr.2014.6924102.
  • Jin Zhang and Dietmar Maringer. “Two Parameter Update Schemes for Recurrent Reinforcement Learning”. In: 2014 IEEE Congress on Evolutionary Computation (CEC). 2014, pp. 1449–1453. doi: 10.1109/CEC.2014.6900330.
  • Dietmar Maringer. “Heuristic Optimization for Time Series Analysis”. In: 7th International Workshop on Simulation. University of Bologna, 2013.
  • Dietmar Maringer and Sebastian Deininger. “Estimating Time Series Models with Heuristic Methods: Tue Case of Economic Parity Conditions”. In: 6th International Conference of the ERCIM WG on Computational and Methodological Statistics. London, 2013.
  • Christian Oesch and Dietmar Maringer. “Portfolio Optimization under Market Impact Costs”. In: 2013 IEEE Congress on Evolutionary Computation. 2013, pp. 1–7. doi:        10.1109/CEC.2013.6557546.
  • Jin Zhang and Dietmar Maringer. “Indicator Selection for Daily Equity Rrading with Recurrent Reinforcement Learning”. In: GECCO 2013. 2013, pp. 1757–1758.
  • Dietmar Maringer and Susan Kriete-Dodds. “Subscription Markets: An Agent-Based Approach”. In: Proceedings of the 8th European Social Simulation Association Conference. 2012, pp. 179–190.
  • Dietmar Maringer and Tikesh Ramtohul. “Regime-Switching Recurrent Reinforcement Learning in Automated Trading”. In: Natural Computing in Computational Finance: Volume 4. Ed. by Anthony Brabazon, Michael O’Neill, and Dietmar Maringer. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012, pp. 93–121. doi: 10.1007/978-3-642-23336-46. url: https://doi.org/10.1007/978-3-642-23336-46.
  • Dietmar Maringer and Tikesh Ramtohul. “GP-Based Rebalancing Triggers for the CPPI”. In: 2011 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr). 2011, pp. 1–8. doi: 10.1109/CIFER.2011.5953561.
  • Jin Zhang and Dietmar Maringer. “Selecting Pair-Copulas with Downside Risk Minimisation”. In: Int. Journal of Financial Markets and Derivatives 2 (Jan. 2011), pp. 121–148.
  • Dietmar Maringer and Tikesh Ramtohul. “Threshold Recurrent Reinforcement Learning Model for Automated Trading”. In: Applications of Evolutionary Computation. Ed. by Cecilia Di Chio et al. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 212–221.
  • Qingfu Zhang, Hui Li, Dietmar Maringer, and Edward Tsang. “MOEA/D with NBI-style Tchebycheff Approach for Portfolio Management”. In: IEEE Congress on Evolutionary Computation. 2010, pp. 1–8. doi:     10.1109/CEC.2010.5586185.
  • Peter Winker and Dietmar Maringer. “Model Selection and Rank Estimation in Vector Error Correction Models”. In: Computational and Financial Econometrics Conference. 2009.
  • Jin Zhang and Dietmar Maringer. “Improving Sharpe Ratios and Stability of Portfolios by Using a Clustering Technique”. In: Proceedings of the World Congress on Engineering (WCE 2009). Vol. I. 2009, pp. 1–6.
  • Anil Khuman, Nick Constantinou, and Dietmar Maringer. “Constant Proportion Portfolio Insurance: Statistical Properties and Practical Implications”. In: Computational Management Science Conference. London, 2008.
  • Dietmar Maringer. “Heuristic Optimization for Portfolio Management [Application Notes]”. In: IEEE Computational Intelligence Magazine 3.4 (2008), pp.  31–34.  doi:  10.1109/MCI.2008.929847.
  • Dietmar Maringer and Mark Meyer. “Smooth Transition Autoregressive Models – New Approaches to the Model Selection Problem”. In: Studies in Nonlinear Dynamics and Econometrics 12 (Mar. 2008).
  • Dietmar Maringer and Evdoxia Pliota. “Clustering of Extreme Events: Application of a Time-Varying Threshold”. In: Computational Management Science Conference. London, 2008.
  • Philip Saks and Dietmar Maringer. “Genetic Programming in Statistical Arbitrage”. In: Applicationsof Evolutionary Computing. Ed. by Mario Giacobini et al. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008, pp. 73–82.
  • Philip Saks and Dietmar Maringer. Single versus Dual Tree Genetic Programming for Dynamic Binary Decision Making. CCFEA Working Paper Series WP019-08. University of Essex, 2008.
  • Dietmar Maringer and Olufemi Oyewumi. “Index Tracking with Constrained Portfolios”. In: Intelligent Systems in Accounting, Finance and Management 15 (June 2007), pp. 57–71.
  • Dietmar Maringer and Evdoxia Pliota. “Extreme Value Theory for VaR: Tue Problem of Sample Size Choice”. In: Computational Management Science Conference. Geneva, 2007.
  • Peter Winker and Dietmar Maringer. “The Threshold Accepting Optimisation Algorithm in Economics and Statistics”. In: Optimisation, Econometric and Financial Analysis. Ed. by Erricos John Kontoghiorghes and Cristian Gatu. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007, pp. 107–125.
  • Dietmar Maringer. Small is Beautiful. Diversification with a Limited Number of Assets. CCFEA Working Paper Series WP005-06. University of Essex, 2006.
  • Peter Winker and Dietmar Maringer. “The Hidden Risks of Optimizing Bond Portfolios under VaR”. In: Journal of Risk 9.4 (July 2005), pp. 1–19.
  • Peter Winker and Dietmar Maringer. Portfolio Optimization and Dilferent Risk Constraints with Modified Memetic Algorithms. Working Paper 2003-005E. University of Erfurt, 2003.
  • Thomas Breuer, Dietmar Maringer, and Filip Pistovcak. “Selecting Relevant Risk Factors for Stress Testing Scenarios”. In: International Conference on Operations Research. Klagenfurt, 2002.
  • Edwin O. Fischer, Christian Keber, and Dietmar Maringer. “Anfang gut, alles gut? Eine Empirische Untersuchung über den Fünftageindikator zur Frühprognose auf Aktienmärkten”. In: Financial Markets and Portfolio Management 16.4 (2002), pp.  487–496.  doi:  10.1007/s11408-002-0404-3.  url: https://doi.org/10.1007/s11408-002-0404-3.
  • Dietmar Maringer. “Portfolioselektion bei Transaktionskosten und Ganzzahligkeitsbeschra¨nkungen”. In: Zeitschrift für Betriebswirtschaft 72.11 (2002), pp. 1155–1176.
  • Dietmar Maringer. “Wertpapierselektion mittels Ant Systems”. In: Zeitschrift für Betriebswirtschaft 72.12 (2002), pp. 1221–1240.
  • Christian Keber and Dietmar Maringer. “On Genes, Crystals and Ants: Determining Marginal Diversification Effects with Nature Based Algorithms”. In: 7th International Conference of the Society of Computational Economics. Yale University, 2001.
  • Dietmar Maringer. “Optimizing Portfolios with Ant Systems”. In: International ICSC Congress on Computational Intelligence: Methods and Applications (CIMA ‘2001). University of Wales at Bangor: ICSC Academic Press, Canada and Tue Netherlands, 2001, pp. 288–294.
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