Publications

Maringer, D., Craig, B. R. and Paterlini, S. (2019) “Recreating Banking Networks under Decreasing Fixed Costs”, FRB of Cleveland Working Paper. Federal Reserve Bank of Cleveland (RDB of Cleveland Working Paper, 19). doi: 10.2139/ssrn.3485745.   edoc
Aussenegg, W., Chen, L., Jelic, R. and Maringer, D. (2019) “Time Varying Factors in the Performance of Corporate Bond Indices”. SSRN. doi: 10.2139/ssrn.3303160.   edoc
Gilli, M., Maringer, D. and Schumann, E. (2019) Numerical Methods and Optimization in Finance. London: Academic Press, Elsevier. doi: 10.1016/C2017-0-01621-X.   edoc
Deininger, S. and Maringer, D. (2017) “Channels of Sovereign Risk Spillovers and Investment in the Manufacturing Sector”. WWZ, University of Basel (WWZ Working Papers, 2017).   edoc | Open Access
Maringer, D. and Deininger, S. H. M. (2016) “Selecting and estimating interest rate models with evolutionary methods”, Evolutionary Intelligence. Springer, 9(4), pp. 137–151. doi: 10.1007/s12065-016-0145-2.   edoc
Oesch, C. and Maringer, D. (2016) “Low-latency liquidity inefficiency strategies”, Quantitative finance. Taylor & Francis, 17(5), pp. 717–727. doi: 10.1080/14697688.2016.1242765.   edoc
James, J., Maringer, D., Palada, V. and Serguieva, A. (2015) “Special Issue of Quantitative Finance on ‘Financial Data Analytics’”, Quantitative finance, pp. 1617–1617. doi: 10.1080/14697688.2015.1075707.   edoc
Maringer, D., Pohl, W. and Vanini, P. (2015) “Structured products: performance, costs, and investments”. Zürich: Swiss Finance Institute (White Paper).   edoc
Zhang, J. and Maringer, D. (2015) “Using a Genetic Algorithm to Improve Recurrent Reinforcement Learning for Equity Trading”, Computational Economics. Springer US, 47(4), pp. 551–567. doi: 10.1007/s10614-015-9490-y.   edoc
Lengwiler, Y. and Maringer, D. (2015) “Regulation and contagion of banks”, Journal of Banking Regulation. Palgrave Macmillan, 16(1), pp. 64–71. doi: 10.1057/jbr.2013.20.   edoc
Oesch, C. and Maringer, D. (2015) “A Neutral Mutation Operator in Grammatical Evolution”, in Angelov, P., Atanassov, K. T., Doukovska, L., Hadjiski, M., Jotsov, V., Kacprzyk, J., Kasabov, N., Sotirov, S., Szmidt, E., and Zadrożny, S. (eds.) Intelligent System’2014. Cham, Heidelberg, New York, Dordrecht, London: Springer International Publishing (Advances in Intelligent Systems and Computing), pp. 439–449. doi: 10.1007/978-3-319-11313-5_39.   edoc
Maringer, D. and Kriete-Dodds, S. (2015) “Overconfidence in the Credit Card Market”, in Diehl, M., Alexandrova-Kabadjova, B., Heuver, R., and Martínez-Jaramillo, S. (eds.) Analyzing the Economics of Financial Market Infrastructures. Hershey, PA, USA: IGI Global, pp. 150–168.   edoc
Maringer, D. and Zhang, J. (2014) “Transition Variable Selection for Regime Switching Recurrent Reinforcement Learning”, in Proceedings of the 2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics. London, UK: IEEE (IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr), pp. 407–413. doi: 10.1109/CIFEr.2014.6924102.   edoc
Maringer, D. and Deininger, S. (2014) “Estimating time series models with heuristic methods: the case of economic parity conditions”, in Book of Abstracts: COMPSTAT 2014 - 21st International Conference on Computational Statistics. Geneva: International Association for Statistical Computing, p. 61. Available at: http://web.tecnico.ulisboa.pt/mcasquilho/ist/public/2014compstatBook-of-Abstracts.pdf.   edoc
Zhang, J. and Maringer, D. (2014) “Two Parameter Update Schemes for Recurrent Reinforcement Learning”, in 2014 IEEE Congress on Evolutionary Computation (CEC). Beijing, China : IEEE (IEEE Congress on Evolutionary Computation (CEC), pp. 1449–1453. doi: 10.1109/CEC.2014.6900330.   edoc
Zhang, J. and Maringer, D. (2013) “Indicator selection for daily equity trading with recurrent reinforcement learning”, in GECCO’13. Proceedings of the Genetic and Evolutionary Computation Conference. New York: ACM, pp. 1757–1758. doi: 10.1145/2464576.2480773.   edoc
Oesch, C. and Maringer, D. (2013) “Portfolio optimization under market impact costs”, in 2013 IEEE Congress on Evolutionary Computation (CEC 2013). Cancun, Mexico, 20-23 June 2013: IEEE, pp. 1–7. doi: 10.1109/CEC.2013.6557546.   edoc
Maringer, D. and Ramtohul, T. (2012) “Regime-switching recurrent reinforcement learning in automated trading”, in Brabazon, A., O’Neill, M., and Maringer, D. (eds.) Natural Computing in Computational Finance . Berlin : Springer-Verlag (Studies in Computational Intelligence), pp. 93–121. doi: 10.1007/978-3-642-23336-4_6.   edoc
Maringer, D., Paterlini, S. and Winker, P. (2012) “Editorial: The 3rd Special Issue on Optimization Heuristics in Estimation”, Computational statistics & data analysis. Elsevier, pp. 2963–2964. doi: 10.1016/j.csda.2012.05.006.   edoc
Kriete-Dodds, S. and Maringer, D. (2012) “Subscription markets: an agent-based approach”, in Proceedings of the 8th European Social Simulation Association Conference. Salzburg: Selbstverl. des Fachbereichs Geographie und Geologie der Univ. Salzburg, pp. 179–190.   edoc
Maringer, D. and Ramtohul, T. (2012) “Regime-switching recurrent reinforcement learning for investment decision making”, Computational Management Science. Springer, Vol. 9, H. 1, pp. 89–107.   edoc
Maringer, D. and Ramtohul, T. (2011) “GP-based rebalancing triggers for the CPPI”, in Computational Intelligence for Financial Engineering and Economics (CIFEr), 2011 IEEE Symposium on. Paris: IEEE (Symposium Series on Computational Intelligence). doi: 10.1109/CIFER.2011.5953561.   edoc
Zhang, J. and Maringer, D. (2011) “Selecting pair-copulas with downside risk minimisation”, Journal of Financial Markets and Derivatives. Inderscience Publishers, 2(1-2), pp. 121–148. doi: 10.1504/IJFMD.2011.038532.   edoc
Gilli, M., Maringer, D. and Schumann, E. (2011) Numerical Methods and Optimization in Finance. Amsterdam: Elsevier.   edoc
Lengwiler, Y. and Maringer, D. (2011) “Autonomously Interacting Banks”. Basel: WWZ (WWZ Discussion Papers, 2011). Available at: http://wwz.unibas.ch/uploads/tx_x4epublication/Interacting-Banks_01.pdf.   edoc | Open Access
Chen, X. and Maringer, D. (2011) “Detecting time-variation in corporate bond index returns”, Journal of Banking and Finance. [online] Elsevier Science, Vol. 35, H. 1, pp. 95–103.   edoc
Saks, P. and Maringer, D. (2010) “Evolutionary money management”, in Natural Computing in Computational Finance. New York: Springer (Studies in computational intelligence), pp. 169–190.   edoc
Maringer, D. and Zhang, J. (2010) “Index Mutual Fund Replication”, in Natural Computing in Computational Finance. New York: Springer (Studies in computational intelligence), pp. 109–130.   edoc
Maringer, D. and Zhang, J. (2010) “A clustering application in portfolio management”, in Electronic engineering and computing technology. Dordrecht, pp. 309–321.   edoc
Maringer, D. and Ramtohul, T. (2010) “Threshold recurrent reinforcement learning model for automated trading”, in Applications of Evolutionary Computation. Berlin (Lecture Notes in Computer Science), pp. 212–221. doi: 10.1007/978-3-642-12242-2_22.   edoc
Zhang, Q., Li, H., Maringer, D. and Tsang, E. (2010) “MOEA/D with NBI-like Tchebycheff approach for Portfolio Management”, in 2010 IEEE Congress on Evolutionary Computation (CEC). Piscataway: IEEE. doi: 10.1109/CEC.2010.5586185.   edoc
Maringer, D. (2009) “Kontroverse um das Datamining.”   edoc
Maringer, D. (2009) “Constrained index tracking under loss aversion using differential evolution”, in Natural Computing in Computational Finance. Dordrecht: Springer (Studies in computational intelligence), pp. 7–24.   edoc
di Tollo, G. and Maringer, D. (2009) “Metaheuristics for index tracking”, in Metaheuristics in the service industry. Berlin: Springer (Lecture notes in economics and mathematical systems), pp. 127–154.   edoc
Maringer, D. and Parpas, P. (2009) “Global optimization of higher moments in portfolio selection”, Journal for Global Optimization. Springer, Vol. 23, pp. 219–230.   edoc
Maringer, D. and Winker, P. (2009) “The convergence of estimators based on heuristics : theory and application to a GARCH model”, Computational statistics. Springer, Vol. 24, pp. 533–550.   edoc
Saks, P. and Maringer, D. (2009) “Evolutionary Money Management”, in Applications of Evolutionary Computing. Berlin: Springer (Lecture Notes in Computer Science), pp. 162–171. doi: 10.1007/978-3-642-01129-0_20.   edoc
Zhang, J. and Maringer, D. (2009) “Improving Sharpe Ratios and Stability of Portfolios by Using a Clustering Technique”, in World Congress on Engineering, WCE 2009 : 1 - 3 July, 2009, Imperial College London, London, U.K,. Hong Kong: IAENG, pp. 1–6. Available at: http://www.iaeng.org/publication/WCE2009/WCE2009_pp1-6.pdf.   edoc
Saks, P. and Maringer, D. (2009) “Statistical Arbitrage with Genetic Programming”, in Natural Computing in Computational Finance. Berlin: Springer (Studies in computational intelligence), pp. 9–29. doi: 10.1007/978-3-540-95974-8_2.   edoc
Khuman, A., Maringer, D. and Constantinou, N. (2008) “Constant Proportion Portfolio Insurance (CPPI) : Statistical Properties and Practical Implications”. [Essex]: [University of Essex]. Available at: http://www.essex.ac.uk/ccfea/research/WorkingPapers/2008/23-08_KhumanMaringerConstantinou_CPPI.pdf.   edoc
Maringer, D. (2008) “Heuristic optimization for portfolio management”, IEEE Computational Intelligence Magazine. Institute of Electrical and Electronics Engineers, Vol. 3, H. 4, pp. 31–34.   edoc
Maringer, D. (2008) “Risk preferences and loss aversion in portfolio optimization”, in Computational Methods in Financial Engineering. Heidelberg: Springer, pp. 27–46.   edoc
Gilli, M., Maringer, D. and Winker, P. (2008) “Applications of Heuristics in Finance”, in Handbook on information technology in finance. Berlin: Springer (International handbooks on information systems), pp. 635–654.   edoc
Saks, P. and Maringer, D. (2008) “Genetic Programming in Statistical Arbitrage”, in Applications of Evolutionary Computation : EvoWorkshops 2008. Berlin: Springer (Lecture Notes in Computer Science), pp. 73–82. doi: 10.1007/978-3-540-78761-7_8.   edoc