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Manfred Gilli

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Manfred Gilli & Enrico Schumann, 2010. "A note on ‘good starting values’ in numerical optimisation," Working Papers 044, COMISEF.

    Cited by:

    1. Asif Lakhany & Andrej Pintar & Amber Zhang, 2021. "Calibrating the Nelson-Siegel-Svensson Model by Genetic Algorithm," Papers 2108.01760, arXiv.org.
    2. Ranik Raaen Wahlstrøm & Florentina Paraschiv & Michael Schürle, 2022. "A Comparative Analysis of Parsimonious Yield Curve Models with Focus on the Nelson-Siegel, Svensson and Bliss Versions," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 967-1004, March.

  2. Manfred Gilli & Stefan Große & Enrico Schumann, 2010. "Calibrating the Nelson–Siegel–Svensson model," Working Papers 031, COMISEF.

    Cited by:

    1. Molenaars, Tomas K. & Reinerink, Nick H. & Hemminga, Marcus A., 2015. "Forecasting the yield curve: art or science?," MPRA Paper 61917, University Library of Munich, Germany.
    2. Grochola, Nicolaus, 2023. "The influence of negative interest rates on life insurance companies," ICIR Working Paper Series 53/23, Goethe University Frankfurt, International Center for Insurance Regulation (ICIR).
    3. Agnieszka Konicz & David Pisinger & Alex Weissensteiner, 2015. "Optimal annuity portfolio under inflation risk," Computational Management Science, Springer, vol. 12(3), pages 461-488, July.
    4. Francisco Rivadeneyra, 2012. "The U.S.-Dollar Supranational Zero-Coupon Curve," Discussion Papers 12-5, Bank of Canada.
    5. Asif Lakhany & Andrej Pintar & Amber Zhang, 2021. "Calibrating the Nelson-Siegel-Svensson Model by Genetic Algorithm," Papers 2108.01760, arXiv.org.
    6. Michał Brzoza-Brzezina & Jacek Kotłowski, 2014. "Measuring the natural yield curve," Applied Economics, Taylor & Francis Journals, vol. 46(17), pages 2052-2065, June.
    7. Francisco Ibáñez, 2016. "Calibrating the Dynamic Nelson-Siegel Model: A Practitioner Approach," Working Papers Central Bank of Chile 774, Central Bank of Chile.
    8. Luchelle Soobyah & Daan Steenkamp, 2020. "Term premium and rate expectation estimates from the South African yield curve," Working Papers 9998, South African Reserve Bank.
    9. Eran Raviv, 2013. "Prediction Bias Correction for Dynamic Term Structure Models," Tinbergen Institute Discussion Papers 13-041/III, Tinbergen Institute.
    10. Karahan, Cenk C. & Soykök, Emre, 2023. "On illiquidity of an emerging sovereign bond market," Economic Systems, Elsevier, vol. 47(2).
    11. Molenaars, Tomas K. & Reinerink, Nick H. & Hemminga, Marcus A., 2013. "Forecasting the yield curve - Forecast performance of the dynamic Nelson-Siegel model from 1971 to 2008," MPRA Paper 61862, University Library of Munich, Germany.
    12. Cousin, Areski & Maatouk, Hassan & Rullière, Didier, 2016. "Kriging of financial term-structures," European Journal of Operational Research, Elsevier, vol. 255(2), pages 631-648.
    13. Ibanez, Francisco, 2015. "Calibrating the Dynamic Nelson-Siegel Model: A Practitioner Approach," MPRA Paper 68377, University Library of Munich, Germany.
    14. Maria Teresa Medeiros Garcia & Vítor Hugo Ferreira Carvalho, 2018. "A static approach to the Nelson-Siegel-Svensson model: an application for several negative yield cases," Working Papers REM 2018/35, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    15. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.
    16. Dang-Nguyen, Stéphane & Le Caillec, Jean-Marc & Hillion, Alain, 2014. "The deterministic shift extension and the affine dynamic Nelson–Siegel model," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 402-417.
    17. Virmani, Vineet, 2013. "On the Choice of Optimization Routine in Estimation of Parsimonious Term Structure Models: Results from the Svensson Model," IIMA Working Papers WP2013-01-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    18. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.

  3. Manfred Gilli & Enrico Schumann, 2010. "Calibrating Option Pricing Models with Heuristics," Working Papers 030, COMISEF.

    Cited by:

    1. Cui, Yiran & del Baño Rollin, Sebastian & Germano, Guido, 2017. "Full and fast calibration of the Heston stochastic volatility model," European Journal of Operational Research, Elsevier, vol. 263(2), pages 625-638.
    2. Stefan Haring & Ronald Hochreiter, 2015. "Efficient and robust calibration of the Heston option pricing model for American options using an improved Cuckoo Search Algorithm," Papers 1507.08937, arXiv.org.
    3. Shuaiqiang Liu & Anastasia Borovykh & Lech A. Grzelak & Cornelis W. Oosterlee, 2019. "A neural network-based framework for financial model calibration," Papers 1904.10523, arXiv.org.
    4. Eudald Romo & Luis Ortiz-Gracia, 2021. "SWIFT calibration of the Heston model," Papers 2103.01570, arXiv.org.
    5. Eudald Romo & Luis Ortiz-Gracia, 2021. "SWIFT Calibration of the Heston Model," Mathematics, MDPI, vol. 9(5), pages 1-20, March.
    6. Silvia Centanni, 2011. "Computing option values by pricing kernel with a stochatic volatility model," Working Papers 05/2011, University of Verona, Department of Economics.
    7. Zaineb Mezdoud & Carsten Hartmann & Mohamed Riad Remita & Omar Kebiri, 2021. "$\alpha$-Hypergeometric Uncertain Volatility Models and their Connection to 2BSDEs," Papers 2108.06965, arXiv.org.
    8. Hilmar Gudmundsson & David Vyncke, 2021. "A Generalized Weighted Monte Carlo Calibration Method for Derivative Pricing," Mathematics, MDPI, vol. 9(7), pages 1-22, March.
    9. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.

  4. Manfred GILLI & Enrico SCHUMANN & Gerda CABEJ & Jonela LULA, 2010. "Replicating Hedge Fund Indices with Optimization Heuristics," Swiss Finance Institute Research Paper Series 10-22, Swiss Finance Institute.

    Cited by:

    1. Willi Semmler & Raphaële Chappe, 2011. "The Operation of Hedge Funds: Econometric Evidence, Dynamic Modeling, and Regulatory Perspectives," Palgrave Macmillan Books, in: Greg N. Gregoriou & Razvan Pascalau (ed.), Financial Econometrics Modeling: Derivatives Pricing, Hedge Funds and Term Structure Models, chapter 1, pages 3-34, Palgrave Macmillan.
    2. Mohammad Reza Tavakoli Baghdadabad & Paskalis Glabadanidis, 2013. "Average Drawdown Risk and Capital Asset Pricing," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1-21.

  5. Manfred Gilli & Enrico Schumann, 2009. "Robust regression with optimisation heuristics," Working Papers 011, COMISEF.

    Cited by:

    1. Arne Risa Hole & Hong Il Yoo, 2014. "The use of heuristic optimization algorithms to facilitate maximum simulated likelihood estimation of random parameter logit models," Working Papers 2014021, The University of Sheffield, Department of Economics.

  6. Manfred Gilli & Enrico Schumann, 2009. "Optimal enough?," Working Papers 010, COMISEF.

    Cited by:

    1. Joseph Andria & Giacomo Tollo & Raffaele Pesenti, 2015. "Detection of local tourism systems by threshold accepting," Computational Management Science, Springer, vol. 12(4), pages 559-575, October.
    2. Björn Fastrich & Peter Winker, 2010. "Robust Portfolio Optimization with a Hybrid Heuristic Algorithm," Working Papers 041, COMISEF.
    3. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.
    4. Bjoern Fastrich & Sandra Paterlini & Peter Winker, 2011. "Cardinality versus q-Norm Constraints for Index Tracking," Center for Economic Research (RECent) 056, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    5. Manfred Gilli & Enrico Schumann, 2010. "Calibrating Option Pricing Models with Heuristics," Working Papers 030, COMISEF.
    6. Zhenxi Chen & Thomas Lux, 2018. "Estimation of Sentiment Effects in Financial Markets: A Simulated Method of Moments Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 711-744, October.
    7. D. Blueschke & I. Savin & V. Blueschke-Nikolaeva, 2020. "An Evolutionary Approach to Passive Learning in Optimal Control Problems," Computational Economics, Springer;Society for Computational Economics, vol. 56(3), pages 659-673, October.
    8. Tae-Seok Jang, 2015. "Identification of Social Interaction Effects in Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 207-238, February.

  7. Manfred Gilli & Enrico Schumann, 2009. "Implementing Binomial Trees," Working Papers 008, COMISEF.

    Cited by:

    1. Burcu Aydoğan & Ümit Aksoy & Ömür Uğur, 2018. "On the methods of pricing American options: case study," Annals of Operations Research, Springer, vol. 260(1), pages 79-94, January.

  8. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.

    Cited by:

    1. Gaudard, Ludovic, 2015. "Pumped-storage project: A short to long term investment analysis including climate change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 91-99.
    2. Cui, Yiran & del Baño Rollin, Sebastian & Germano, Guido, 2017. "Full and fast calibration of the Heston stochastic volatility model," European Journal of Operational Research, Elsevier, vol. 263(2), pages 625-638.
    3. Gaudard, Ludovic & Madani, Kaveh, 2019. "Energy storage race: Has the monopoly of pumped-storage in Europe come to an end?," Energy Policy, Elsevier, vol. 126(C), pages 22-29.
    4. Ardia, David & Boudt, Kris & Carl, Peter & Mullen, Katharine M. & Peterson, Brian, 2010. "Differential Evolution (DEoptim) for Non-Convex Portfolio Optimization," MPRA Paper 22135, University Library of Munich, Germany.
    5. Andrea Scozzari & Fabio Tardella & Sandra Paterlini & Thiemo Krink, 2013. "Exact and heuristic approaches for the index tracking problem with UCITS constraints," Annals of Operations Research, Springer, vol. 205(1), pages 235-250, May.
    6. Giuseppe Montesi & Giovanni Papiro & Massimiliano Fazzini & Alessandro Ronga, 2020. "Stochastic Optimization System for Bank Reverse Stress Testing," JRFM, MDPI, vol. 13(8), pages 1-44, August.
    7. Carole Bernard & Massimiliano Caporin & Bertrand Maillet & Xiang Zhang, 2023. "Omega Compatibility: A Meta-analysis," Computational Economics, Springer;Society for Computational Economics, vol. 62(2), pages 493-526, August.
    8. Monica Billio & Massimiliano Caporin & Michele Costola, 2012. "Backward/forward optimal combination of performance measures for equity screening," Working Papers 2012_13, Department of Economics, University of Venice "Ca' Foscari".
    9. Sana Ben Hamida & Wafa Abdelmalek & Fathi Abid, 2020. "Applying Dynamic Training-Subset Selection Methods Using Genetic Programming for Forecasting Implied Volatility," Papers 2007.07207, arXiv.org.
    10. Wei Zhao & Yi Lu & Genfu Feng, 2019. "How Many Agents are Rational in China’s Economy? Evidence from a Heterogeneous Agent-Based New Keynesian Model," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 575-611, August.
    11. Jevtić, Petar & Luciano, Elisa & Vigna, Elena, 2013. "Mortality surface by means of continuous time cohort models," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 122-133.
    12. Eudald Romo & Luis Ortiz-Gracia, 2021. "SWIFT calibration of the Heston model," Papers 2103.01570, arXiv.org.
    13. Filipa Fernandes & Charalampos Stasinakis & Zivile Zekaite, 2019. "Forecasting government bond spreads with heuristic models: evidence from the Eurozone periphery," Annals of Operations Research, Springer, vol. 282(1), pages 87-118, November.
    14. Eudald Romo & Luis Ortiz-Gracia, 2021. "SWIFT Calibration of the Heston Model," Mathematics, MDPI, vol. 9(5), pages 1-20, March.
    15. Konstantinos Konstantaras & Vasilios Sogiakas, 2019. "Is stock liquidity transferred and upgraded in acquisitions? Evidence from liquidity synergies in US freeze-outs," Annals of Operations Research, Springer, vol. 282(1), pages 179-216, November.
    16. G.A. Vijayalakshmi Pai & Thierry Michel, 2012. "Integrated Metaheuristic Optimization Of 130–30 Investment‐Strategy‐Based Long–Short Portfolios," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 19(1), pages 43-74, January.
    17. Doering, Jana & Kizys, Renatas & Juan, Angel A. & Fitó, Àngels & Polat, Onur, 2019. "Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends," Operations Research Perspectives, Elsevier, vol. 6(C).
    18. Leonardo Riegel Sant’Anna & Tiago Pascoal Filomena & Pablo Cristini Guedes & Denis Borenstein, 2017. "Index tracking with controlled number of assets using a hybrid heuristic combining genetic algorithm and non-linear programming," Annals of Operations Research, Springer, vol. 258(2), pages 849-867, November.
    19. T. Gärtner & S. Kaniovski & Y. Kaniovski, 2021. "Numerical estimates of risk factors contingent on credit ratings," Computational Management Science, Springer, vol. 18(4), pages 563-589, October.
    20. Gregory Gadzinski & Markus Schuller & Shabnam Mousavi, 2022. "Long-lasting heuristics principles for efficient investment decisions," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 14(4), pages 570-583, March.
    21. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.

  9. Manfred GILLI & Enrico SCHUMANN, 2009. "An Empirical Analysis of Alternative Portfolio Selection Criteria," Swiss Finance Institute Research Paper Series 09-06, Swiss Finance Institute.

    Cited by:

    1. Manfred Gilli & Enrico Schumann, 2009. "Robust regression with optimisation heuristics," Working Papers 011, COMISEF.
    2. Manfred Gilli & Enrico Schumann, 2009. "Optimal enough?," Working Papers 010, COMISEF.
    3. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.
    4. Mohammad Reza Tavakoli Baghdadabad & Paskalis Glabadanidis, 2013. "Average Drawdown Risk and Capital Asset Pricing," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1-21.
    5. Manfred Gilli & Enrico Schumann & Giacomo di Tollo & Gerda Cabej, 2011. "Constructing 130/30-portfolios with the Omega ratio," Journal of Asset Management, Palgrave Macmillan, vol. 12(2), pages 94-108, June.

  10. Manfred Gilli & Enrico Schumann, 2008. "Distributed Optimisation of a Portfolio's Omega," Swiss Finance Institute Research Paper Series 08-17, Swiss Finance Institute.

    Cited by:

    1. Massimiliano Caporin & Michele Costola & Gregory Mathieu Jannin & Bertrand Maillet, 2016. "On the (Ab)Use of Omega?," Working Papers hal-01697640, HAL.
    2. Abdallah Ben Saida & Jean-luc Prigent, 2018. "On the robustness of portfolio allocation under copula misspecification," Annals of Operations Research, Springer, vol. 262(2), pages 631-652, March.
    3. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.
    4. Zhu, Min, 2013. "Return distribution predictability and its implications for portfolio selection," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 209-223.
    5. Gaustaroba, Gianfranco & Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Linear Programming Models based on Omega Ratio for the Enhanced Index Tracking Problem," MPRA Paper 67097, University Library of Munich, Germany.
    6. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.

  11. Manfred Gilli & Peter Winker, 2008. "Review of Heuristic Optimization Methods in Econometrics," Working Papers 001, COMISEF.

    Cited by:

    1. Florios, Kostas, 2018. "A hyperplanes intersection simulated annealing algorithm for maximum score estimation," Econometrics and Statistics, Elsevier, vol. 8(C), pages 37-55.
    2. Liu, Yu-Hsin, 2011. "Incorporating scatter search and threshold accepting in finding maximum likelihood estimates for the multinomial probit model," European Journal of Operational Research, Elsevier, vol. 211(1), pages 130-138, May.
    3. Ardia, David & Boudt, Kris & Carl, Peter & Mullen, Katharine M. & Peterson, Brian, 2010. "Differential Evolution (DEoptim) for Non-Convex Portfolio Optimization," MPRA Paper 22135, University Library of Munich, Germany.
    4. Peter Winker & Marianna Lyra & Chris Sharpe, 2008. "Least Median of Squares Estimation by Optimization Heuristics with an Application to the CAPM and Multi Factor Models," Working Papers 006, COMISEF.
    5. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.
    6. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    7. Jin Zhang & Dietmar Maringer, 2010. "Asset Allocation under Hierarchical Clustering," Working Papers 036, COMISEF.
    8. El-Shagi, Makram, 2010. "An Evolutionary Algorithm for the Estimation of Threshold Vector Error Correction Models," IWH Discussion Papers 1/2010, Halle Institute for Economic Research (IWH).
    9. Bjoern Fastrich & Sandra Paterlini & Peter Winker, 2011. "Cardinality versus q-Norm Constraints for Index Tracking," Center for Economic Research (RECent) 056, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    10. Jakob Grazzini & Matteo G. Richiardi, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," LABORatorio R. Revelli Working Papers Series 130, LABORatorio R. Revelli, Centre for Employment Studies.
    11. Jakob Grazzini, 2011. "Consistent Estimation of Agent Based Models," LABORatorio R. Revelli Working Papers Series 110, LABORatorio R. Revelli, Centre for Employment Studies.
    12. Maciel, Leandro & Gomide, Fernando & Ballini, Rosangela, 2016. "A differential evolution algorithm for yield curve estimation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 129(C), pages 10-30.
    13. Hazar Altınbaş & Vincenzo Pacelli & Edgardo Sica, 2022. "An Empirical Assessment of the Contagion Determinants in the Euro Area in a Period of Sovereign Debt Risk," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 8(2), pages 339-371, July.
    14. Grazzini Jakob, 2011. "Estimating Micromotives from Macrobehavior," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201111, University of Turin.
    15. Stephen Kinsella, 2012. "Blueprint For An Algorithmic Economics," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 101-111.
    16. Liu, Liwei & Sun, Xiaoru & Chen, Chuxiang & Zhao, Erdong, 2016. "How will auctioning impact on the carbon emission abatement cost of electric power generation sector in China?," Applied Energy, Elsevier, vol. 168(C), pages 594-609.

  12. Manfred GILLI & Enrico SCHUMANN & Giacomo DI TOLLO & Gerda CABEJ, 2008. "Constructing Long/Short Portfolios with the Omega ratio," Swiss Finance Institute Research Paper Series 08-34, Swiss Finance Institute.

    Cited by:

    1. Massimiliano Caporin & Michele Costola & Gregory Mathieu Jannin & Bertrand Maillet, 2016. "On the (Ab)Use of Omega?," Working Papers hal-01697640, HAL.
    2. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.
    3. Eric Benhamou & Beatrice Guez & Nicolas Paris1, 2019. "Omega and Sharpe ratio," Papers 1911.10254, arXiv.org.
    4. Amita Sharma & Sebastian Utz & Aparna Mehra, 2017. "Omega-CVaR portfolio optimization and its worst case analysis," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(2), pages 505-539, March.
    5. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    6. Gaustaroba, Gianfranco & Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Linear Programming Models based on Omega Ratio for the Enhanced Index Tracking Problem," MPRA Paper 67097, University Library of Munich, Germany.
    7. Eduardo Acosta-Gonz�lez & Reinaldo Armas-Herrera & Fernando Fern�ndez-Rodr�guez, 2015. "On the index tracking and the statistical arbitrage choosing the stocks by means of cointegration: the role of stock picking," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1075-1091, June.
    8. Kapsos, Michalis & Christofides, Nicos & Rustem, Berç, 2014. "Worst-case robust Omega ratio," European Journal of Operational Research, Elsevier, vol. 234(2), pages 499-507.
    9. Yu, Jing-Rung & Paul Chiou, Wan-Jiun & Hsin, Yi-Ting & Sheu, Her-Jiun, 2022. "Omega portfolio models with floating return threshold," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 743-758.
    10. Marie Briere & Ariane Szafarz, 2017. "Factor Investing: The Rocky Road from Long-Only to Long-Short," Working Papers CEB 17-013, ULB -- Universite Libre de Bruxelles.

  13. Peter Winker & Manfred Gilli & Vahidin Jeleskovic, 2007. "An Objective Function for Simulation Based Inference on Exchange Rate Data," Swiss Finance Institute Research Paper Series 07-01, Swiss Finance Institute.

    Cited by:

    1. Westerhoff Frank H., 2008. "The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 195-227, April.
    2. Ivan Jericevich & Patrick Chang & Tim Gebbie, 2021. "Simulation and estimation of an agent-based market-model with a matching engine," Papers 2108.07806, arXiv.org, revised Aug 2021.
    3. Vandin, Andrea & Giachini, Daniele & Lamperti, Francesco & Chiaromonte, Francesca, 2022. "Automated and distributed statistical analysis of economic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    4. Jascha-Alexander Koch & Jens Lausen & Moritz Kohlhase, 2021. "Internalizing the externalities of overfunding: an agent-based model approach for analyzing the market dynamics on crowdfunding platforms," Journal of Business Economics, Springer, vol. 91(9), pages 1387-1430, November.
    5. Ivan Jericevich & Murray McKechnie & Tim Gebbie, 2021. "Calibrating an adaptive Farmer-Joshi agent-based model for financial markets," Papers 2104.09863, arXiv.org.
    6. Barde, Sylvain, 2016. "Direct comparison of agent-based models of herding in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 329-353.
    7. Franke, Reiner & Westerhoff, Frank, 2011. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," BERG Working Paper Series 78, Bamberg University, Bamberg Economic Research Group.
    8. Efstathios Panayi & Gareth W. Peters, 2015. "Stochastic simulation framework for the limit order book using liquidity-motivated agents," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(02), pages 1-52.
    9. LeBaron Blake & Winker Peter, 2008. "Introduction to the Special Issue on Agent-Based Models for Economic Policy Advice," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 141-148, April.
    10. Andrea Vandin & Daniele Giachini & Francesco Lamperti & Francesca Chiaromonte, 2021. "Automated and Distributed Statistical Analysis of Economic Agent-Based Models," Papers 2102.05405, arXiv.org, revised Nov 2023.
    11. Francesco Lamperti & Andrea Roventini & Amir Sani, 2017. "Agent-Based Model Calibration using Machine Learning Surrogates," Working Papers hal-03458875, HAL.
    12. Fischer, Thomas & Riedler, Jesper, 2012. "Prices, Debt and Market Structure in an Agent-Based Model of the Financial Market," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 58512, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    13. Matthew Dicks & Andrew Paskaramoorthy & Tim Gebbie, 2023. "Many learning agents interacting with an agent-based market model," Papers 2303.07393, arXiv.org, revised Nov 2023.
    14. Donovan Platt & Tim Gebbie, 2016. "The Problem of Calibrating an Agent-Based Model of High-Frequency Trading," Papers 1606.01495, arXiv.org, revised Mar 2017.
    15. Dinghai Xu & Jingru Ji & Donghua Wang, 2018. "Modelling the spreading process of extreme risks via a simple agent-based model: Evidence from the China stock market," Working Papers 1806, University of Waterloo, Department of Economics, revised 09 Jan 2018.
    16. Zila, Eric & Kukacka, Jiri, 2023. "Moment set selection for the SMM using simple machine learning," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 366-391.
    17. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 277-293, October.
    18. Emanuele Ciola & Edoardo Gaffeo & Mauro Gallegati, 2021. "Search for Profits and Business Fluctuations: How Banks' Behaviour Explain Cycles?," Working Papers 450, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    19. Zhang, Jinyu & Zhang, Qiaosen & Li, Yong & Wang, Qianchao, 2023. "Sequential Bayesian inference for agent-based models with application to the Chinese business cycle," Economic Modelling, Elsevier, vol. 126(C).
    20. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.
    21. Francesco Lamperti, 2016. "Empirical Validation of Simulated Models through the GSL-div: an Illustrative Application," LEM Papers Series 2016/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    22. Radu T. Pruna & Maria Polukarov & Nicholas R. Jennings, 2020. "Loss aversion in an agent-based asset pricing model," Quantitative Finance, Taylor & Francis Journals, vol. 20(2), pages 275-290, February.
    23. Jacob Grazzini & Matteo Richiardi & Lisa Sella, 2012. "Indirect estimation of agent-based models.An application to a simple diffusion model," LABORatorio R. Revelli Working Papers Series 118, LABORatorio R. Revelli, Centre for Employment Studies.
    24. Chen, Zhenxi & Zheng, Huanhuan, 2022. "Herding in the Chinese and US stock markets: Evidence from a micro-founded approach," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 597-604.
    25. Westerhoff, Frank, 2009. "A simple agent-based financial market model: Direct interactions and comparisons of trading profits," BERG Working Paper Series 61, Bamberg University, Bamberg Economic Research Group.
    26. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    27. Blaurock, Ivonne & Schmitt, Noemi & Westerhoff, Frank, 2018. "Market entry waves and volatility outbursts in stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 19-37.
    28. Donovan Platt & Tim Gebbie, 2016. "Can Agent-Based Models Probe Market Microstructure?," Papers 1611.08510, arXiv.org, revised Aug 2017.
    29. Giovanni Dosi & Andrea Roventini, 2019. "More is different ... and complex! the case for agent-based macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 1-37, March.
    30. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    31. Ciola, Emanuele & Gaffeo, Edoardo & Gallegati, Mauro, 2022. "Search for profits and business fluctuations: How does banks’ behaviour explain cycles?," Journal of Economic Dynamics and Control, Elsevier, vol. 135(C).
    32. Schmitt, Noemi & Westerhoff, Frank, 2016. "Heterogeneity, spontaneous coordination and extreme events within large-scale and small-scale agent-based financial market models," BERG Working Paper Series 111, Bamberg University, Bamberg Economic Research Group.
    33. Jakob Grazzini & Matteo G. Richiardi, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," LABORatorio R. Revelli Working Papers Series 130, LABORatorio R. Revelli, Centre for Employment Studies.
    34. Demary, Markus, 2009. "Transaction taxes and traders with heterogeneous investment horizons in an agent-based financial market model," Economics Discussion Papers 2009-47, Kiel Institute for the World Economy (IfW Kiel).
    35. Seri, Raffaello & Martinoli, Mario & Secchi, Davide & Centorrino, Samuele, 2021. "Model calibration and validation via confidence sets," Econometrics and Statistics, Elsevier, vol. 20(C), pages 62-86.
    36. Mario Martinoli & Alessio Moneta & Gianluca Pallante, 2022. "Calibration and Validation of Macroeconomic Simulation Models by Statistical Causal Search," LEM Papers Series 2022/33, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    37. Alexandru Mandes & Peter Winker, 2015. "Complexity and Model Comparison in Agent Based Modeling of Financial Markets," MAGKS Papers on Economics 201528, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    38. Giorgio Fagiolo & Andrea Roventini, 2016. "Macroeconomic Policy in DGSE and Agent-Based Models Redux: New Developments and Challenges Ahead," Sciences Po publications info:hdl:2441/dcditnq6282, Sciences Po.
    39. Jakob Grazzini, 2011. "Consistent Estimation of Agent Based Models," LABORatorio R. Revelli Working Papers Series 110, LABORatorio R. Revelli, Centre for Employment Studies.
    40. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Working Papers hal-04141079, HAL.
    41. Grosche, Stephanie & Heckelei, Thomas, 2014. "Price dynamics and financialization effects in corn futures markets with heterogeneous traders," Discussion Papers 172077, University of Bonn, Institute for Food and Resource Economics.
    42. Cafferata, Alessia & Tramontana, Fabio, 2022. "Disposition Effect and its outcome on endogenous price fluctuations," MPRA Paper 113904, University Library of Munich, Germany.
    43. Lamperti, Francesco, 2018. "An information theoretic criterion for empirical validation of simulation models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 83-106.
    44. Kukacka, Jiri & Barunik, Jozef, 2016. "Estimation of financial agent-based models with simulated maximum likelihood," FinMaP-Working Papers 63, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    45. Juana Castro & Stefan Drews & Filippos Exadaktylos & Joël Foramitti & Franziska Klein & Théo Konc & Ivan Savin & Jeroen van den Bergh, 2020. "A review of agent‐based modeling of climate‐energy policy," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(4), July.
    46. Franke, Reiner, 2009. "Applying the method of simulated moments to estimate a small agent-based asset pricing model," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 804-815, December.
    47. Noemi Schmitt & Frank Westerhoff, 2017. "Herding behaviour and volatility clustering in financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1187-1203, August.
    48. Nan Lu, 2018. "La modélisation de l’indice CAC 40 avec un modèle basé agent," Erudite Ph.D Dissertations, Erudite, number ph18-02 edited by François Legendre, December.
    49. Giorgio Fagiolo & Andrea Roventini, 2016. "Macroeconomic Policy in DGSE and Agent-Based Models Redux," Working Papers hal-03459348, HAL.
    50. Donovan Platt, 2019. "A Comparison of Economic Agent-Based Model Calibration Methods," Papers 1902.05938, arXiv.org.
    51. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.
    52. Platt, Donovan & Gebbie, Tim, 2018. "Can agent-based models probe market microstructure?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1092-1106.
    53. Zhenxi Chen & Thomas Lux, 2018. "Estimation of Sentiment Effects in Financial Markets: A Simulated Method of Moments Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 711-744, October.
    54. Efstathios Panayi & Gareth Peters, 2015. "Stochastic simulation framework for the Limit Order Book using liquidity motivated agents," Papers 1501.02447, arXiv.org, revised Jan 2015.
    55. Elizabeth Jane Casabianca & Alessia Lo Turco & Daniela Maggioni, 2021. "Migration And The Structure Of Manufacturing Production. A View From Italian Provinces," Working Papers 448, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    56. Francesco Lamperti, 2018. "Empirical validation of simulated models through the GSL-div: an illustrative application," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 143-171, April.
    57. Markus Demary, 2011. "Transaction taxes, greed and risk aversion in an agent-based financial market model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(1), pages 1-28, May.
    58. Haber Gottfried, 2008. "Monetary and Fiscal Policy Analysis With an Agent-Based Macroeconomic Model," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 276-295, April.
    59. Zhenxi Chen & Jing Ru, 2021. "Herding and capitalization size in the Chinese stock market: a micro-foundation evidence," Empirical Economics, Springer, vol. 60(4), pages 1895-1911, April.
    60. Radu T. Pruna & Maria Polukarov & Nicholas R. Jennings, 2016. "A new structural stochastic volatility model of asset pricing and its stylized facts," Papers 1604.08824, arXiv.org.
    61. Tae-Seok Jang, 2015. "Identification of Social Interaction Effects in Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 207-238, February.

  14. Ilir Roko & Manfred Gilli, 2006. "Using Economic and Financial Information for Stock Selection," Swiss Finance Institute Research Paper Series 06-21, Swiss Finance Institute.

    Cited by:

    1. Peter Winker & Marianna Lyra & Chris Sharpe, 2008. "Least Median of Squares Estimation by Optimization Heuristics with an Application to the CAPM and Multi Factor Models," Working Papers 006, COMISEF.
    2. Piotr Arendarski, 2012. "Tactical allocation in falling stocks: Combining momentum and solvency ratio signals," Working Papers 2012-01, Faculty of Economic Sciences, University of Warsaw.
    3. Björn Fastrich & Peter Winker, 2010. "Robust Portfolio Optimization with a Hybrid Heuristic Algorithm," Working Papers 041, COMISEF.
    4. I-Cheng Yeh, 2023. "Synergy frontier of multi-factor stock selection model," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 445-480, March.
    5. I-Cheng Yeh & Yi-Cheng Liu, 2020. "Discovering optimal weights in weighted-scoring stock-picking models: a mixture design approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-28, December.

  15. M. Gilli & E. Kellezi & H. Hysi, 2006. "A Data-Driven Optimization Heuristic for Downside Risk Minimization," Computing in Economics and Finance 2006 355, Society for Computational Economics.

    Cited by:

    1. Jin Zhang & Dietmar Maringer, 2016. "Using a Genetic Algorithm to Improve Recurrent Reinforcement Learning for Equity Trading," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 551-567, April.
    2. Gaudard, Ludovic & Madani, Kaveh, 2019. "Energy storage race: Has the monopoly of pumped-storage in Europe come to an end?," Energy Policy, Elsevier, vol. 126(C), pages 22-29.
    3. Thiemo Krink & Sandra Paterlini, 2011. "Multiobjective optimization using differential evolution for real-world portfolio optimization," Computational Management Science, Springer, vol. 8(1), pages 157-179, April.
    4. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00375765, HAL.
    5. Manfred Gilli & Enrico Schumann, 2009. "Robust regression with optimisation heuristics," Working Papers 011, COMISEF.
    6. Harris, Richard D.F. & Mazibas, Murat, 2013. "Dynamic hedge fund portfolio construction: A semi-parametric approach," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 139-149.
    7. Oleksandr Romanko & Helmut Mausser, 2016. "Robust scenario-based value-at-risk optimization," Annals of Operations Research, Springer, vol. 237(1), pages 203-218, February.
    8. Iwona Konarzewska, 2008. "On measuring the sensitivity of the optimal portfolio allocation," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 18(2), pages 55-73.
    9. Manfred Gilli & Enrico Schumann, 2009. "Optimal enough?," Working Papers 010, COMISEF.
    10. Thapar, Rishi & Minsky, Bernard & Obradovic, M & Tang, Qi, 2009. "Applying a global optimisation algorithm to Fund of Hedge Funds portfolio optimisation," MPRA Paper 17099, University Library of Munich, Germany.
    11. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.
    12. Yuichi Takano & Jun-ya Gotoh, 2010. "α-Conservative approximation for probabilistically constrained convex programs," Computational Optimization and Applications, Springer, vol. 46(1), pages 113-133, May.
    13. Zhu, Min, 2013. "Return distribution predictability and its implications for portfolio selection," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 209-223.
    14. Marco Di Francesco, 2021. "Portfolio optimization under solvency II: a multi-objective approach incorporating market views and real-world constraints," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 269-294, June.
    15. Ludovic Gaudard & Jeannette Gabbi & Andreas Bauder & Franco Romerio, 2016. "Long-term Uncertainty of Hydropower Revenue Due to Climate Change and Electricity Prices," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1325-1343, March.
    16. Babat, Onur & Vera, Juan C. & Zuluaga, Luis F., 2018. "Computing near-optimal Value-at-Risk portfolios using integer programming techniques," European Journal of Operational Research, Elsevier, vol. 266(1), pages 304-315.
    17. Lwin, Khin T. & Qu, Rong & MacCarthy, Bart L., 2017. "Mean-VaR portfolio optimization: A nonparametric approach," European Journal of Operational Research, Elsevier, vol. 260(2), pages 751-766.
    18. David Vidal-Tomás & Ana M. Ibáñez & José E. Farinós, 2021. "The Effect of the Launch of Bitcoin Futures on the Cryptocurrency Market: An Economic Efficiency Approach," Mathematics, MDPI, vol. 9(4), pages 1-14, February.
    19. Ludovic Gaudard & Jeannette Gabbi & Andreas Bauder & Franco Romerio, 2016. "Long-term Uncertainty of Hydropower Revenue Due to Climate Change and Electricity Prices," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1325-1343, March.
    20. Adolfo Hilario-Caballero & Ana Garcia-Bernabeu & Jose Vicente Salcedo & Marisa Vercher, 2020. "Tri-Criterion Model for Constructing Low-Carbon Mutual Fund Portfolios: A Preference-Based Multi-Objective Genetic Algorithm Approach," IJERPH, MDPI, vol. 17(17), pages 1-15, August.
    21. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," Post-Print halshs-00375765, HAL.
    22. Jin Zhang & Dietmar Maringer, 2010. "Asset Pair-Copula Selection with Downside Risk Minimization," Working Papers 037, COMISEF.
    23. Konstantinos Anagnostopoulos & Georgios Mamanis, 2011. "Multiobjective evolutionary algorithms for complex portfolio optimization problems," Computational Management Science, Springer, vol. 8(3), pages 259-279, August.
    24. Travkin, A., 2015. "Estimating Pair-Copula Constructions Using Empirical Tail Dependence Functions: an Application to Russian Stock Market," Journal of the New Economic Association, New Economic Association, vol. 25(1), pages 39-55.
    25. Oleksandr Romanko & Helmut Mausser, 2016. "Robust scenario-based value-at-risk optimization," Annals of Operations Research, Springer, vol. 237(1), pages 203-218, February.
    26. J. Baixauli-Soler & Eva Alfaro-Cid & Matilde Fernandez-Blanco, 2011. "Mean-VaR Portfolio Selection Under Real Constraints," Computational Economics, Springer;Society for Computational Economics, vol. 37(2), pages 113-131, February.
    27. A. Garcia-Bernabeu & J. V. Salcedo & A. Hilario & D. Pla-Santamaria & Juan M. Herrero, 2019. "Computing the Mean-Variance-Sustainability Nondominated Surface by ev-MOGA," Complexity, Hindawi, vol. 2019, pages 1-12, December.
    28. Thiemo Krink & Sandra Paterlini, 2008. "Differential Evolution for Multiobjective Portfolio Optimization," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0007, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    29. Gianni Filograsso & Giacomo Tollo, 2023. "Adaptive evolutionary algorithms for portfolio selection problems," Computational Management Science, Springer, vol. 20(1), pages 1-38, December.
    30. Guan, Guohui & Liang, Zongxia & Xia, Yi, 2023. "Optimal management of DC pension fund under the relative performance ratio and VaR constraint," European Journal of Operational Research, Elsevier, vol. 305(2), pages 868-886.
    31. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.
    32. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," PSE-Ecole d'économie de Paris (Postprint) halshs-00375765, HAL.
    33. Massimiliano Kaucic & Mojtaba Moradi & Mohmmad Mirzazadeh, 2019. "Portfolio optimization by improved NSGA-II and SPEA 2 based on different risk measures," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-28, December.
    34. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    35. Yu, Jing-Rung & Paul Chiou, Wan-Jiun & Hsin, Yi-Ting & Sheu, Her-Jiun, 2022. "Omega portfolio models with floating return threshold," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 743-758.
    36. M. Schyns & Y. Crama & G. Hübner, 2010. "Optimal selection of a portfolio of options under Value-at-Risk constraints: a scenario approach," Annals of Operations Research, Springer, vol. 181(1), pages 683-708, December.

  16. Winmker, P. & Gilli, M., 2001. "Indirect Estimation of the Parameters of Agent Based Models of Financial Markets," Papers 38, Manitoba - Department of Economics.

    Cited by:

    1. Peter Boswijk & Cars H. Hommes & Sebastiano Manzan, 2005. "Behavioral Heterogeneity in Stock Prices," Tinbergen Institute Discussion Papers 05-052/1, Tinbergen Institute.
    2. Cars Hommes & Florian Wagener, 2008. "Complex Evolutionary Systems in Behavioral Finance," Tinbergen Institute Discussion Papers 08-054/1, Tinbergen Institute.
    3. Monira Essa Aloud, 2016. "Profitability of Directional Change Based Trading Strategies: The Case of Saudi Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 87-95.
    4. Baur, Dirk G. & Glover, Kristoffer J., 2014. "Heterogeneous expectations in the gold market: Specification and estimation," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 116-133.
    5. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    6. Xue-Zhong He & Youwei Li, 2015. "Testing of a Market Fraction Model and Power-Law Behaviour in the Dax 30," Research Paper Series 354, Quantitative Finance Research Centre, University of Technology, Sydney.
    7. Amilon, Henrik, 2008. "Estimation of an adaptive stock market model with heterogeneous agents," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 342-362, March.
    8. Hommes, C.H., 2005. "Heterogeneous Agent Models in Economics and Finance, In: Handbook of Computational Economics II: Agent-Based Computational Economics, edited by Leigh Tesfatsion and Ken Judd , Elsevier, Amsterdam 2006," CeNDEF Working Papers 05-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    9. Sylvain Barde & Sander Van Der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," Sciences Po publications 17/12, Sciences Po.
    10. Gilli, M. & Winker, P., 2003. "A global optimization heuristic for estimating agent based models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 299-312, March.
    11. Pasquale Cirillo & Carlo Bianchi & Mauro Gallegati & Pietro Vagliasindi, 2006. "Validating and Calibrating Agent-based Models: a Case Study," Computing in Economics and Finance 2006 277, Society for Computational Economics.
    12. Jacob Grazzini & Matteo Richiardi & Lisa Sella, 2012. "Indirect estimation of agent-based models.An application to a simple diffusion model," LABORatorio R. Revelli Working Papers Series 118, LABORatorio R. Revelli, Centre for Employment Studies.
    13. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    14. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
    15. Jakob Grazzini & Matteo G. Richiardi, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," LABORatorio R. Revelli Working Papers Series 130, LABORatorio R. Revelli, Centre for Employment Studies.
    16. Todd Feldman & Shuming Liu, 2018. "A New Predictive Measure Using Agent-Based Behavioral Finance," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 941-959, April.
    17. Seri, Raffaello & Martinoli, Mario & Secchi, Davide & Centorrino, Samuele, 2021. "Model calibration and validation via confidence sets," Econometrics and Statistics, Elsevier, vol. 20(C), pages 62-86.
    18. Xue-Zhong He & Youwei Li, 2017. "The adaptiveness in stock markets: testing the stylized facts in the DAX 30," Journal of Evolutionary Economics, Springer, vol. 27(5), pages 1071-1094, November.
    19. Witte, Björn-Christopher, 2011. "Removing systematic patterns in returns in a financial market model by artificially intelligent traders," BERG Working Paper Series 82, Bamberg University, Bamberg Economic Research Group.
    20. Recchioni, Maria Cristina & Tedeschi, Gabriele & Gallegati, Mauro, 2014. "A calibration procedure for analyzing stock price dynamics in an agent-based framework," FinMaP-Working Papers 26, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    21. Thorsten Lehnert & Bart Frijns & Remco Zwinkels, 2009. "A Volatility Targeting GARCH model with Time-Varying Coefficients," LSF Research Working Paper Series 09-08, Luxembourg School of Finance, University of Luxembourg.
    22. Kampouridis, Michael & Chen, Shu-Heng & Tsang, Edward, 2012. "Market fraction hypothesis: A proposed test," International Review of Financial Analysis, Elsevier, vol. 23(C), pages 41-54.
    23. Yanqiao Zheng & Xiaobing Zhao & Xiaoqi Zhang & Xinyue Ye & Qiwen Dai, 2019. "Mining the Hidden Link Structure from Distribution Flows for a Spatial Social Network," Complexity, Hindawi, vol. 2019, pages 1-17, May.
    24. Kukacka, Jiri & Barunik, Jozef, 2016. "Estimation of financial agent-based models with simulated maximum likelihood," FinMaP-Working Papers 63, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    25. Juana Castro & Stefan Drews & Filippos Exadaktylos & Joël Foramitti & Franziska Klein & Théo Konc & Ivan Savin & Jeroen van den Bergh, 2020. "A review of agent‐based modeling of climate‐energy policy," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(4), July.
    26. Saskia ter Ellen & Willem F. C. Verschoor, 2018. "Heterogeneous Beliefs and Asset Price Dynamics: A Survey of Recent Evidence," Dynamic Modeling and Econometrics in Economics and Finance, in: Fredj Jawadi (ed.), Uncertainty, Expectations and Asset Price Dynamics, pages 53-79, Springer.
    27. de Jong, Eelke & Verschoor, Willem F.C. & Zwinkels, Remco C.J., 2009. "Behavioural heterogeneity and shift-contagion: Evidence from the Asian crisis," Journal of Economic Dynamics and Control, Elsevier, vol. 33(11), pages 1929-1944, November.
    28. Radu T. Pruna & Maria Polukarov & Nicholas R. Jennings, 2016. "A new structural stochastic volatility model of asset pricing and its stylized facts," Papers 1604.08824, arXiv.org.
    29. de Jong, Eelke & Verschoor, Willem F.C. & Zwinkels, Remco C.J., 2010. "Heterogeneity of agents and exchange rate dynamics: Evidence from the EMS," Journal of International Money and Finance, Elsevier, vol. 29(8), pages 1652-1669, December.
    30. Saskia ter Ellen & Willem F.C. Verschoor, 2017. "Heterogeneous beliefs and asset price dynamics: a survey of recent evidence," Working Paper 2017/22, Norges Bank.

  17. Manfred Gilli and Evis Kellezi, 2001. "Threshold Accepting for Index Tracking," Computing in Economics and Finance 2001 72, Society for Computational Economics.

    Cited by:

    1. Nikos S. Thomaidis & Timotheos Angelidis & Vassilios Vassiliadis & Georgios Dounias, 2009. "Active Portfolio Management With Cardinality Constraints: An Application Of Particle Swarm Optimization," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 535-555.
    2. Rubén Ruiz-Torrubiano & Alberto Suárez, 2009. "A hybrid optimization approach to index tracking," Annals of Operations Research, Springer, vol. 166(1), pages 57-71, February.

  18. Manfred Gilli, Evis Kellezi, 2000. "Heuristic Approaches For Portfolio Optimization," Computing in Economics and Finance 2000 289, Society for Computational Economics.

    Cited by:

    1. Derya TURFAN & Cagdas Hakan ALADAG & Ozgur YENIAY, 2012. "A New Genetic Algorithm To Solve Knapsack Problems," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 1(2), pages 40-47, DECEMBER.
    2. Adam, Alexandre & Houkari, Mohamed & Laurent, Jean-Paul, 2008. "Spectral risk measures and portfolio selection," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1870-1882, September.

  19. Evis Këllezi & Manfred Gilli, 2000. "Extreme Value Theory for Tail-Related Risk Measures," FAME Research Paper Series rp18, International Center for Financial Asset Management and Engineering.

    Cited by:

    1. Gupta, Anurag & Liang, Bing, 2005. "Do hedge funds have enough capital? A value-at-risk approach," Journal of Financial Economics, Elsevier, vol. 77(1), pages 219-253, July.
    2. Byström, Hans, 2001. "Extreme Value Theory and Extremely Large Electricity Price Changes," Working Papers 2001:19, Lund University, Department of Economics.
    3. Cristina Sommacampagna, 2002. "Stima del Value-at-Risk con il Filtro di Kalman," Rivista di Politica Economica, SIPI Spa, vol. 92(6), pages 147-174, November-.
    4. Ioan TalpoÅŸ & Cosmin Enache, 2007. "Public Finance And Extreme Events," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(9), pages 1-3.
    5. Byström, Hans, 2001. "Managing Extreme Risks in Tranquil and Volatile Markets Using Conditional Extreme Value Theory," Working Papers 2001:18, Lund University, Department of Economics.
    6. Lampros Kalyvas & Athanasios Sfetsos, 2006. "Does The Application Of Innovative Internal Models Diminish Regulatory Capital?," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 217-226.
    7. Haque, Mahfuzul & Varela, Oscar & Hassan, M. Kabir, 2007. "Safety-first and extreme value bilateral U.S.-Mexican portfolio optimization around the peso crisis and NAFTA in 1994," The Quarterly Review of Economics and Finance, Elsevier, vol. 47(3), pages 449-469, July.
    8. Novak, S.Y. & Beirlant, J., 2006. "The magnitude of a market crash can be predicted," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 453-462, February.
    9. Li, Wenwei & Hommel, Ulrich & Paterlini, Sandra, 2018. "Network topology and systemic risk: Evidence from the Euro Stoxx market," Finance Research Letters, Elsevier, vol. 27(C), pages 105-112.

  20. Manfred Gilli & Evis Këllezi, 2000. "A Heuristic Approach to Portfolio Optimization," FAME Research Paper Series rp20, International Center for Financial Asset Management and Engineering.

    Cited by:

    1. Ralph Steuer & Yue Qi & Markus Hirschberger, 2007. "Suitable-portfolio investors, nondominated frontier sensitivity, and the effect of multiple objectives on standard portfolio selection," Annals of Operations Research, Springer, vol. 152(1), pages 297-317, July.

  21. Manfred Gilli & Giorgio Pauletto, "undated". "An Application of Nonstationary Iterative Methods for Solving a Multi-Country Model with Rational Expectations," Computing in Economics and Finance 1996 _045, Society for Computational Economics.

    Cited by:

    1. Peter Hollinger, "undated". "The Stacked-Time Simulator in TROLL: A Robust Algorithm for Solving Forward-Looking Models," Computing in Economics and Finance 1996 _026, Society for Computational Economics.

Articles

  1. Ludovic Gaudard & Manfred Gilli & Franco Romerio, 2013. "Climate Change Impacts on Hydropower Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5143-5156, December.

    Cited by:

    1. Gaudard, Ludovic, 2015. "Pumped-storage project: A short to long term investment analysis including climate change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 91-99.
    2. Asmadi Ahmad & Ahmed El-Shafie & Siti Razali & Zawawi Mohamad, 2014. "Reservoir Optimization in Water Resources: a Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3391-3405, September.
    3. Gaudard, Ludovic & Madani, Kaveh, 2019. "Energy storage race: Has the monopoly of pumped-storage in Europe come to an end?," Energy Policy, Elsevier, vol. 126(C), pages 22-29.
    4. Kałuża, Tomasz & Hämmerling, Mateusz & Zawadzki, Paweł & Czekała, Wojciech & Kasperek, Robert & Sojka, Mariusz & Mokwa, Marian & Ptak, Mariusz & Szkudlarek, Arkadiusz & Czechlowski, Mirosław & Dach, J, 2022. "The hydropower sector in Poland: Barriers and the outlook for the future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    5. Stucchi, Leonardo & Bocchiola, Daniele & Simoni, Camilla & Ambrosini, Stefano Romano & Bianchi, Alberto & Rosso, Renzo, 2023. "Future hydropower production under the framework of NextGenerationEU: The case of Santa Giustina reservoir in Italian Alps," Renewable Energy, Elsevier, vol. 215(C).
    6. Patro, Epari Ritesh & De Michele, Carlo & Avanzi, Francesco, 2018. "Future perspectives of run-of-the-river hydropower and the impact of glaciers’ shrinkage: The case of Italian Alps," Applied Energy, Elsevier, vol. 231(C), pages 699-713.
    7. Werner Hediger, 2018. "The Corporate Social Responsibility of Hydropower Companies in Alpine Regions—Theory and Policy Recommendations," Sustainability, MDPI, vol. 10(10), pages 1-20, October.
    8. Julian David Hunt & Giacomo Falchetta & Behnam Zakeri & Andreas Nascimento & Paulo Smith Schneider & Natália Assis Brasil Weber & André Luiz Amarante Mesquita & Paulo Sergio Franco Barbosa & Nivalde J, 2020. "Hydropower impact on the river flow of a humid regional climate," Climatic Change, Springer, vol. 163(1), pages 379-393, November.
    9. Mariusz Adynkiewicz-Piragas & Bartłomiej Miszuk, 2020. "Risk Analysis Related to Impact of Climate Change on Water Resources and Hydropower Production in the Lusatian Neisse River Basin," Sustainability, MDPI, vol. 12(12), pages 1-23, June.
    10. Gaudard, Ludovic & Avanzi, Francesco & De Michele, Carlo, 2018. "Seasonal aspects of the energy-water nexus: The case of a run-of-the-river hydropower plant," Applied Energy, Elsevier, vol. 210(C), pages 604-612.
    11. Didier Haguma & Robert Leconte, 2018. "Long-Term Planning of Water Systems in the Context of Climate Non-Stationarity with Deterministic and Stochastic Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1725-1739, March.
    12. Edson Bortoni & Zulcy de Souza & Augusto Viana & Helcio Villa-Nova & Ângelo Rezek & Luciano Pinto & Roberto Siniscalchi & Rafael Bragança & José Bernardes, 2019. "The Benefits of Variable Speed Operation in Hydropower Plants Driven by Francis Turbines," Energies, MDPI, vol. 12(19), pages 1-20, September.
    13. Ludovic Gaudard & Franco Romerio, 2020. "A Conceptual Framework to Classify and Manage Risk, Uncertainty and Ambiguity: An Application to Energy Policy," Energies, MDPI, vol. 13(6), pages 1-22, March.
    14. Bo Su & Cunde Xiao & Deliang Chen & Dahe Qin & Yongjian Ding, 2019. "Cryosphere Services and Human Well-Being," Sustainability, MDPI, vol. 11(16), pages 1-23, August.
    15. Baptiste François & Benoit Hingray & Marco Borga & Davide Zoccatelli & Casey Brown & Jean-Dominique Creutin, 2018. "Impact of Climate Change on Combined Solar and Run-of-River Power in Northern Italy," Energies, MDPI, vol. 11(2), pages 1-22, January.
    16. Liu Yuan & Jianzhong Zhou & Chunlong Li & Mengfei Xie & Li Mo, 2016. "Benefit and Risk Balance Optimization for Stochastic Hydropower Scheduling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3347-3361, August.
    17. Lucas, Edimilson Costa & Mendes-Da-Silva, Wesley, 2018. "Impact of climate on firm value: Evidence from the electric power industry in Brazil," Energy, Elsevier, vol. 153(C), pages 359-368.
    18. Hunt, Julian David & Nascimento, Andreas & Caten, Carla Schwengber ten & Tomé, Fernanda Munari Caputo & Schneider, Paulo Smith & Thomazoni, André Luis Ribeiro & Castro, Nivalde José de & Brandão, Robe, 2022. "Energy crisis in Brazil: Impact of hydropower reservoir level on the river flow," Energy, Elsevier, vol. 239(PA).
    19. B. François & B. Hingray & J. Creutin & F. Hendrickx, 2015. "Estimating Water System Performance Under Climate Change: Influence of the Management Strategy Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4903-4918, October.

  2. Manfred Gilli & Enrico Schumann, 2012. "Heuristic optimisation in financial modelling," Annals of Operations Research, Springer, vol. 193(1), pages 129-158, March.
    See citations under working paper version above.
  3. Gilli, Manfred & Schumann, Enrico, 2010. "Optimization in financial engineering - an essay on 'good' solutions and misplaced exactitude," Journal of Financial Transformation, Capco Institute, vol. 28, pages 117-122.

    Cited by:

    1. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.
    2. Manfred Gilli & Enrico Schumann, 2010. "Calibrating Option Pricing Models with Heuristics," Working Papers 030, COMISEF.

  4. I. Roko & M. Gilli, 2008. "Using economic and financial information for stock selection," Computational Management Science, Springer, vol. 5(4), pages 317-335, October.
    See citations under working paper version above.
  5. Gatu, Cristian & Kontoghiorghes, Erricos J. & Gilli, Manfred & Winker, Peter, 2008. "An efficient branch-and-bound strategy for subset vector autoregressive model selection," Journal of Economic Dynamics and Control, Elsevier, vol. 32(6), pages 1949-1963, June.

    Cited by:

    1. Wagner Martin & Hlouskova Jaroslava, 2015. "Growth Regressions, Principal Components Augmented Regressions and Frequentist Model Averaging," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(6), pages 642-662, December.
    2. Sachs, Andreas & Schleer, Frauke, 2019. "Labor Market Performance in OECD Countries: The Role of Institutional Interdependencies," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 33(3), pages 431-454.
    3. Shafik, Nivien & Tutz, Gerhard, 2009. "Boosting nonlinear additive autoregressive time series," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2453-2464, May.
    4. Ivan Savin & Peter Winker, 2012. "Heuristic Optimization Methods for Dynamic Panel Data Model Selection: Application on the Russian Innovative Performance," Computational Economics, Springer;Society for Computational Economics, vol. 39(4), pages 337-363, April.
    5. Gatu, Cristian & Yanev, Petko I. & Kontoghiorghes, Erricos J., 2007. "A graph approach to generate all possible regression submodels," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 799-815, October.
    6. Fossati, Sebastian, 2011. "Covariate Unit Root Tests with Good Size and Power," Working Papers 2011-4, University of Alberta, Department of Economics.
    7. Andreas Sachs & Frauke Schleer, 2013. "Labour Market Performance in OECD Countries: A Comprehensive Empirical Modelling Approach of Institutional Interdependencies. WWWforEurope Working Paper No. 7," WIFO Studies, WIFO, number 46851, April.

  6. Peter Winker & Manfred Gilli & Vahidin Jeleskovic, 2007. "An objective function for simulation based inference on exchange rate data," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 2(2), pages 125-145, December.
    See citations under working paper version above.
  7. Gilli, Manfred & Winker, Peter, 2007. "2nd Special Issue on Applications of Optimization Heuristics to Estimation and Modelling Problems," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 2-3, September.

    Cited by:

    1. Peter Winker & Marianna Lyra & Chris Sharpe, 2008. "Least Median of Squares Estimation by Optimization Heuristics with an Application to the CAPM and Multi Factor Models," Working Papers 006, COMISEF.
    2. Vera, J. Fernando & Di­az-Garci­a, Jose A., 2008. "A global simulated annealing heuristic for the three-parameter lognormal maximum likelihood estimation," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5055-5065, August.
    3. Dennis K.J. Lin & Chris Sharpe & Peter Winker, 2009. "Optimized U-type Designs on Flexible Regions," Working Papers 013, COMISEF.
    4. Gimeno, Ricardo & Nave, Juan M., 2009. "A genetic algorithm estimation of the term structure of interest rates," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2236-2250, April.

  8. Manfred Gilli & Evis këllezi, 2006. "An Application of Extreme Value Theory for Measuring Financial Risk," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 207-228, May.

    Cited by:

    1. David E. Giles & Qinlu Chen, 2014. "Risk Analysis for Three Precious Metals: An Application of Extreme Value Theory," Econometrics Working Papers 1402, Department of Economics, University of Victoria.
    2. Asima Saleem, 2022. "Action for Action: Mad COVID-19, Falling Markets and Rising Volatility of SAARC Region," Annals of Data Science, Springer, vol. 9(1), pages 33-54, February.
    3. Dey Ashim Kumar & Das Kumer Pial, 2020. "Predicting Federal Funds Rate Using Extreme Value Theory," Stochastics and Quality Control, De Gruyter, vol. 35(1), pages 1-15, June.
    4. Małgorzata Just & Krzysztof Echaust, 2021. "An Optimal Tail Selection in Risk Measurement," Risks, MDPI, vol. 9(4), pages 1-16, April.
    5. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    6. Krzysztof Echaust & Małgorzata Just, 2020. "Value at Risk Estimation Using the GARCH-EVT Approach with Optimal Tail Selection," Mathematics, MDPI, vol. 8(1), pages 1-24, January.
    7. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    8. Ahmed, Dilan & Soleymani, Fazlollah & Ullah, Malik Zaka & Hasan, Hataw, 2021. "Managing the risk based on entropic value-at-risk under a normal-Rayleigh distribution," Applied Mathematics and Computation, Elsevier, vol. 402(C).
    9. Julia S. Mehlitz & Benjamin R. Auer, 2021. "Time‐varying dynamics of expected shortfall in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 895-925, June.
    10. Amira Dridi & Mohamed El Ghourabi & Mohamed Limam, 2012. "On monitoring financial stress index with extreme value theory," Quantitative Finance, Taylor & Francis Journals, vol. 12(3), pages 329-339, March.
    11. Renan O. Regis & Raydonal Ospina & Wilton Bernardino & Francisco Cribari-Neto, 2023. "Asset pricing in the Brazilian financial market: five-factor GAMLSS modeling," Empirical Economics, Springer, vol. 64(5), pages 2373-2409, May.
    12. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    13. Feng Ren & David E. Giles, 2007. "Extreme Value Analysis of Daily Canadian Crude Oil Prices," Econometrics Working Papers 0708, Department of Economics, University of Victoria.
    14. Feng, Zhen-Hua & Wei, Yi-Ming & Wang, Kai, 2012. "Estimating risk for the carbon market via extreme value theory: An empirical analysis of the EU ETS," Applied Energy, Elsevier, vol. 99(C), pages 97-108.
    15. M. Naresh Kumar & V. Sree Hari Rao, 2015. "A New Methodology for Estimating Internal Credit Risk and Bankruptcy Prediction under Basel II Regime," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 83-102, June.
    16. Allen, David E. & Singh, Abhay K. & Powell, Robert J., 2013. "EVT and tail-risk modelling: Evidence from market indices and volatility series," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 355-369.
    17. Muteba Mwamba, John W. & Hammoudeh, Shawkat & Gupta, Rangan, 2017. "Financial tail risks in conventional and Islamic stock markets: A comparative analysis," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 60-82.
    18. Jacob Gyntelberg & Eli M Remolona, 2007. "Risk in carry trades: a look at target currencies in Asia and the Pacific," BIS Quarterly Review, Bank for International Settlements, December.
    19. Delson Chikobvu & Thabani Ndlovu, 2023. "The Generalised Extreme Value Distribution Approach to Comparing the Riskiness of BitCoin/US Dollar and South African Rand/US Dollar Returns," JRFM, MDPI, vol. 16(4), pages 1-16, April.
    20. Biener, Christian & Eling, Martin & Wirfs, Jan Hendrik, 2015. "Insurability of Cyber Risk: An Empirical Analysis," Working Papers on Finance 1503, University of St. Gallen, School of Finance.
    21. Montshioa, Keitumetse & Muteba Mwamba, John Weirstrass & Bonga-Bonga, Lumengo, 2021. "Asset allocation in extreme market conditions: a comparative analysis between developed and emerging economies," MPRA Paper 106248, University Library of Munich, Germany.
    22. John Kwaku Mensah Mawutor & Kezia Bortey & Bernardine Ansah & Faustina Osei- Frimpong & Worlanyo Kumassah, 2015. "Credit Risk Management and Profitability of Banks Listed on the Ghana Stock Exchange," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 4(7), pages 396-406.
    23. Knowledge Chinhamu & Chun-Kai Huang & Chun-Sung Huang & Jahvaid Hammujuddy, 2015. "Empirical Analyses of Extreme Value Models for the South African Mining Index," South African Journal of Economics, Economic Society of South Africa, vol. 83(1), pages 41-55, March.
    24. Suarez, R, 2001. "Improving Modeling of Extreme Events using Generalized Extreme Value Distribution or Generalized Pareto Distribution with Mixing Unconditional Disturbances," MPRA Paper 17443, University Library of Munich, Germany.
    25. Marco Flores, 2013. "Cuantificación del riesgo operacional mediante modelos de pérdidas agregadas y simulación de Monte Carlo," Analítika, Analítika - Revista de Análisis Estadístico/Journal of Statistical Analysis, vol. 5(1), pages 39-48, Junio.
    26. Julian Pareja Vasseur & Juan Giraldo Cerón & Santiago Zapata Valencia, 2017. "Market Risk, Non-parametric Methods: Hong-Kong Case," Economia Coyuntural,Revista de temas de perspectivas y coyuntura, Instituto de Investigaciones Economicas y Sociales 'Jose Ortiz Mercado' (IIES-JOM), Facultad de Ciencias Economicas, Administrativas y Financieras, Universidad Autonoma Gabriel Rene Moreno, vol. 2(4), pages 45-80.
    27. Zhi-Fu Mi & Yue-Jun Zhang, 2010. "Estimating the 'value at risk' of EUA futures prices based on the extreme value theory," CEEP-BIT Working Papers 9, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    28. Davide Ferrari & Sandra Paterlini, 2007. "The Maximum Lq-Likelihood Method: an Application to Extreme Quantile Estimation in Finance," Department of Economics 555, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    29. Chiara Lattanzi & Manuele Leonelli, 2019. "A changepoint approach for the identification of financial extreme regimes," Papers 1902.09205, arXiv.org.
    30. Yong Ma & Zhengjun Zhang & Weiguo Zhang & Weidong Xu, 2015. "Evaluating the Default Risk of Bond Portfolios with Extreme Value Theory," Computational Economics, Springer;Society for Computational Economics, vol. 45(4), pages 647-668, April.
    31. Kokoszka Piotr & Miao Hong & Stoev Stilian & Zheng Ben, 2019. "Risk Analysis of Cumulative Intraday Return Curves," Journal of Time Series Econometrics, De Gruyter, vol. 11(2), pages 1-31, July.
    32. Bert Kramer, 2012. "CVaR optimization of real estate portfolios in an ALM context," ERES eres2012_019, European Real Estate Society (ERES).
    33. Xia Yang & Jing Zhang & Wei-Xin Ren, 2018. "Threshold selection for extreme value estimation of vehicle load effect on bridges," International Journal of Distributed Sensor Networks, , vol. 14(2), pages 15501477187, February.
    34. Heba M. Ezzat, 2019. "Disposition effect and multi-asset market dynamics," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 11(2), pages 144-164, June.
    35. Huang, Chun-Kai & North, Delia & Zewotir, Temesgen, 2017. "Exchangeability, extreme returns and Value-at-Risk forecasts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 204-216.
    36. Nieto, María Rosa & Ruiz Ortega, Esther, 2010. "Bootstrap prediction intervals for VaR and ES in the context of GARCH models," DES - Working Papers. Statistics and Econometrics. WS ws102814, Universidad Carlos III de Madrid. Departamento de Estadística.
    37. Alex Huang, 2011. "Volatility Modeling by Asymmetrical Quadratic Effect with Diminishing Marginal Impact," Computational Economics, Springer;Society for Computational Economics, vol. 37(3), pages 301-330, March.
    38. Xin Chen & Zhangming Shan & Decai Tang & Biao Zhou & Valentina Boamah, 2023. "Interest rate risk of Chinese commercial banks based on the GARCH-EVT model," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    39. Chao Wang & Richard Gerlach, 2019. "Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall," Papers 1906.09961, arXiv.org.
    40. Balesdent, Mathieu & Morio, Jérôme & Marzat, Julien, 2015. "Recommendations for the tuning of rare event probability estimators," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 68-78.
    41. Cifter, Atilla, 2011. "Value-at-risk estimation with wavelet-based extreme value theory: Evidence from emerging markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2356-2367.
    42. Abdul-Aziz Ibn Musah & Jianguo Du & Hira Salah Ud din Khan & Alhassan Alolo Abdul-Rasheed Akeji, 2018. "The Asymptotic Decision Scenarios of an Emerging Stock Exchange Market: Extreme Value Theory and Artificial Neural Network," Risks, MDPI, vol. 6(4), pages 1-24, November.
    43. Ahmed, Rizwan & Chaudhry, Sajid M. & Kumpamool, Chamaiporn & Benjasak, Chonlakan, 2022. "Tail risk, systemic risk and spillover risk of crude oil and precious metals," Energy Economics, Elsevier, vol. 112(C).
    44. Giuseppe Storti & Chao Wang, 2023. "Modeling uncertainty in financial tail risk: A forecast combination and weighted quantile approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1648-1663, November.
    45. Cerović Julija & Lipovina-Božović Milena & Vujošević Saša, 2015. "A Comparative Analysis of Value at Risk Measurement on Emerging Stock Markets: Case of Montenegro," Business Systems Research, Sciendo, vol. 6(1), pages 36-55, March.
    46. Nathalie HILMI & Alain SAFA & Victor PLANAS-BIELSA & Yasser KADMIRI & Mine CINAR, 2017. "Ocean acidification in the Middle East and North African region," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 46, pages 43-57.
    47. Bertrand Maillet & Jean-Philippe Médecin & Thierry Michel, 2009. "High Watermarks of Market Risks," Post-Print halshs-00425585, HAL.
    48. Mario Domingues de Paula Simões & Marcelo Cabus Klotzle & Antonio Carlos Figueiredo Pinto & Leonardo Lima Gomes, 2016. "Electricity prices forecast analysis using the extreme value theory," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 5(1), pages 1-22.
    49. Singh, Abhay K. & Allen, David E. & Robert, Powell J., 2013. "Extreme market risk and extreme value theory," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 310-328.
    50. Gonzales-Martínez, Rolando, 2008. "Medidas de Riesgo Financiero y una Aplicación a las Variaciones de Depósitos del Sistema Financiero Boliviano [Risk Measures and an Application to the Withdrawals of Deposits in the Bolivian Financ," MPRA Paper 14700, University Library of Munich, Germany.
    51. Masih-Tehrani, Behdad & Xu, Susan H. & Kumara, Soundar & Li, Haijun, 2011. "A single-period analysis of a two-echelon inventory system with dependent supply uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1128-1151, September.
    52. Marcin Pitera & Thorsten Schmidt, 2020. "Estimating and backtesting risk under heavy tails," Papers 2010.09937, arXiv.org, revised Jan 2022.
    53. M. Naresh Kumar & V. Sree Hari Rao, 2015. "A New Methodology for Estimating Internal Credit Risk and Bankruptcy Prediction under Basel II Regime," Papers 1502.00882, arXiv.org.
    54. Chaudhry, Sajid M. & Ahmed, Rizwan & Huynh, Toan Luu Duc & Benjasak, Chonlakan, 2022. "Tail risk and systemic risk of finance and technology (FinTech) firms," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    55. Mizgier, Kamil J. & Hora, Manpreet & Wagner, Stephan M. & Jüttner, Matthias P., 2015. "Managing operational disruptions through capital adequacy and process improvement," European Journal of Operational Research, Elsevier, vol. 245(1), pages 320-332.
    56. Moch Panji Agung Saputra & Diah Chaerani & Sukono & Mazlynda Md. Yusuf, 2023. "Reserve Fund Optimization Model for Digital Banking Transaction Risk with Extreme Value-at-Risk Constraints," Mathematics, MDPI, vol. 11(16), pages 1-16, August.
    57. Zhang, Hanxiong & Auer, Benjamin R. & Vortelinos, Dimitrios I., 2018. "Performance ranking (dis)similarities in commodity markets," Global Finance Journal, Elsevier, vol. 35(C), pages 115-137.
    58. Salhi, Khaled & Deaconu, Madalina & Lejay, Antoine & Champagnat, Nicolas & Navet, Nicolas, 2016. "Regime switching model for financial data: Empirical risk analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 148-157.
    59. Giuseppe Storti & Chao Wang, 2021. "Modelling uncertainty in financial tail risk: a forecast combination and weighted quantile approach," Papers 2104.04918, arXiv.org, revised Jul 2021.
    60. Bi, Guang & Giles, David E., 2009. "Modelling the financial risk associated with U.S. movie box office earnings," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2759-2766.
    61. Li, Longqing, 2017. "A Comparative Study of GARCH and EVT Model in Modeling Value-at-Risk," MPRA Paper 85645, University Library of Munich, Germany.
    62. Khamis Hamed Al‐Yahyaee & Syed Jawad Hussain Shahzad & Walid Mensi & Seong‐Min Yoon, 2021. "Is there a systemic risk between Sharia, Sukuk, and GCC stock markets? A ΔCoVaR risk metric‐based copula approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2904-2926, April.
    63. Rashid Nikzad & David McDonald, 2017. "Extreme Value Theory with an Application to Bank Failures through Contagion," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(3), pages 1-6.
    64. Minkah, Richard & de Wet, Tertius & Ghosh, Abhik, 2022. "Robust Extreme Quantile Estimation for Pareto-Type tails through an Exponential Regression Model," AfricArxiv hf7vk, Center for Open Science.
    65. Suarez, Ronny, 2009. "Improving Modeling of Extreme Events using Generalized Extreme Value Distribution or Generalized Pareto Distribution with Mixing Unconditional Disturbances," MPRA Paper 17482, University Library of Munich, Germany.
    66. Jian Zhou & Randy Anderson, 2012. "Extreme Risk Measures for International REIT Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 45(1), pages 152-170, June.
    67. Smith, Curtis L., 2020. "Representing external hazard initiating events using a Bayesian approach and a generalized extreme value model," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    68. Yunhan Li & J. Scott Shonkwiler, 2021. "Assessing the Role of Ordering in Sequential English Auctions – Evidence from the Online Western Video Market Auction," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(1), pages 90-105, January.
    69. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    70. Jittima Singvejsakul & Chukiat Chaiboonsri & Songsak Sriboonchitta, 2021. "The Optimization of Bayesian Extreme Value: Empirical Evidence for the Agricultural Commodities in the US," Economies, MDPI, vol. 9(1), pages 1-10, March.
    71. Heinz, Frigyes Ferdinand & Rusinova, Desislava, 2015. "An alternative view of exchange market pressure episodes in emerging Europe: an analysis using Extreme Value Theory (EVT)," Working Paper Series 1818, European Central Bank.
    72. Tomáš Jeøábek, 2020. "The Efficiency of GARCH Models in Realizing Value at Risk Estimates," ACTA VSFS, University of Finance and Administration, vol. 14(1), pages 32-50.
    73. Bonga-Bonga, Lumengo & Montshioa, Keitumetse, 2024. "Navigating extreme market fluctuations: asset allocation strategies in developed vs. emerging economies," MPRA Paper 119910, University Library of Munich, Germany.
    74. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
    75. Wang, Yi-Chen & Wang, Ching-Wen & Huang, Chia-Hsing, 2015. "The impact of unconventional monetary policy on the tail risks of stock markets between U.S. and Japan," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 41-51.
    76. Ra l de Jes s-Guti rrez & Roberto J. Santill n-Salgado, 2019. "Conditional Extreme Values Theory and Tail-related Risk Measures: Evidence from Latin American Stock Markets," International Journal of Economics and Financial Issues, Econjournals, vol. 9(3), pages 127-141.
    77. Eling, Martin & Wirfs, Jan Hendrik, 2016. "Cyber Risk: Too Big to Insure? Risk Transfer Options for a mercurial risk class," I.VW HSG Schriftenreihe, University of St.Gallen, Institute of Insurance Economics (I.VW-HSG), volume 59, number 59.

  9. Winker, Peter & Gilli, Manfred, 2004. "Applications of optimization heuristics to estimation and modelling problems," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 211-223, September.

    Cited by:

    1. Chipman, J. & Winker, P., 2005. "Optimal aggregation of linear time series models," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 311-331, April.
    2. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    3. Viktoria Blüschke-Nikolaeva & Dmitri Blüschke & Reinhard Neck, 2010. "Optimal Control of Nonlinear Dynamic Econometric Models: An Algorithm and an Application," Working Papers 032, COMISEF.
    4. Florios, Kostas, 2018. "A hyperplanes intersection simulated annealing algorithm for maximum score estimation," Econometrics and Statistics, Elsevier, vol. 8(C), pages 37-55.
    5. Baur, Dirk G. & Glover, Kristoffer J., 2014. "Heterogeneous expectations in the gold market: Specification and estimation," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 116-133.
    6. Ivan Savin & Abiodun Egbetokun, 2013. "Emergence of Innovation Networks from R&D Cooperation with Endogenous Absorptive Capacity," Working Papers CEB 13-022, ULB -- Universite Libre de Bruxelles.
    7. Peter Winker & Marianna Lyra & Chris Sharpe, 2008. "Least Median of Squares Estimation by Optimization Heuristics with an Application to the CAPM and Multi Factor Models," Working Papers 006, COMISEF.
    8. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Lyra, M. & Paha, J. & Paterlini, S. & Winker, P., 2010. "Optimization heuristics for determining internal rating grading scales," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2693-2706, November.
    10. Unler, Alper & Murat, Alper, 2010. "A discrete particle swarm optimization method for feature selection in binary classification problems," European Journal of Operational Research, Elsevier, vol. 206(3), pages 528-539, November.
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    12. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.
    13. Kapetanios, George, 2007. "Variable selection in regression models using nonstandard optimisation of information criteria," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 4-15, September.
    14. Ivan Savin & Peter Winker, 2012. "Heuristic Optimization Methods for Dynamic Panel Data Model Selection: Application on the Russian Innovative Performance," Computational Economics, Springer;Society for Computational Economics, vol. 39(4), pages 337-363, April.
    15. El-Shagi, Makram, 2010. "An Evolutionary Algorithm for the Estimation of Threshold Vector Error Correction Models," IWH Discussion Papers 1/2010, Halle Institute for Economic Research (IWH).
    16. Chen, Ray-Bing & Hsu, Yen-Wen & Hung, Ying & Wang, Weichung, 2014. "Discrete particle swarm optimization for constructing uniform design on irregular regions," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 282-297.
    17. S.-C. Horng & S.-Y. Lin, 2009. "Ordinal Optimization of G/G/1/K Polling Systems with k-Limited Service Discipline," Journal of Optimization Theory and Applications, Springer, vol. 140(2), pages 213-231, February.
    18. Dennis K.J. Lin & Chris Sharpe & Peter Winker, 2009. "Optimized U-type Designs on Flexible Regions," Working Papers 013, COMISEF.
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    21. Fitzenberger, Bernd & Winker, Peter, 2007. "Improving the computation of censored quantile regressions," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 88-108, September.
    22. S. Bandyopadhyay & R. Baragona & U. Maulik, 2010. "Fuzzy clustering of univariate and multivariate time series by genetic multiobjective optimization," Working Papers 028, COMISEF.
    23. Tscheschel, A. & Stoyan, D., 2006. "Statistical reconstruction of random point patterns," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 859-871, November.
    24. Manfred Gilli & Enrico Schumann, 2010. "Calibrating Option Pricing Models with Heuristics," Working Papers 030, COMISEF.
    25. V. Robles & C. Bielza & P. Larrañaga & S. González & L. Ohno-Machado, 2008. "Optimizing logistic regression coefficients for discrimination and calibration using estimation of distribution algorithms," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(2), pages 345-366, December.
    26. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
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    Cited by:

    1. Tomas Balint & Francesco Lamperti & Antoine Mandel & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2016. "Complexity and the Economics of Climate Change: a Survey and a Look Forward," SciencePo Working papers Main halshs-01390694, HAL.
    2. Westerhoff Frank H., 2008. "The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 195-227, April.
    3. Winker, Peter & Gilli, Manfred, 2004. "Applications of optimization heuristics to estimation and modelling problems," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 211-223, September.
    4. Peter Boswijk & Cars H. Hommes & Sebastiano Manzan, 2005. "Behavioral Heterogeneity in Stock Prices," Tinbergen Institute Discussion Papers 05-052/1, Tinbergen Institute.
    5. Chipman, J. & Winker, P., 2005. "Optimal aggregation of linear time series models," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 311-331, April.
    6. Cars Hommes & Florian Wagener, 2008. "Complex Evolutionary Systems in Behavioral Finance," Tinbergen Institute Discussion Papers 08-054/1, Tinbergen Institute.
    7. Bianchi, Carlo & Cirillo, Pasquale & Gallegati, Mauro & Vagliasindi, Pietro A., 2008. "Validation in agent-based models: An investigation on the CATS model," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 947-964, September.
    8. Peter Winker & Manfred Gilli & Vahidin Jeleskovic, 2007. "An Objective Function for Simulation Based Inference on Exchange Rate Data," Swiss Finance Institute Research Paper Series 07-01, Swiss Finance Institute.
    9. Domenico Delli Gatti & Jakob Grazzini, 2019. "Rising to the Challenge: Bayesian Estimation and Forecasting Techniques for Macroeconomic Agent-Based Models," CESifo Working Paper Series 7894, CESifo.
    10. Ivan Jericevich & Patrick Chang & Tim Gebbie, 2021. "Simulation and estimation of an agent-based market-model with a matching engine," Papers 2108.07806, arXiv.org, revised Aug 2021.
    11. Klein, Achim & Urbig, Diemo, 2008. "Who Drives the Market? Estimating a Heterogeneous Agent-based Financial Market Model Using a Neural Network Approach," MPRA Paper 116175, University Library of Munich, Germany, revised 30 Apr 2011.
    12. Ivan Jericevich & Murray McKechnie & Tim Gebbie, 2021. "Calibrating an adaptive Farmer-Joshi agent-based model for financial markets," Papers 2104.09863, arXiv.org.
    13. Yi Zhang & Zhe Li & Yongchao Zhang, 2020. "Validation and Calibration of an Agent-Based Model: A Surrogate Approach," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-9, January.
    14. Barde, Sylvain, 2016. "Direct comparison of agent-based models of herding in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 329-353.
    15. Carro, Adrian & Hinterschweiger, Marc & Uluc, Arzu & Farmer, J. Doyne, 2022. "Heterogeneous effects and spillovers of macroprudential policy in an agent-based model of the UK housing market," Bank of England working papers 976, Bank of England.
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    17. Severin Reissl, 2021. "Heterogeneous expectations, forecasting behaviour and policy experiments in a hybrid Agent-based Stock-flow-consistent model," Journal of Evolutionary Economics, Springer, vol. 31(1), pages 251-299, January.
    18. Ryuichi Yamamoto & Hideaki Hirata, "undated". "Strategy Switching in the Japanese Stock Market," Working Paper 164466, Harvard University OpenScholar.
    19. Franke, Reiner & Westerhoff, Frank, 2011. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," BERG Working Paper Series 78, Bamberg University, Bamberg Economic Research Group.
    20. Baur, Dirk G. & Glover, Kristoffer J., 2014. "Heterogeneous expectations in the gold market: Specification and estimation," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 116-133.
    21. Vidal-Tomás, David & Alfarano, Simone, 2018. "An agent based early warning indicator for financial market instability," MPRA Paper 89693, University Library of Munich, Germany.
    22. Chen, Zhiping & Duan, Qihong, 2011. "New models of trader beliefs and their application for explaining financial bubbles," Economic Modelling, Elsevier, vol. 28(5), pages 2215-2227, September.
    23. Severin Reissl & Alessandro Caiani & Francesco Lamperti & Mattia Guerini & Fabio Vanni & Giorgio Fagiolo & Tommaso Ferraresi & Leonardo Ghezzi & Mauro Napoletano & Andrea Roventini, 2021. "Assessing the economic impact of lockdowns in Italy: a computational input-output approach," SciencePo Working papers Main hal-03373672, HAL.
    24. LeBaron Blake & Winker Peter, 2008. "Introduction to the Special Issue on Agent-Based Models for Economic Policy Advice," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 141-148, April.
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    35. Schmitt, Noemi & Westerhoff, Frank, 2014. "Speculative behavior and the dynamics of interacting stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 262-288.
    36. Xue-Zhong He & Youwei Li, 2015. "Testing of a Market Fraction Model and Power-Law Behaviour in the Dax 30," Research Paper Series 354, Quantitative Finance Research Centre, University of Technology, Sydney.
    37. Donovan Platt & Tim Gebbie, 2016. "The Problem of Calibrating an Agent-Based Model of High-Frequency Trading," Papers 1606.01495, arXiv.org, revised Mar 2017.
    38. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Economics Working Papers 2008-08, Christian-Albrechts-University of Kiel, Department of Economics.
    39. Tedeschi, Gabriele & Recchioni, Maria Cristina & Berardi, Simone, 2019. "An approach to identifying micro behavior: How banks’ strategies influence financial cycles," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 329-346.
    40. Ge, Jiaqi, 2014. "Stepping into new territory: Three essays on agent-based computational economics and environmental economics," ISU General Staff Papers 201401010800004899, Iowa State University, Department of Economics.
    41. Zila, Eric & Kukacka, Jiri, 2023. "Moment set selection for the SMM using simple machine learning," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 366-391.
    42. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 277-293, October.
    43. Tiziana Assenza & William Brock & Cars Hommes, 2013. "Animal Spirits, Heterogeneous Expectations and the Emergence of Booms and Busts," DISCE - Working Papers del Dipartimento di Economia e Finanza def007, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    44. Emanuele Ciola & Edoardo Gaffeo & Mauro Gallegati, 2021. "Search for Profits and Business Fluctuations: How Banks' Behaviour Explain Cycles?," Working Papers 450, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    45. Raquel Almeida Ramos & Federico Bassi & Dany Lang, 2020. "Bet against the trend and cash in profits," FMM Working Paper 60-2020, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    46. Zhang, Jinyu & Zhang, Qiaosen & Li, Yong & Wang, Qianchao, 2023. "Sequential Bayesian inference for agent-based models with application to the Chinese business cycle," Economic Modelling, Elsevier, vol. 126(C).
    47. Wei Zhao & Yi Lu & Genfu Feng, 2019. "How Many Agents are Rational in China’s Economy? Evidence from a Heterogeneous Agent-Based New Keynesian Model," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 575-611, August.
    48. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.
    49. Amilon, Henrik, 2008. "Estimation of an adaptive stock market model with heterogeneous agents," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 342-362, March.
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    51. Thorsten Lehnert & Bart Frijns & Remco C.J. Zwinkels, 2010. "Modelling structural changes in the volatility process," LSF Research Working Paper Series 10-05, Luxembourg School of Finance, University of Luxembourg.
    52. Francesco Lamperti, 2016. "Empirical Validation of Simulated Models through the GSL-div: an Illustrative Application," LEM Papers Series 2016/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    53. Radu T. Pruna & Maria Polukarov & Nicholas R. Jennings, 2020. "Loss aversion in an agent-based asset pricing model," Quantitative Finance, Taylor & Francis Journals, vol. 20(2), pages 275-290, February.
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    58. Di Iorio, Francesca & Calzolari, Giorgio, 2006. "Discontinuities in indirect estimation: An application to EAR models," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 2124-2136, April.
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    61. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    62. Jakob Grazzini, 2012. "Analysis of the Emergent Properties: Stationarity and Ergodicity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(2), pages 1-7.
    63. Ghonghadze, Jaba & Lux, Thomas, 2016. "Bringing an elementary agent-based model to the data: Estimation via GMM and an application to forecasting of asset price volatility," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 1-19.
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    67. Severin Reissl & Alessandro Caiani & Francesco Lamperti & Mattia Guerini & Fabio Vanni & Giorgio Fagiolo & Tommaso Ferraresi & Leonardo Ghezzi & Mauro Napoletano & Andrea Roventini, 2021. "Assessing the economic effects of lockdowns in Italy: a computational Input-Output approach," LEM Papers Series 2021/03, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    68. Adrian Carro, 2022. "Could Spain be less different? Exploring the effects of macroprudential policy on the house price cycle," Working Papers 2230, Banco de España.
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    108. Federico Bassi & Raquel Ramos & Dany Lang, 2023. "Bet against the trend and cash in profits: An agent-based model of endogenous fluctuations of exchange rates," Journal of Evolutionary Economics, Springer, vol. 33(2), pages 429-472, April.
    109. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers 12/08, Department of Economics, City University London.
    110. Nan Lu, 2018. "La modélisation de l’indice CAC 40 avec un modèle basé agent," Erudite Ph.D Dissertations, Erudite, number ph18-02 edited by François Legendre, December.
    111. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    112. Giorgio Fagiolo & Andrea Roventini, 2016. "Macroeconomic Policy in DGSE and Agent-Based Models Redux," Working Papers hal-03459348, HAL.
    113. Simone Berardi & Gabriele Tedeschi, 2016. "How banks’ strategies influence financial cycles: An approach to identifying micro behavior," Working Papers 2016/24, Economics Department, Universitat Jaume I, Castellón (Spain).
    114. Donovan Platt, 2019. "A Comparison of Economic Agent-Based Model Calibration Methods," Papers 1902.05938, arXiv.org.
    115. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.
    116. Platt, Donovan & Gebbie, Tim, 2018. "Can agent-based models probe market microstructure?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1092-1106.
    117. Zhenxi Chen & Thomas Lux, 2018. "Estimation of Sentiment Effects in Financial Markets: A Simulated Method of Moments Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 711-744, October.
    118. Siyan Chen & Saul Desiderio, 2022. "A Regression-Based Calibration Method for Agent-Based Models," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 687-700, February.
    119. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Springer;Society for Computational Economics, vol. 26(1), pages 19-49, August.
    120. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    121. Sylvain Barde, 2022. "Bayesian Estimation of Large-Scale Simulation Models with Gaussian Process Regression Surrogates," Studies in Economics 2203, School of Economics, University of Kent.
    122. Elizabeth Jane Casabianca & Alessia Lo Turco & Daniela Maggioni, 2021. "Migration And The Structure Of Manufacturing Production. A View From Italian Provinces," Working Papers 448, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    123. Francesco Lamperti, 2018. "Empirical validation of simulated models through the GSL-div: an illustrative application," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 143-171, April.
    124. Markus Demary, 2011. "Transaction taxes, greed and risk aversion in an agent-based financial market model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(1), pages 1-28, May.
    125. Wai-Mun Chia & Mengling Li & Huanhuan Zheng, 2017. "Behavioral heterogeneity in the Australian housing market," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 872-885, February.
    126. Haber Gottfried, 2008. "Monetary and Fiscal Policy Analysis With an Agent-Based Macroeconomic Model," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 276-295, April.
    127. Saskia ter Ellen & Willem F. C. Verschoor, 2018. "Heterogeneous Beliefs and Asset Price Dynamics: A Survey of Recent Evidence," Dynamic Modeling and Econometrics in Economics and Finance, in: Fredj Jawadi (ed.), Uncertainty, Expectations and Asset Price Dynamics, pages 53-79, Springer.
    128. Radu T. Pruna & Maria Polukarov & Nicholas R. Jennings, 2016. "A new structural stochastic volatility model of asset pricing and its stylized facts," Papers 1604.08824, arXiv.org.
    129. Tae-Seok Jang, 2015. "Identification of Social Interaction Effects in Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 207-238, February.
    130. Saskia ter Ellen & Willem F.C. Verschoor, 2017. "Heterogeneous beliefs and asset price dynamics: a survey of recent evidence," Working Paper 2017/22, Norges Bank.

  11. Gilli, Manfred & Kellezi, Evis & Pauletto, Giorgio, 2002. "Solving finite difference schemes arising in trivariate option pricing," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1499-1515, August.

    Cited by:

    1. Karpuz, Başak & Özsavaş, Büşra, 2021. "An improved product type oscillation test for partial difference equations," Applied Mathematics and Computation, Elsevier, vol. 391(C).
    2. Stradi-Granados, Benito A. & Haven, Emmanuel, 2010. "The use of interval arithmetic in solving a non-linear rational expectation based multiperiod output-inflation process model: The case of the IN/GB method," European Journal of Operational Research, Elsevier, vol. 203(1), pages 222-229, May.

  12. Giorgio Pauletto & Manfred Gilli, 2000. "Parallel Krylov Methods for Econometric Model Simulation," Computational Economics, Springer;Society for Computational Economics, vol. 16(1/2), pages 173-186, October.

    Cited by:

    1. William L. Goffe & Michael Creel, 2005. "Multi-core CPUs, Clusters and Grid Computing: a Tutorial," Computing in Economics and Finance 2005 438, Society for Computational Economics.
    2. N. B. Melnikov & A. P. Gruzdev & M. G. Dalton & M. Weitzel & B. C. O’Neill, 2021. "Parallel Extended Path Method for Solving Perfect Foresight Models," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 517-534, August.
    3. Gilli, Manfred & Kellezi, Evis & Pauletto, Giorgio, 2002. "Solving finite difference schemes arising in trivariate option pricing," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1499-1515, August.

  13. Henri Louberge & Evis Kellezi & Manfred Gilli, 1999. "Using Catastrophe-Linked Securities to Diversity Insurance Risk: A Financial Analysis of Cat Bonds," Journal of Insurance Issues, Western Risk and Insurance Association, vol. 22(2), pages 125-146.

    Cited by:

    1. Massimo Mariani & Paola Amoruso, 2016. "The Effectiveness of Catastrophe Bonds in Portfolio Diversification," International Journal of Economics and Financial Issues, Econjournals, vol. 6(4), pages 1760-1767.
    2. Pérez-Fructuoso, María José, 2017. "Tarificación de bonos sobre catástrofes (cat bonds) con desencadenantes de índices de pérdidas. Modelación mediante un proceso de Ornstein-Uhlenbeck || Pricing Loss Index Triggered Cat Bonds. An Ornst," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 24(1), pages 340-361, Diciembre.
    3. Ma, Zong-Gang & Ma, Chao-Qun, 2013. "Pricing catastrophe risk bonds: A mixed approximation method," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 243-254.
    4. Chang Carolyn W. & Feng Yalan, 2021. "Hurricane Bond Price Dependency on Underlying Hurricane Parameters," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 15(1), pages 1-21, January.
    5. Zac J. Taylor, 2020. "The real estate risk fix: Residential insurance-linked securitization in the Florida metropolis," Environment and Planning A, , vol. 52(6), pages 1131-1149, September.
    6. Riza Andrian Ibrahim & Sukono & Herlina Napitupulu & Rose Irnawaty Ibrahim, 2024. "Earthquake Bond Pricing Model Involving the Inconstant Event Intensity and Maximum Strength," Mathematics, MDPI, vol. 12(6), pages 1-21, March.
    7. Eckhard Platen & David Taylor, 2016. "Loading Pricing of Catastrophe Bonds and Other Long-Dated, Insurance-Type Contracts," Papers 1610.09875, arXiv.org.
    8. Y. Esmaeelzade Aghdam & A. Neisy & A. Adl, 2024. "Simulating and Pricing CAT Bonds Using the Spectral Method Based on Chebyshev Basis," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 423-435, January.
    9. Ivan Damnjanovic & Zafer Aslan & John Mander, 2010. "Market‐Implied Spread for Earthquake CAT Bonds: Financial Implications of Engineering Decisions," Risk Analysis, John Wiley & Sons, vol. 30(12), pages 1753-1770, December.
    10. Ben Ammar, Semir & Braun, Alexander & Eling, Martin, 2015. "Alternative Risk Transfer and Insurance-Linked Securities: Trends, Challenges and New Market Opportunities," I.VW HSG Schriftenreihe, University of St.Gallen, Institute of Insurance Economics (I.VW-HSG), volume 56, number 56.
    11. Braun, Alexander, 2011. "Pricing catastrophe swaps: A contingent claims approach," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 520-536.
    12. Fabio Pizzutilo & Elisabetta Venezia, 2018. "Are catastrophe bonds effective financial instruments in the transport and infrastructure industries? Evidence from international financial markets," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(2), pages 256-267, April.
    13. Henri Loubergé, 1998. "Risk and Insurance Economics 25 Years After," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 23(4), pages 540-567, October.
    14. Riza Andrian Ibrahim & Sukono & Herlina Napitupulu, 2022. "Multiple-Trigger Catastrophe Bond Pricing Model and Its Simulation Using Numerical Methods," Mathematics, MDPI, vol. 10(9), pages 1-17, April.
    15. Sukono & Riza Andrian Ibrahim & Moch Panji Agung Saputra & Yuyun Hidayat & Hafizan Juahir & Igif Gimin Prihanto & Nurfadhlina Binti Abdul Halim, 2022. "Modeling Multiple-Event Catastrophe Bond Prices Involving the Trigger Event Correlation, Interest, and Inflation Rates," Mathematics, MDPI, vol. 10(24), pages 1-18, December.

  14. Gaspard Aeschimann & Gabrielle Antille & Fabrizio Carlevaro & Jean-Paul Chaze & Giovanni Ferro-Luzzi & Yves Flückiger & Manfred Gilli, 1999. "Modelling and forecasting the social contributions to the Swiss Old Age and Survivor Insurance scheme," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 135(III), pages 349-368, September.

    Cited by:

    1. Laura Barbieri & Chiara Mussida, 2018. "Structural differences across macroregions: an empirical investigation," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(2), pages 215-246, May.
    2. Laura Barbieri & Maurizio Baussola & Chiara Mussida, 2012. "A regional labour market model for analyzing the impact of a recession," DISCE - Quaderni del Dipartimento di Scienze Economiche e Sociali dises1288, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    3. Enrico Fabrizi, 2009. "The Determinants of Labour Market Transitions," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 68(2), pages 233-265, July.

  15. Gilli, Manfred & Pauletto, Giorgio, 1998. "Krylov methods for solving models with forward-looking variables," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1275-1289, August.

    Cited by:

    1. Hallett, A. J. Hughes & Piscitelli, Laura, 1998. "Simple reordering techniques for expanding the convergence radius of first-order iterative techniques," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1319-1333, August.
    2. N. B. Melnikov & A. P. Gruzdev & M. G. Dalton & M. Weitzel & B. C. O’Neill, 2021. "Parallel Extended Path Method for Solving Perfect Foresight Models," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 517-534, August.
    3. Jan Bruha & Jiri Podpiera & Mr. Stanislav Polak, 2007. "The Convergence Dynamics of a Transition Economy: The Case of the Czech Republic," IMF Working Papers 2007/116, International Monetary Fund.
    4. Judd, Kenneth L., 2002. "The parametric path method: an alternative to Fair-Taylor and L-B-J for solving perfect foresight models," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1557-1583, August.
    5. Binder, Michael & Pesaran, Hashem, 2000. "Solution of finite-horizon multivariate linear rational expectations models and sparse linear systems," Journal of Economic Dynamics and Control, Elsevier, vol. 24(3), pages 325-346, March.
    6. Jiri Popiera & Jan Bruha, 2007. "Inquiries on Dynamics of Transition Economy Convergence in a Two-Country Model," 2007 Meeting Papers 587, Society for Economic Dynamics.
    7. Bajeux-Besnainou, Isabelle & Bandara, Wachindra & Bura, Efstathia, 2012. "A Krylov subspace approach to large portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 36(11), pages 1688-1699.
    8. Stradi-Granados, Benito A. & Haven, Emmanuel, 2010. "The use of interval arithmetic in solving a non-linear rational expectation based multiperiod output-inflation process model: The case of the IN/GB method," European Journal of Operational Research, Elsevier, vol. 203(1), pages 222-229, May.
    9. Mrkaic, Mico, 2002. "Policy iteration accelerated with Krylov methods," Journal of Economic Dynamics and Control, Elsevier, vol. 26(4), pages 517-545, April.
    10. Gilli, Manfred & Kellezi, Evis & Pauletto, Giorgio, 2002. "Solving finite difference schemes arising in trivariate option pricing," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1499-1515, August.

  16. Gilli, Manfred & Pauletto, Giorgio, 1997. "Sparse direct methods for model simulation," Journal of Economic Dynamics and Control, Elsevier, vol. 21(6), pages 1093-1111, June.

    Cited by:

    1. Binder, Michael & Pesaran, Hashem, 2000. "Solution of finite-horizon multivariate linear rational expectations models and sparse linear systems," Journal of Economic Dynamics and Control, Elsevier, vol. 24(3), pages 325-346, March.
    2. Yongyang Cai & Kenneth L. Judd, 2023. "A simple but powerful simulated certainty equivalent approximation method for dynamic stochastic problems," Quantitative Economics, Econometric Society, vol. 14(2), pages 651-687, May.
    3. Franz, Wolfgang & Göggelmann, Klaus & Schellhorn, Martin & Winker, Peter, 1998. "Quasi-Monte Carlo Methods in Stochastic Simulations: An Application to Fiscal Policy Simulations using an Aggregate Disequilibrium Model of the West German Economy," ZEW Discussion Papers 98-03, ZEW - Leibniz Centre for European Economic Research.
    4. Stradi-Granados, Benito A. & Haven, Emmanuel, 2010. "The use of interval arithmetic in solving a non-linear rational expectation based multiperiod output-inflation process model: The case of the IN/GB method," European Journal of Operational Research, Elsevier, vol. 203(1), pages 222-229, May.
    5. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September.
    6. Gary S. Anderson, "undated". "An Application of Sparse Methods to Solving a Multi-Country Model With Rational Expectations," Computing in Economics and Finance 1996 _063, Society for Computational Economics.
    7. Gilli, Manfred & Pauletto, Giorgio, 1998. "Krylov methods for solving models with forward-looking variables," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1275-1289, August.
    8. Gilli, Manfred & Kellezi, Evis & Pauletto, Giorgio, 2002. "Solving finite difference schemes arising in trivariate option pricing," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1499-1515, August.

  17. Gilli, Manfred, 1992. "Causal Ordering and Beyond," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(4), pages 957-971, November.

    Cited by:

    1. Bates, Samuel & Angeon, Valérie & Ainouche, Ahmed, 2014. "The pentagon of vulnerability and resilience: A methodological proposal in development economics by using graph theory," Economic Modelling, Elsevier, vol. 42(C), pages 445-453.
    2. Hallett, A. J. Hughes & Piscitelli, Laura, 1998. "Simple reordering techniques for expanding the convergence radius of first-order iterative techniques," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1319-1333, August.
    3. Alessio Moneta, 2003. "Graphical Models for Structural Vector Autoregressions," LEM Papers Series 2003/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    4. Faust, Jon & Tryon, Ralph, 1995. "A Distributed Block Approach to Solving Near-Block-Diagonal Systems with an Application to a Large Macroeconometric Model," Computational Economics, Springer;Society for Computational Economics, vol. 8(4), pages 303-316, November.
    5. Jon Faust & Ralph W. Tryon, 1995. "Block distributed methods for solving multi-country econometric models," International Finance Discussion Papers 516, Board of Governors of the Federal Reserve System (U.S.).
    6. Gelman, Irit Askira, 2005. "Addressing time-scale differences among decision-makers through model abstractions," European Journal of Operational Research, Elsevier, vol. 160(2), pages 325-335, January.
    7. Gilli, Manfred & Garbely, Myriam, 1996. "Matchings, covers, and Jacobian matrices," Journal of Economic Dynamics and Control, Elsevier, vol. 20(9-10), pages 1541-1556.

  18. Gilli, M & Pauletto, G & Garbely, M, 1992. "Equation Reordering for Iterative Processes--A Comment," Computer Science in Economics & Management, Kluwer;Society for Computational Economics, vol. 5(2), pages 147-153, May.

    Cited by:

    1. Gilli, Manfred & Pauletto, Giorgio, 1997. "Sparse direct methods for model simulation," Journal of Economic Dynamics and Control, Elsevier, vol. 21(6), pages 1093-1111, June.
    2. Manfred Gilli & Giorgio Pauletto, "undated". "An Application of Nonstationary Iterative Methods for Solving a Multi-Country Model with Rational Expectations," Computing in Economics and Finance 1996 _045, Society for Computational Economics.
    3. Jon Faust & Ralph W. Tryon, 1995. "Block distributed methods for solving multi-country econometric models," International Finance Discussion Papers 516, Board of Governors of the Federal Reserve System (U.S.).

  19. Garbely, Myriam & Gilli, Manfred, 1991. "Qualitative decomposition of the eigenvalue problem in a dynamic system," Journal of Economic Dynamics and Control, Elsevier, vol. 15(3), pages 539-548, July.

    Cited by:

    1. Lady, George M., 1995. "Robust economic models," Journal of Economic Dynamics and Control, Elsevier, vol. 19(3), pages 481-501, April.

  20. Gilli, M & Ritschard, G, 1978. "A Program for Causal and Qualitative Analysis of Economic," Econometrica, Econometric Society, vol. 46(2), pages 477-478, March.

    Cited by:

    1. Manfred Gilli & Gilbert Ritschard & Daniel Royer, 1983. "Pour une approche structurale en économie," Revue Économique, Programme National Persée, vol. 34(2), pages 277-304.
    2. Bruce Larson, 1980. "An algebraic approach to qualitative knowledge," Quality & Quantity: International Journal of Methodology, Springer, vol. 14(2), pages 355-362, March.

Books

  1. Gilli, Manfred & Maringer, Dietmar & Schumann, Enrico, 2011. "Numerical Methods and Optimization in Finance," Elsevier Monographs, Elsevier, edition 1, number 9780123756626.

    Cited by:

    1. Marc S. Paolella, 2014. "Fast Methods For Large-Scale Non-Elliptical Portfolio Optimization," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 1-32.
    2. Stefan Andreea-Mirabela, 2020. "Metaheuristichybridization: Memeticalgorithm," Annals of University of Craiova - Economic Sciences Series, University of Craiova, Faculty of Economics and Business Administration, vol. 1(48), pages 155-164, August.
    3. Gaudard, Ludovic & Madani, Kaveh, 2019. "Energy storage race: Has the monopoly of pumped-storage in Europe come to an end?," Energy Policy, Elsevier, vol. 126(C), pages 22-29.
    4. Kapetanios, George & Marcellino, Massimiliano & Papailias, Fotis, 2016. "Forecasting inflation and GDP growth using heuristic optimisation of information criteria and variable reduction methods," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 369-382.
    5. Miśkiewicz, Janusz, 2013. "Power law classification scheme of time series correlations. On the example of G20 group," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2150-2162.
    6. Andrea Scozzari & Fabio Tardella & Sandra Paterlini & Thiemo Krink, 2013. "Exact and heuristic approaches for the index tracking problem with UCITS constraints," Annals of Operations Research, Springer, vol. 205(1), pages 235-250, May.
    7. Pierre Cahuc & Franck Malherbet & Julien Prat, 2019. "The Detrimental Effect of Job Protection on Employment: Evidence from France," Working Papers hal-03881628, HAL.
    8. Ludovic Gaudard & Manfred Gilli & Franco Romerio, 2013. "Climate Change Impacts on Hydropower Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5143-5156, December.
    9. Joseph Andria & Giacomo Tollo & Raffaele Pesenti, 2015. "Detection of local tourism systems by threshold accepting," Computational Management Science, Springer, vol. 12(4), pages 559-575, October.
    10. Radpour, Saeidreza & Gemechu, Eskinder & Ahiduzzaman, Md & Kumar, Amit, 2021. "Development of a framework for the assessment of the market penetration of novel in situ bitumen extraction technologies," Energy, Elsevier, vol. 220(C).
    11. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.
    12. Becker, Martin & Klößner, Stefan, 2018. "Fast and reliable computation of generalized synthetic controls," Econometrics and Statistics, Elsevier, vol. 5(C), pages 1-19.
    13. Manuel Kleinknecht & Wing Lon Ng, 2015. "Minimizing Basel III Capital Requirements with Unconditional Coverage Constraint," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 22(4), pages 263-281, October.
    14. Mullen, Katharine M., 2014. "Continuous Global Optimization in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 60(i06).
    15. Marco Di Francesco, 2021. "Portfolio optimization under solvency II: a multi-objective approach incorporating market views and real-world constraints," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 269-294, June.
    16. Paulo M.M. Rodrigues & Gabriel Zsurkis, 2023. "First passage times in portfolio optimization: a novel nonparametric approach," Working Papers w202309, Banco de Portugal, Economics and Research Department.
    17. Bilias, Yannis & Florios, Kostas & Skouras, Spyros, 2019. "Exact computation of Censored Least Absolute Deviations estimator," Journal of Econometrics, Elsevier, vol. 212(2), pages 584-606.
    18. Longbing Cao & Qiang Yang & Philip S. Yu, 2020. "Data science and AI in FinTech: An overview," Papers 2007.12681, arXiv.org, revised Jul 2021.
    19. Longbing Cao, 2021. "AI in Finance: Challenges, Techniques and Opportunities," Papers 2107.09051, arXiv.org.
    20. De Haas Samuel & Winker Peter, 2016. "Detecting Fraudulent Interviewers by Improved Clustering Methods – The Case of Falsifications of Answers to Parts of a Questionnaire," Journal of Official Statistics, Sciendo, vol. 32(3), pages 643-660, September.
    21. Capuozzo, Pietro & Panella, Emanuele & Schettini Gherardini, Tancredi & Vvedensky, Dimitri D., 2021. "Path integral Monte Carlo method for option pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    22. Doering, Jana & Kizys, Renatas & Juan, Angel A. & Fitó, Àngels & Polat, Onur, 2019. "Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends," Operations Research Perspectives, Elsevier, vol. 6(C).
    23. Marco Di Francesco & Kevin Kamm, 2021. "How to handle negative interest rates in a CIR framework," Papers 2106.03716, arXiv.org.
    24. Bergmeir, Christoph & Molina, Daniel & Benítez, José M., 2016. "Memetic Algorithms with Local Search Chains in R: The Rmalschains Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 75(i04).
    25. Singh, Vikas Vikram & Lisser, Abdel & Arora, Monika, 2021. "An equivalent mathematical program for games with random constraints," Statistics & Probability Letters, Elsevier, vol. 174(C).
    26. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.
    27. Tahereh Khodamoradi & Maziar Salahi & Ali Reza Najafi, 2021. "Cardinality-constrained portfolio optimization with short selling and risk-neutral interest rate," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 197-214, June.
    28. Moritz Birgit & Becker Martin & Schmidtchen Dieter, 2018. "Measuring the Deterrent Effect of European Cartel Law Enforcement," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 18(3), pages 1-27, July.
    29. Marcello Calvanese Strinati & Claudio Conti, 2022. "Multidimensional hyperspin machine," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    30. Samuel Fern'andez-Lorenzo & Diego Porras & Juan Jos'e Garc'ia-Ripoll, 2020. "Hybrid quantum-classical optimization for financial index tracking," Papers 2008.12050, arXiv.org, revised Oct 2021.
    31. Dufo-López, Rodolfo & Cristóbal-Monreal, Iván R. & Yusta, José M., 2016. "Stochastic-heuristic methodology for the optimisation of components and control variables of PV-wind-diesel-battery stand-alone systems," Renewable Energy, Elsevier, vol. 99(C), pages 919-935.
    32. Ben R. Craig & Dietmar Maringer & Sandra Paterlini, 2019. "Recreating Banking Networks under Decreasing Fixed Costs," Working Papers 19-21, Federal Reserve Bank of Cleveland.
    33. Tae-Seok Jang, 2015. "Identification of Social Interaction Effects in Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 207-238, February.

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