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Cees Diks

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. Wilko Bolt & Maria Demertzis & Cees Diks & Cars Hommes & Marco van der Leij, 2014. "Identifying Booms and Busts in House Prices under Heterogeneous Expectations," European Economy - Economic Papers 2008 - 2015 540, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.

    Cited by:

    1. Martin, Carolin & Schmitt, Noemi & Westerhoff, Frank, 2021. "Heterogeneous expectations, housing bubbles and tax policy," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 555-573.
    2. Ling Zhang & Wenlong Bian & Hao Zhang, 2019. "Dissecting the myth of the house price in Chinese metropolises: allowing for behavioral heterogeneity among investors," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 721-740, December.
    3. Martin, Carolin & Schmitt, Noemi & Westerhoff, Frank, 2019. "Housing markets, expectation formation and interest rates," BERG Working Paper Series 142, Bamberg University, Bamberg Economic Research Group.
    4. Te Bao & Cars Hommes & Tomasz Makarewicz, 2015. "Bubble Formation and (In)Efficient Markets in Learning-to-Forecast and -optimise Experiments," Tinbergen Institute Discussion Papers 15-107/II, Tinbergen Institute.
    5. Makarewicz, Tomasz, 2021. "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 626-673.
    6. Ming-Chu Chiang & I-Chun Tsai, 2020. "Importance of Proper Monetary Liquidity: Sustainable Development of the Housing and Stock Markets," Sustainability, MDPI, vol. 12(21), pages 1-20, October.
    7. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    8. Chen, Zhenxi, 2016. "Regimes dependent speculative trading: Evidence from the United States housing market," FinMaP-Working Papers 66, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    9. Christophe André & Nikolaos Antonakakis & Rangan Gupta & Mulatu F. Zerihun, 2017. "Asymmetric Behaviour in Nominal and Real Housing Prices: Evidence from Advanced and Emerging Economies," Working Papers 201711, University of Pretoria, Department of Economics.
    10. Daniel L. Tortorice, 2019. "Long-Run Expectations, Learning and the US Housing Market," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 45(4), pages 497-531, October.
    11. Makarewicz, Tomasz, 2019. "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," BERG Working Paper Series 141, Bamberg University, Bamberg Economic Research Group.
    12. Christophe Andre & Rangan Gupta & John W. Muteba Mwamba, 2016. "Are Housing Price Cycles Asymmetric? Evidence from the US States and Metropolitan Areas," Working Papers 201635, University of Pretoria, Department of Economics.
    13. Dieci, Roberto & Schmitt, Noemi & Westerhoff, Frank H., 2018. "Interactions between stock, bond and housing markets," BERG Working Paper Series 133, Bamberg University, Bamberg Economic Research Group.
    14. Anufriev, M. & Hommes, C.H. & Makarewicz, T.A., 2015. "Simple Forecasting Heuristics that Make us Smart: Evidence from Different Market Experiments," CeNDEF Working Papers 15-07, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    15. Bolgorian, Meysam, 2019. "Can a cusp catastrophe model describe the effect of sanctions on exchange rates?," Economics Discussion Papers 2019-2, Kiel Institute for the World Economy (IfW Kiel).
    16. Benjamin Patrick Evans & Mikhail Prokopenko, 2022. "Bounded strategic reasoning explains crisis emergence in multi-agent market games," Papers 2206.05568, arXiv.org.
    17. Alessandra Canepa & Emilio Zanetti Chini & Huthaifa Alqaralleh, 2020. "Global Cities and Local Housing Market Cycles," The Journal of Real Estate Finance and Economics, Springer, vol. 61(4), pages 671-697, November.
    18. Saskia ter Ellen & Cars H. Hommes & Remco C.J. Zwinkels, 2017. "Comparing behavioural heterogeneity across asset classes," Working Paper 2017/12, Norges Bank.
    19. Jian Yang & Zheng Li & Ziliang Yu, 2024. "Low‐ frequency versus high‐frequency housing price spillovers in China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(4), pages 3713-3749, December.
    20. Yang Tang & Kairong Hong & Yucheng Zou & Yanwei Zhang, 2021. "Impact of Emotional Perceived Value on the Uncertain Evolution of the Housing Bubble," Mathematics, MDPI, vol. 9(13), pages 1-23, July.
    21. Stjepan Begušić & Zvonko Kostanjčar & Dejan Kovač & H. Eugene Stanley & Boris Podobnik, 2018. "Information Feedback in Temporal Networks as a Predictor of Market Crashes," Complexity, Hindawi, vol. 2018, pages 1-13, September.
    22. Zheng, Min & Wang, Hefei & Wang, Chengzhang & Wang, Shouyang, 2017. "Speculative behavior in a housing market: Boom and bust," Economic Modelling, Elsevier, vol. 61(C), pages 50-64.
    23. Roy Kouwenberg & Remco C J Zwinkels, 2015. "Endogenous Price Bubbles in a Multi-Agent System of the Housing Market," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-10, June.
    24. Diks, Cees & Wang, Juanxi, 2016. "Can a stochastic cusp catastrophe model explain housing market crashes?," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 68-88.
    25. Dieci, Roberto & Westerhoff, Frank, 2016. "Heterogeneous expectations, boom-bust housing cycles, and supply conditions: A nonlinear economic dynamics approach," Journal of Economic Dynamics and Control, Elsevier, vol. 71(C), pages 21-44.
    26. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    27. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    28. Hommes, Cars & Vroegop, Joris, 2019. "Contagion between asset markets: A two market heterogeneous agents model with destabilising spillover effects," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 314-333.
    29. 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.
    30. Donald Coletti, 2023. "A Blueprint for the Fourth Generation of Bank of Canada Projection and Policy Analysis Models," Discussion Papers 2023-23, Bank of Canada.
    31. Michael S. Harr'e, 2018. "Multi-agent Economics and the Emergence of Critical Markets," Papers 1809.01332, arXiv.org.
    32. Dieci, Roberto & Westerhoff, Frank, 2015. "Heterogeneous expectations, boom-bust housing cycles, and supply conditions: A nonlinear dynamics approach," BERG Working Paper Series 99, Bamberg University, Bamberg Economic Research Group.
    33. Wang, J., 2015. "Can a stochastic cusp catastrophe model explain housing market crashes?," CeNDEF Working Papers 15-12, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    34. Noemi Schmitt & Frank Westerhoff, 2022. "Speculative housing markets and rent control: insights from nonlinear economic dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(1), pages 141-163, January.
    35. Zhang, Hao & Huang, Yuyuan & Yao, Haixiang, 2016. "Heterogeneous expectation, beliefs evolution and house price volatility," Economic Modelling, Elsevier, vol. 53(C), pages 409-418.
    36. Alona Shmygel, 2022. "House Price Bubble Detection in Ukraine," IHEID Working Papers 22-2022, Economics Section, The Graduate Institute of International Studies.

  2. Diks, C.G.H. & Wolski, M., 2013. "Nonlinear Granger Causality: Guidelines for Multivariate Analysis," CeNDEF Working Papers 13-15, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Guochang Wang & Wai Keung Li & Ke Zhu, 2018. "New HSIC-based tests for independence between two stationary multivariate time series," Papers 1804.09866, arXiv.org.
    2. Stolbov, Mikhail & Shchepeleva, Maria, 2020. "Systemic risk, economic policy uncertainty and firm bankruptcies: Evidence from multivariate causal inference," Research in International Business and Finance, Elsevier, vol. 52(C).
    3. Emmanuel Joel Aikins Abakah & Aviral Kumar Tiwari & Imhotep Paul Alagidede & Shawkat Hammoudeh, 2023. "Nonlinearity in the causality and systemic risk spillover between the OPEC oil and GCC equity markets: a pre- and post-financial crisis analysis," Empirical Economics, Springer, vol. 65(3), pages 1027-1103, September.
    4. Ren, Weijie & Li, Baisong & Han, Min, 2020. "A novel Granger causality method based on HSIC-Lasso for revealing nonlinear relationship between multivariate time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    5. Roberto Fuentes M. & Irene Crimaldi & Armando Rungi, 2024. "Non-linear dependence and Granger causality: A vine copula approach," Papers 2409.15070, arXiv.org.
    6. Ahmed, Ali & Granberg, Mark & Troster, Victor & Uddin, Gazi Salah, 2020. "Asymmetric Dynamics between Uncertainty and Unemployment Flows in the United States," LiU Working Papers in Economics 7, Linköping University, Division of Economics, Department of Management and Engineering.
    7. Le, Thai-Ha & Nguyen, Canh Phuc, 2019. "Is energy security a driver for economic growth? Evidence from a global sample," Energy Policy, Elsevier, vol. 129(C), pages 436-451.
    8. Zheng Fang & Marcin Wolski, 2021. "Human capital, energy and economic growth in China: evidence from multivariate nonlinear Granger causality tests," Empirical Economics, Springer, vol. 60(2), pages 607-632, February.
    9. Jose Perez-Montiel & Carles Manera Erbina, 2019. "Investment Sustained by Consumption: A Linear and Nonlinear Time Series Analysis," Sustainability, MDPI, vol. 11(16), pages 1-15, August.
    10. Costas Siriopoulos & Sophia Kassapi, 2019. "Is Education an Investment for the Future? The Impact of the Greek case on Economic Growth," Annals of Social Sciences & Management studies, Juniper Publishers Inc., vol. 3(5), pages 116-119, July.
    11. Grobys, Klaus & Huynh, Toan Luu Duc, 2022. "When Tether says “JUMP!” Bitcoin asks “How low?”," Finance Research Letters, Elsevier, vol. 47(PA).
    12. Gary J. Cornwall & Jeffrey A. Mills & Beau A. Sauley & Huibin Weng, 2019. "Predictive Testing for Granger Causality via Posterior Simulation and Cross-validation," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 275-292, Emerald Group Publishing Limited.
    13. Stolbov, Mikhail & Shchepeleva, Maria & Karminsky, Alexander, 2022. "When central bank research meets Google search: A sentiment index of global financial stress," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    14. Shafiullah, Muhammad & Miah, Mohammad Dulal & Alam, Md Samsul & Atif, Muhammad, 2021. "Does economic policy uncertainty affect renewable energy consumption?," Renewable Energy, Elsevier, vol. 179(C), pages 1500-1521.
    15. Zheng Fang & Jiang Yu, 2020. "The role of human capital in energy-growth nexus: an international evidence," Empirical Economics, Springer, vol. 58(3), pages 1225-1247, March.
    16. Troster, Victor & Bouri, Elie & Roubaud, David, 2019. "A quantile regression analysis of flights-to-safety with implied volatilities," Resources Policy, Elsevier, vol. 62(C), pages 482-495.
    17. Zięba, Damian, 2024. "If GPU(time) == money: Sustainable crypto-asset market? Analysis of similarity among crypto-asset financial time series," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 863-912.
    18. Li, Sufang & Tu, Dalun & Zeng, Yan & Gong, Chenggang & Yuan, Di, 2022. "Does geopolitical risk matter in crude oil and stock markets? Evidence from disaggregated data," Energy Economics, Elsevier, vol. 113(C).
    19. Jena, Sangram Keshari & Tiwari, Aviral Kumar & Hammoudeh, Shawkat & Roubaud, David, 2019. "Distributional predictability between commodity spot and futures: Evidence from nonparametric causality-in-quantiles tests," Energy Economics, Elsevier, vol. 78(C), pages 615-628.
    20. Kim, Jong-Min & Lee, Namgil & Hwang, Sun Young, 2020. "A Copula Nonlinear Granger Causality," Economic Modelling, Elsevier, vol. 88(C), pages 420-430.
    21. Muhammad Shahbaz & Muhammad Shafiullah & Mantu K. Mahalik, 2019. "The dynamics of financial development, globalisation, economic growth and life expectancy in sub‐Saharan Africa," Australian Economic Papers, Wiley Blackwell, vol. 58(4), pages 444-479, December.
    22. Omane-Adjepong, Maurice & Alagidede, Imhotep Paul, 2019. "Multiresolution analysis and spillovers of major cryptocurrency markets," Research in International Business and Finance, Elsevier, vol. 49(C), pages 191-206.
    23. Wolski, Marcin, 2018. "Sovereign risk and corporate cost of borrowing: Evidence from a counterfactual study," EIB Working Papers 2018/05, European Investment Bank (EIB).
    24. Lien, Donald & Lee, Geul & Yang, Li & Zhang, Yuyin, 2018. "Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 187-201.
    25. Piotr FISZEDER & Witold ORZESZKO, 2018. "Nonlinear Granger causality between grains and livestock," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 64(7), pages 328-336.
    26. Nana Kwame Akosah & Imhotep Paul Alagidede & Eric Schaling, 2021. "Dynamics of Money Market Interest Rates in Ghana: Time‐Frequency Analysis of Volatility Spillovers," South African Journal of Economics, Economic Society of South Africa, vol. 89(4), pages 555-589, December.
    27. Meng Yan & Kai Shi, 2024. "Revisiting the Impact of US Uncertainty Shocks: New Evidence from China’s Investment Dynamics," Open Economies Review, Springer, vol. 35(3), pages 457-495, July.
    28. Katleho Makatjane & Ntebogang Moroke & Diteboho Xaba, 2017. "Threshold Cointegration and Nonlinear Causality test between Inflation Rate and Repo Rate," Journal of Economics and Behavioral Studies, AMH International, vol. 9(3), pages 163-170.
    29. Bu, Hui & Tang, Wenjin & Wu, Junjie, 2019. "Time-varying comovement and changes of comovement structure in the Chinese stock market: A causal network method," Economic Modelling, Elsevier, vol. 81(C), pages 181-204.
    30. Mohammad Dulal Miah & Muhammad Shafiullah & Md. Samsul Alam, 2024. "The effect of financial stress on renewable energy consumption: evidence from US data," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(10), pages 26623-26646, October.

  3. Bolt, W. & Demertzis, D. & Diks, C.G.H. & Van der Leij, M.J., 2011. "Complex Methods in Economics: An Example of Behavioral Heterogeneity in House Prices," CeNDEF Working Papers 11-12, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Darius Kulikauskas, 2015. "Measuring fundamental housing prices in the Baltic States: empirical approach," ERES eres2015_31, European Real Estate Society (ERES).
    2. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.

  4. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Grigory Franguridi, 2014. "Higher order conditional moment dynamics and forecasting value-at-risk (in Russian)," Quantile, Quantile, issue 12, pages 69-82, February.
    3. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    4. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    5. Taillardat, Maxime & Fougères, Anne-Laure & Naveau, Philippe & de Fondeville, Raphaël, 2023. "Evaluating probabilistic forecasts of extremes using continuous ranked probability score distributions," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1448-1459.
    6. Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    7. James Mitchell & Martin Weale, 2021. "Censored Density Forecasts: Production and Evaluation," Working Papers 21-12R, Federal Reserve Bank of Cleveland, revised 16 Aug 2022.
    8. Christopher McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," CAMA Working Papers 2016-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Luisa Bisaglia & Matteo Grigoletto, 2018. "A new time-varying model for forecasting long-memory series," Papers 1812.07295, arXiv.org.
    10. Chaya Weerasinghe & Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2023. "ABC-based Forecasting in State Space Models," Monash Econometrics and Business Statistics Working Papers 12/23, Monash University, Department of Econometrics and Business Statistics.
    11. Rossi, Barbara & Sekhposyan, Tatevik, 2013. "Conditional predictive density evaluation in the presence of instabilities," Journal of Econometrics, Elsevier, vol. 177(2), pages 199-212.
    12. Emilio Zanetti Chini, 2019. "Strategic judgment: its game-theoretic foundations,its econometric elicitation," Working Papers in Public Economics 190, Department of Economics and Law, Sapienza University of Roma.
    13. David T. Frazier & Gael M. Martin & Ruben Loaiza-Maya, 2022. "Variational Bayes in State Space Models: Inferential and Predictive Accuracy," Monash Econometrics and Business Statistics Working Papers 1/22, Monash University, Department of Econometrics and Business Statistics.
    14. Barbara Rossi & Tatevik Sekhposyan, 2013. "Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set," Economics Working Papers 1370, Department of Economics and Business, Universitat Pompeu Fabra.
    15. Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
    16. J. Hambuckers & C. Heuchenne, 2017. "A robust statistical approach to select adequate error distributions for financial returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(1), pages 137-161, January.
    17. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    18. Jie Cheng, 2024. "Evaluating Density Forecasts Using Weighted Multivariate Scores in a Risk Management Context," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3617-3643, December.
    19. C. Alexander & M. Coulon & Y. Han & X. Meng, 2024. "Evaluating the discrimination ability of proper multi-variate scoring rules," Annals of Operations Research, Springer, vol. 334(1), pages 857-883, March.
    20. Elena Andreou & Andros Kourtellos, 2018. "Scoring rules for simple forecasting models: The case of Cyprus GDP and its sectors," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 12(1), pages 59-73, June.
    21. Benjamin Beckers & Helmut Herwartz & Moritz Seidel, 2017. "Risk forecasting in (T)GARCH models with uncorrelated dependent innovations," Quantitative Finance, Taylor & Francis Journals, vol. 17(1), pages 121-137, January.
    22. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
    23. Lee, Cheol Woo & Kang, Kyu Ho, 2023. "Estimating and testing skewness in a stochastic volatility model," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 445-467.
    24. Götz, T.B. & Hecq, A.W. & Urbain, J.R.Y.J., 2014. "Combining distributions of real-time forecasts: An application to U.S. growth," Research Memorandum 027, Maastricht University, Graduate School of Business and Economics (GSBE).
    25. Mahsa Gorji & Rasoul Sajjad, 2017. "Improving Value-at-Risk Estimation from the Normal EGARCH Model," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 11(1), March.
    26. Gael M. Martin & Rub'en Loaiza-Maya & David T. Frazier & Worapree Maneesoonthorn & Andr'es Ram'irez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Papers 2009.09592, arXiv.org.
    27. Shamsi Zamenjani, Azam, 2021. "Do financial variables help predict the conditional distribution of the market portfolio?," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 327-345.
    28. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    29. Cees Diks & Valentyn Panchenko & Oleg Sokolinskiy, & Dick van Dijk, 2013. "Comparing the Accuracy of Copula-Based Multivariate Density Forecasts in Selected Regions of Support," Tinbergen Institute Discussion Papers 13-061/III, Tinbergen Institute.
    30. Zdeněk Zmeškal & Dana Dluhošová & Karolina Lisztwanová & Antonín Pončík & Iveta Ratmanová, 2023. "Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy," Forecasting, MDPI, vol. 5(2), pages 1-19, May.
    31. Luisa Bisaglia & Matteo Grigoletto, 2021. "A new time-varying model for forecasting long-memory series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 139-155, March.
    32. Michael B. Gordy & Alexander J. McNeil, 2018. "Spectral Backtests of Forecast Distributions with Application to Risk Management," Finance and Economics Discussion Series 2018-021, Board of Governors of the Federal Reserve System (U.S.).
    33. Giovanni Bonaccolto & Massimiliano Caporin & Rangan Gupta, 2015. "The Dynamic Impact of Uncertainty in Causing and Forecasting the Distribution of Oil Returns and Risk," Working Papers 201564, University of Pretoria, Department of Economics.
    34. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
    35. Diks, Cees & Fang, Hao, 2020. "Comparing density forecasts in a risk management context," International Journal of Forecasting, Elsevier, vol. 36(2), pages 531-551.
    36. Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019. "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers 19-057/III, Tinbergen Institute.
    37. Fawcett, Nicholas & Kapetanios, George & Mitchell, James & Price, Simon, 2014. "Generalised density forecast combinations," Bank of England working papers 492, Bank of England.
    38. Julien Hambuckers & Marie Kratz & Antoine Usseglio-Carleve, 2023. "Efficient Estimation In Extreme Value Regression Models Of Hedge Fund Tail Risks," Working Papers hal-04090916, HAL.
    39. Anufriev, Mikhail & Panchenko, Valentyn, 2015. "Connecting the dots: Econometric methods for uncovering networks with an application to the Australian financial institutions," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 241-255.
    40. Julien Hambuckers & Marie Kratz & Antoine Usseglio-Carleve, 2023. "Efficient Estimation in Extreme Value Regression Models of Hedge Fund Tail Risks," Papers 2304.06950, arXiv.org.
    41. Shaun P Vahey & Elizabeth C Wakerly, 2013. "Moving towards probability forecasting," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation and inflation dynamics in Asia and the Pacific, volume 70, pages 3-8, Bank for International Settlements.
    42. Mengheng Li & Siem Jan (S.J.) Koopman, 2018. "Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction," Tinbergen Institute Discussion Papers 18-027/III, Tinbergen Institute.
    43. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2014. "Improving Density Forecasts and Value-at-Risk Estimates by Combining Densities," Tinbergen Institute Discussion Papers 14-090/III, Tinbergen Institute.
    44. Diks, Cees & Panchenko, Valentyn & Sokolinskiy, Oleg & van Dijk, Dick, 2014. "Comparing the accuracy of multivariate density forecasts in selected regions of the copula support," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 79-94.
    45. Tobias Fissler & Hajo Holzmann, 2022. "Measurability of functionals and of ideal point forecasts," Papers 2203.08635, arXiv.org.
    46. Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024. "Kullback-Leibler-based characterizations of score-driven updates," Papers 2408.02391, arXiv.org, revised Sep 2024.
    47. Onno Kleen, 2024. "Scaling and measurement error sensitivity of scoring rules for distribution forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 833-849, August.
    48. Delatola, E.-I. & Griffin, J.E., 2013. "A Bayesian semiparametric model for volatility with a leverage effect," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 97-110.
    49. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
    50. Chiang, I-Hsuan Ethan & Liao, Yin & Zhou, Qing, 2021. "Modeling the cross-section of stock returns using sensible models in a model pool," Journal of Empirical Finance, Elsevier, vol. 60(C), pages 56-73.
    51. Kim, Dongwhan & Kang, Kyu Ho, 2021. "Conditional value-at-risk forecasts of an optimal foreign currency portfolio," International Journal of Forecasting, Elsevier, vol. 37(2), pages 838-861.
    52. Peter McAdam & Anders Warne, 2024. "Density forecast combinations: The real‐time dimension," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1153-1172, August.
    53. Diego Chicana & Rafael Nivin, 2021. "Evaluating Growth-at-Risk as a tool for monitoring macro-financial risks in the Peruvian economy," IHEID Working Papers 07-2021, Economics Section, The Graduate Institute of International Studies.
    54. McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.
    55. Yuru Sun & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Gael M. Martin, 2023. "Optimal probabilistic forecasts for risk management," Papers 2303.01651, arXiv.org.
    56. Pauwels, Laurent, 2019. "Predicting China’s Monetary Policy with Forecast Combinations," Working Papers BAWP-2019-07, University of Sydney Business School, Discipline of Business Analytics.
    57. Baggio, Roberta & Muzy, Jean-François, 2024. "Improving probabilistic wind speed forecasting using M-Rice distribution and spatial data integration," Applied Energy, Elsevier, vol. 360(C).
    58. Lukasz Gatarek & Lennart Hoogerheide & Koen Hooning & Herman K. van Dijk, 2013. "Censored Posterior and Predictive Likelihood in Left-Tail Prediction for Accurate Value at Risk Estimation," Tinbergen Institute Discussion Papers 13-060/III, Tinbergen Institute, revised 06 Mar 2014.
    59. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    60. Jonas R. Brehmer & Tilmann Gneiting, 2020. "Properization: constructing proper scoring rules via Bayes acts," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 659-673, June.
    61. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    62. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    63. Xiaochun Meng & James W. Taylor & Souhaib Ben Taieb & Siran Li, 2020. "Scores for Multivariate Distributions and Level Sets," Papers 2002.09578, arXiv.org, revised Jun 2023.
    64. A. Ford Ramsey & Yong Liu, 2023. "Linear pooling of potentially related density forecasts in crop insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(3), pages 769-788, September.
    65. Kuangyu Wen & Wenbin Wu & Ximing Wu, 2023. "Electricity demand forecasting and risk management using Gaussian process model with error propagation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 957-969, July.
    66. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    67. Allen, Sam & Koh, Jonathan & Segers, Johan & Ziegel, Johanna, 2024. "Tail calibration of probabilistic forecasts," LIDAM Discussion Papers ISBA 2024018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  5. Diks, C.G.H. & Wagener, F.O.O., 2011. "Phenomenological and ratio bifurcations of a class of discrete time stochastic processes," CeNDEF Working Papers 11-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Schmitt, Noemi & Westerhoff, Frank, 2017. "On the bimodality of the distribution of the S&P 500's distortion: Empirical evidence and theoretical explanations," BERG Working Paper Series 119, Bamberg University, Bamberg Economic Research Group.

  6. De Gooijer, J. & Diks, C.G.H. & Gatarek, L., 2009. "Information Flows Around the Globe: Predicting Opening Gaps from Overnight Foreign Stock Price Patterns," CeNDEF Working Papers 09-13, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2020. "Volatility forecasting using related markets’ information for the Tokyo stock exchange," Economic Modelling, Elsevier, vol. 90(C), pages 143-158.
    2. Rodriguez, E. & Aguilar-Cornejo, M. & Femat, R. & Alvarez-Ramirez, J., 2014. "US stock market efficiency over weekly, monthly, quarterly and yearly time scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 554-564.
    3. Katja Ahoniemi & Ana-Maria Fuertes & Jose Olmo, 2016. "Overnight News and Daily Equity Trading Risk Limits," Journal of Financial Econometrics, Oxford University Press, vol. 14(3), pages 525-551.
    4. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    5. Ana-Maria Fuertes & Jose Olmo, 2016. "On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?," JRFM, MDPI, vol. 9(3), pages 1-20, September.
    6. Christian L Dunis & Jason Laws & Jozef Rudy, 2011. "Profitable mean reversion after large price drops: A story of day and night in the S&P 500, 400 MidCap and 600 SmallCap Indices," Journal of Asset Management, Palgrave Macmillan, vol. 12(3), pages 185-202, August.

  7. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.

    Cited by:

    1. Ardia, David & Lennart, Hoogerheide & Nienke, Corré, 2011. "Stock index returns’ density prediction using GARCH models: Frequentist or Bayesian estimation?," MPRA Paper 28259, University Library of Munich, Germany.
    2. Hoogerheide, Lennart F. & Ardia, David & Corré, Nienke, 2012. "Density prediction of stock index returns using GARCH models: Frequentist or Bayesian estimation?," Economics Letters, Elsevier, vol. 116(3), pages 322-325.
    3. Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
    4. Amisano, Gianni & Geweke, John, 2008. "Comparing and evaluating Bayesian predictive distributions of assets returns," Working Paper Series 969, European Central Bank.

  8. Diks, C.G.H. & Dijk, D. van & Panchenko, V., 2008. "Out-of-sample comparison of copula specifications in multivariate density forecasts," CeNDEF Working Papers 08-10, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Gang-Jin Wang & Chi Xie & Peng Zhang & Feng Han & Shou Chen, 2014. "Dynamics of Foreign Exchange Networks: A Time-Varying Copula Approach," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-11, May.
    2. Tobias Fissler & Yannick Hoga, 2024. "How to Compare Copula Forecasts?," Papers 2410.04165, arXiv.org.
    3. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    4. Koziol, Philipp & Schell, Carmen & Eckhardt, Meik, 2015. "Credit risk stress testing and copulas: Is the Gaussian copula better than its reputation?," Discussion Papers 46/2015, Deutsche Bundesbank.
    5. Tamás Kiss & Hoang Nguyen & Pär Österholm, 2021. "Modelling Returns in US Housing Prices—You’re the One for Me, Fat Tails," JRFM, MDPI, vol. 14(11), pages 1-17, October.
    6. Jean-David Fermanian, 2012. "An overview of the goodness-of-fit test problem for copulas," Papers 1211.4416, arXiv.org.
    7. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
    8. Tranberg, Bo & Hansen, Rasmus Thrane & Catania, Leopoldo, 2020. "Managing volumetric risk of long-term power purchase agreements," Energy Economics, Elsevier, vol. 85(C).
    9. Hayette Gatfaoui, 2010. "Investigating the dependence structure between credit default swap spreads and the U.S. financial market," Annals of Finance, Springer, vol. 6(4), pages 511-535, October.
    10. Cees Diks & Valentyn Panchenko & Oleg Sokolinskiy, & Dick van Dijk, 2013. "Comparing the Accuracy of Copula-Based Multivariate Density Forecasts in Selected Regions of Support," Tinbergen Institute Discussion Papers 13-061/III, Tinbergen Institute.
    11. Diks, Cees & Fang, Hao, 2020. "Comparing density forecasts in a risk management context," International Journal of Forecasting, Elsevier, vol. 36(2), pages 531-551.
    12. Liu, Xiaochun, 2011. "Modeling the time-varying skewness via decomposition for out-of-sample forecast," MPRA Paper 41248, University Library of Munich, Germany.
    13. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Papers 2011-W01, Economics Group, Nuffield College, University of Oxford.
    14. Anufriev, Mikhail & Panchenko, Valentyn, 2015. "Connecting the dots: Econometric methods for uncovering networks with an application to the Australian financial institutions," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 241-255.
    15. Ahmet Akca & Ethem Çanakoğlu, 2021. "Adaptive stochastic risk estimation of firm operating profit," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 48(3), pages 463-504, September.
    16. Jin Xisong & Lehnert Thorsten, 2018. "Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas," Dependence Modeling, De Gruyter, vol. 6(1), pages 19-46, February.
    17. Marc Gronwald & Janina Ketterer & Stefan Trück, 2011. "The Dependence Structure between Carbon Emission Allowances and Financial Markets - A Copula Analysis," CESifo Working Paper Series 3418, CESifo.
    18. Balaev, Alexey, 2014. "The copula based on multivariate t-distribution with vector of degrees of freedom," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 90-110.
    19. Diks, Cees & Panchenko, Valentyn & Sokolinskiy, Oleg & van Dijk, Dick, 2014. "Comparing the accuracy of multivariate density forecasts in selected regions of the copula support," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 79-94.
    20. Jin Seo Cho & Peter C. B. Phillips & Juwon Seo, 2019. "Parametric Inference on the Mean of Functional Data Applied to Lifetime Income Curves," Working papers 2019rwp-153, Yonsei University, Yonsei Economics Research Institute.
    21. Fawad, Muhammad & Yan, Ting & Chen, Lu & Huang, Kangdi & Singh, Vijay P., 2019. "Multiparameter probability distributions for at-site frequency analysis of annual maximum wind speed with L-Moments for parameter estimation," Energy, Elsevier, vol. 181(C), pages 724-737.
    22. Gregor Bäurle & Elizabeth Steiner & Gabriel Züllig, 2021. "Forecasting the production side of GDP," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 458-480, April.
    23. Krenar Avdulaj & Jozef Barunik, 2013. "Are benefits from oil - stocks diversification gone? New evidence from a dynamic copula and high frequency data," Papers 1307.5981, arXiv.org, revised Feb 2015.
    24. Gregor Weiß, 2013. "Copula-GARCH versus dynamic conditional correlation: an empirical study on VaR and ES forecasting accuracy," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 179-202, August.
    25. Weiß, Gregor N.F., 2011. "Are Copula-GoF-tests of any practical use? Empirical evidence for stocks, commodities and FX futures," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(2), pages 173-188, May.
    26. 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.
    27. Pelster, Matthias & Vilsmeier, Johannes, 2016. "The determinants of CDS spreads: Evidence from the model space," Discussion Papers 43/2016, Deutsche Bundesbank.
    28. Pircalabu, A. & Hvolby, T. & Jung, J. & Høg, E., 2017. "Joint price and volumetric risk in wind power trading: A copula approach," Energy Economics, Elsevier, vol. 62(C), pages 139-154.
    29. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.

  9. Bekiros, S. & Diks, C.G.H., 2007. "The Relationship between Crude Oil Spot and Futures Prices: Cointegration, Linear and Nonlinear Causality," CeNDEF Working Papers 07-11, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Chi Zhang & Zhengning Pu & Qin Zhou, 2018. "Sustainable Energy Consumption in Northeast Asia: A Case from China’s Fuel Oil Futures Market," Sustainability, MDPI, vol. 10(1), pages 1-14, January.
    2. Ying Kou & Liming Liu & Meifeng Luo, 2014. "Lead-lag relationship between new-building and second-hand ship prices," Maritime Policy & Management, Taylor & Francis Journals, vol. 41(4), pages 303-327, July.
    3. Cagli, Efe Caglar & Taskin, Dilvin & Evrim Mandaci, Pınar, 2019. "The short- and long-run efficiency of energy, precious metals, and base metals markets: Evidence from the exponential smooth transition autoregressive models," Energy Economics, Elsevier, vol. 84(C).
    4. Ruchika Kaura & Namita Rajput, 2024. "Future–Spot Relationship in Commodity Market: A Comparison Across Commodity Segments in India," Global Business Review, International Management Institute, vol. 25(5), pages 1314-1335, October.
    5. Dergiades, Theologos & Madlener, Reinhard & Christofidou, Georgia, 2012. "The Nexus between Natural Gas Spot and Futures Prices at NYMEX: Do Weather Shocks and Non-Linear Causality in Low Frequencies Matter?," FCN Working Papers 17/2012, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Sep 2013.
    6. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2010. "Market Efficiency of Oil Spot and Futures: A Mean-Variance and Stochastic Dominance Approach," Working Papers in Economics 10/18, University of Canterbury, Department of Economics and Finance.
    7. Smyth, Russell & Narayan, Paresh Kumar, 2015. "Applied econometrics and implications for energy economics research," Energy Economics, Elsevier, vol. 50(C), pages 351-358.
    8. Mihaela Nicolau, 2012. "Do Spot Prices Move towards Futures Prices? A study on Crude Oil Market," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 5(5), pages 166-176, October.
    9. Apostolakis, George N. & Floros, Christos & Gkillas, Konstantinos & Wohar, Mark, 2024. "Volatility spillovers across the spot and futures oil markets after news announcements," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    10. Chiarella, Carl & Kang, Boda & Nikitopoulos, Christina Sklibosios & Tô, Thuy-Duong, 2013. "Humps in the volatility structure of the crude oil futures market: New evidence," Energy Economics, Elsevier, vol. 40(C), pages 989-1000.
    11. Zhang, Dongyang & Zhao, Mengjiao & Wang, Yizhi & Vigne, Samuel A. & Benkraiem, Ramzi, 2024. "Technological innovation and its influence on energy risk management: Unpacking China’s energy consumption structure optimisation amidst climate change," Energy Economics, Elsevier, vol. 131(C).
    12. Krzysztof Drachal, 2018. "Exchange Rate and Oil Price Interactions in Selected CEE Countries," Economies, MDPI, vol. 6(2), pages 1-21, May.
    13. Sugra Ingilab Humbatova & Natig Qadim-Oglu Hajiyev, 2019. "Oil Factor in Economic Development," Energies, MDPI, vol. 12(8), pages 1-40, April.
    14. Jorge Antunes & Luis Alberiko Gil-Alana & Rossana Riccardi & Yong Tan & Peter Wanke, 2022. "Unveiling endogeneity and temporal dependence in energy prices and demand in Iberian countries: a stochastic hidden Markov model approach," Annals of Operations Research, Springer, vol. 313(1), pages 191-229, June.
    15. Hong, Yun & Li, Yi, 2020. "Housing prices and investor sentiment dynamics: Evidence from China using a wavelet approach," Finance Research Letters, Elsevier, vol. 35(C).
    16. Scott, Ayesha & Schoen, Tilman & Fernandez-Perez, Adrian, 2020. "The Predictive Power of NZX Dairy Futures," 2020 Conference (64th), February 12-14, 2020, Perth, Western Australia 305230, Australian Agricultural and Resource Economics Society.
    17. Semei Coronado & Rebeca Jim'enez-Rodr'iguez & Omar Rojas, 2015. "An empirical analysis of the relationships between crude oil, gold and stock markets," Papers 1510.07599, arXiv.org, revised May 2016.
    18. Yang, Yan-Hong & Shao, Ying-Hui, 2020. "Time-dependent lead-lag relationships between the VIX and VIX futures markets," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    19. Li, Yang & Du, Qingfeng, 2024. "Oil price volatility and gold prices volatility asymmetric links with natural resources via financial market fluctuations: Implications for green recovery," Resources Policy, Elsevier, vol. 88(C).
    20. Magkonis, Georgios & Tsouknidis, Dimitris A., 2017. "Dynamic spillover effects across petroleum spot and futures volatilities, trading volume and open interest," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 104-118.
    21. You‐How Go & Wee‐Yeap Lau, 2023. "What do we know about informational efficiency? Three puzzles and the new direction forward," Journal of Economic Surveys, Wiley Blackwell, vol. 37(4), pages 1489-1525, September.
    22. Lean, H.H. & McAleer, M.J. & Wong, W.-K., 2013. "Risk-averse and Risk-seeking Investor Preferences for Oil Spot and Futures," Econometric Institute Research Papers EI 2013-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    23. Monge, Manuel & Gil-Alana, Luis A. & Pérez de Gracia, Fernando, 2017. "Crude oil price behaviour before and after military conflicts and geopolitical events," Energy, Elsevier, vol. 120(C), pages 79-91.
    24. Maria Pempetzoglou, 2014. "Electricity Consumption and Economic Growth: A Linear and Nonlinear Causality Investigation for Turkey," International Journal of Energy Economics and Policy, Econjournals, vol. 4(2), pages 263-273.
    25. P. Sakthivel & Krishna Reddy Chittedi & Daniel Sakyi, 2017. "Price Discovery and Volatility Transmission in Currency Spot and Futures Markets in India: An Empirical Analysis," Global Business Review, International Management Institute, vol. 20(4), pages 931-945, August.
    26. Nick, Sebastian, 2013. "Price Formation and Intertemporal Arbitrage within a Low-Liquidity Framework: Empirical Evidence from European Natural Gas Markets," EWI Working Papers 2013-14, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    27. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Dynamic frequency relationships and volatility spillovers in natural gas, crude oil, gas oil, gasoline, and heating oil markets: Implications for portfolio management," Resources Policy, Elsevier, vol. 73(C).
    28. LI, Jie & HUANG, Lixin & LI, Ping, 2021. "Are Chinese crude oil futures good hedging tools?," Finance Research Letters, Elsevier, vol. 38(C).
    29. Tokic, Damir, 2011. "Rational destabilizing speculation, positive feedback trading, and the oil bubble of 2008," Energy Policy, Elsevier, vol. 39(4), pages 2051-2061, April.
    30. Xu, Xiaojie, 2014. "Price Discovery in U.S. Corn Cash and Futures Markets: The Role of Cash Market Selection," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169809, Agricultural and Applied Economics Association.
    31. Caspi, Itamar & Katzke, Nico & Gupta, Rangan, 2018. "Date stamping historical periods of oil price explosivity: 1876–2014," Energy Economics, Elsevier, vol. 70(C), pages 582-587.
    32. Balcilar, Mehmet & Gungor, Hasan & Hammoudeh, Shawkat, 2015. "The time-varying causality between spot and futures crude oil prices: A regime switching approach," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 51-71.
    33. Aminu, Alarudeen & Raifu, Isiaka Akande, 2018. "Dynamic Nexus between Government Revenues and Expenditures in Nigeria: Evidence from Asymmetric Causality and Cointegration Methods," MPRA Paper 97880, University Library of Munich, Germany.
    34. Silvério, Renan & Szklo, Alexandre, 2012. "The effect of the financial sector on the evolution of oil prices: Analysis of the contribution of the futures market to the price discovery process in the WTI spot market," Energy Economics, Elsevier, vol. 34(6), pages 1799-1808.
    35. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2010. "Investor Preferences for Oil Spot and Futures Based on Mean-Variance and Stochastic Dominance," Working Papers in Economics 10/22, University of Canterbury, Department of Economics and Finance.
    36. Xiaojie Xu, 2019. "Contemporaneous Causal Orderings of CSI300 and Futures Prices through Directed Acyclic Graphs," Economics Bulletin, AccessEcon, vol. 39(3), pages 2052-2077.
    37. Wang, Yudong & Wu, Chongfeng, 2012. "Energy prices and exchange rates of the U.S. dollar: Further evidence from linear and nonlinear causality analysis," Economic Modelling, Elsevier, vol. 29(6), pages 2289-2297.
    38. Xu Xiaojie, 2018. "Using Local Information to Improve Short-Run Corn Price Forecasts," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 16(1), pages 1-15, January.
    39. Mobeen Ur Rehman, 2020. "Dynamic correlation pattern amongst alternative energy market for diversification opportunities," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-24, December.
    40. Shrestha, Keshab & Philip, Sheena & Peranginangin, Yessy, 2020. "Contributions of Crude Oil Exchange Traded Funds in Price Discovery Process," American Business Review, Pompea College of Business, University of New Haven, vol. 23(2), pages 393-407, November.
    41. Zheng Fang & Marcin Wolski, 2021. "Human capital, energy and economic growth in China: evidence from multivariate nonlinear Granger causality tests," Empirical Economics, Springer, vol. 60(2), pages 607-632, February.
    42. David, S.A. & Inácio Jr., C.M.C. & Tenreiro Machado, José A., 2021. "The recovery of global stock markets indices after impacts due to pandemics," Research in International Business and Finance, Elsevier, vol. 55(C).
    43. Xianfang Su & Huiming Zhu & Xinxia Yang, 2019. "Heterogeneous Causal Relationships between Spot and Futures Oil Prices: Evidence from Quantile Causality Analysis," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    44. Lammerding, Marc & Stephan, Patrick & Trede, Mark & Wilfling, Bernd, 2013. "Speculative bubbles in recent oil price dynamics: Evidence from a Bayesian Markov-switching state-space approach," Energy Economics, Elsevier, vol. 36(C), pages 491-502.
    45. Wang, Yudong & Wu, Chongfeng, 2013. "Are crude oil spot and futures prices cointegrated? Not always!," Economic Modelling, Elsevier, vol. 33(C), pages 641-650.
    46. Imtiaz Mohammad Sifat & Azhar Mohamad & Kevin Reinaldo Amin, 2021. "Intertemporal price discovery between stock index futures and spot markets: New evidence from high‐frequency data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 898-913, January.
    47. Carlotta Penone & Elisa Giampietri & Samuele Trestini, 2022. "Futures–spot price transmission in EU corn markets," Agribusiness, John Wiley & Sons, Ltd., vol. 38(3), pages 679-709, July.
    48. Wang, Fan & Tian, Lixin & Du, Ruijin & Dong, Gaogao, 2021. "Universal law in the crude oil market based on visibility graph algorithm and network structure," Resources Policy, Elsevier, vol. 70(C).
    49. Pradita Nareswari & Sigit S. Wibowo, 2020. "Global and Local Commodity Prices: A Further Look at the Indonesian Agricultural Commodities," Capital Markets Review, Malaysian Finance Association, vol. 28(1), pages 65-76.
    50. Nazlioglu, Saban, 2011. "World oil and agricultural commodity prices: Evidence from nonlinear causality," Energy Policy, Elsevier, vol. 39(5), pages 2935-2943, May.
    51. Derick D. Quintino & Sergio A. David & Carlos E. de F. Vian, 2017. "Analysis of the Relationship between Ethanol Spot and Futures Prices in Brazil," IJFS, MDPI, vol. 5(2), pages 1-10, April.
    52. Shao, Mingao & Hua, Yongjun, 2022. "Price discovery efficiency of China's crude oil futures: Evidence from the Shanghai crude oil futures market," Energy Economics, Elsevier, vol. 112(C).
    53. Ghassan, Hassan Belkacem & AlHajhoj, Hassan Rafdan, 2016. "Long run dynamic volatilities between OPEC and non-OPEC crude oil prices," Applied Energy, Elsevier, vol. 169(C), pages 384-394.
    54. Guglielmo Caporale & Davide Ciferri & Alessandro Girardi, 2010. "Time-varying spot and futures oil price dynamics," Quaderni del Dipartimento di Economia, Finanza e Statistica 75/2010, Università di Perugia, Dipartimento Economia.
    55. Chang, Chun-Ping & Lee, Chien-Chiang, 2015. "Do oil spot and futures prices move together?," Energy Economics, Elsevier, vol. 50(C), pages 379-390.
    56. Chevillon, Guillaume & Rifflart, Christine, 2009. "Physical market determinants of the price of crude oil and the market premium," Energy Economics, Elsevier, vol. 31(4), pages 537-549, July.
    57. Ding, Haoyuan & Kim, Hyung-Gun & Park, Sung Y., 2014. "Do net positions in the futures market cause spot prices of crude oil?," Economic Modelling, Elsevier, vol. 41(C), pages 177-190.
    58. Emmanuel Anoruo, 2011. "Testing for Linear and Nonlinear Causality between Crude Oil Price Changes and Stock Market Returns," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 4(3), pages 75-92, December.
    59. Ampofo, Gideon Kwaku Minua & Cheng, Jinhua & Asante, Daniel Akwasi & Bosah, Philip, 2020. "Total natural resource rents, trade openness and economic growth in the top mineral-rich countries: New evidence from nonlinear and asymmetric analysis," Resources Policy, Elsevier, vol. 68(C).
    60. Prashant Sharma & Geetika Arora & Prashant Gupta, 2020. "Evidences on Price Discovery in BRICS," International Journal of Economics and Financial Issues, Econjournals, vol. 10(6), pages 99-105.
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    62. Witold Orzeszko, 2021. "Nonlinear Causality between Crude Oil Prices and Exchange Rates: Evidence and Forecasting," Energies, MDPI, vol. 14(19), pages 1-16, September.
    63. Prabhat Mittal, 2024. "Forecasting of Crude Oil Prices Using Wavelet Decomposition Based Denoising with ARMA Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(2), pages 355-365, June.
    64. Lean, H.H. & McAleer, M.J. & Wong, W.-K., 2010. "Market Efficiency of Oil Spot and Futures: A Stochastic Dominance Approach," Econometric Institute Research Papers EI 2010-11, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    65. Xu Xiaojie, 2018. "Linear and Nonlinear Causality between Corn Cash and Futures Prices," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 16(2), pages 1-16, November.
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    2. Dicle Ozdemir, 2017. "Causal Relationship between Agricultural Exports and Exchange Rate: Evidence for India," Applied Economics and Finance, Redfame publishing, vol. 4(6), pages 36-41, November.
    3. Said Zamin Shah & Ahmad Zubaidi Baharumshah & Muzafar Shah Habibullah, 2019. "Dynamic Linkages and Volatility Transmissions between Macroeconomic Uncertainty and Performance: Evidence from South Asian Countries," Journal of South Asian Development, , vol. 14(3), pages 281-313, December.
    4. Muhsin KAR & Saban NAZLIOGLU & Huseyin AGIR, 2014. "Trade Openness, Financial Development, and Economic Growth in Turkey: Linear and Nonlinear Causality Analysis," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 8(1), pages 63-86.
    5. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    6. Xu, Xiaojie, 2014. "Price Discovery in U.S. Corn Cash and Futures Markets: The Role of Cash Market Selection," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169809, Agricultural and Applied Economics Association.
    7. Leonel Muinelo-Gallo & Ronald Miranda, 2020. "The Behaviour of Social Transfers over the Business Cycle: Empirical Evidence of Uruguay," Hacienda Pública Española / Review of Public Economics, IEF, vol. 233(2), pages 25-54, June.
    8. Soon, Siew-Voon & Baharumshah, Ahmad Zubaidi, 2021. "Exchange rates and fundamentals: Further evidence based on asymmetric causality test," International Economics, Elsevier, vol. 165(C), pages 67-84.
    9. Daniel Danau, 2018. "Prudence and preference for flexibility gain," Economics Working Paper Archive (University of Rennes & University of Caen) 2018-05, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS, revised May 2019.
    10. Gideon Minua Kwaku Ampofo & Prosper Basommi Laari & Emmanuel Opoku Ware & Williams Shaw, 2023. "Further investigation of the total natural resource rents and economic growth nexus in resource-abundant sub-Saharan African countries," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(1), pages 97-121, January.
    11. Maghyereh, Aktham & Abdoh, Hussein, 2021. "Time–frequency quantile dependence between Bitcoin and global equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    12. Xu Xiaojie, 2018. "Linear and Nonlinear Causality between Corn Cash and Futures Prices," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 16(2), pages 1-16, November.
    13. Maghyereh, Aktham & Awartani, Basel & Abdoh, Hussein, 2020. "The effects of investor emotions sentiments on crude oil returns: A time and frequency dynamics analysis," International Economics, Elsevier, vol. 162(C), pages 110-124.
    14. Douglas de Medeiros Franco, 2022. "Expectations, Economic Uncertainty, and Sentiment," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 26(5), pages 210029-2100.
    15. G. Bampinas & T. Panagiotidis, 2015. "On the relationship between oil and gold before and after financial crisis: Linear, nonlinear and time-varying causality testing," Working Paper series 15-04, Rimini Centre for Economic Analysis.
    16. Dajcman, Silvio & Festic, Mejra, 2012. "The Interdependence of the Stock Markets of Slovenia, The Czech Republic and Hungary with Some Developed European Stock Markets – The Effects of Joining the European Union and the Global Financial Cri," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 163-180, December.
    17. Pami Dua & Ritu Suri, 2019. "Interlinkages Between USD–INR, EUR–INR, GBP–INR and JPY–INR Exchange Rate Markets and the Impact of RBI Intervention," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(1_suppl), pages 102-136, April.
    18. Maghyereh, Aktham & Abdoh, Hussein, 2020. "The tail dependence structure between investor sentiment and commodity markets," Resources Policy, Elsevier, vol. 68(C).
    19. Grigoryev, Ruslan & Jaffry, Shabbar & Marchenko, German, 2012. "Investigation of the consequences of ignoring daily data non-synchronism in cross-market linkages: BRIC and developed countries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 26(2), pages 92-112.
    20. Syed Hassan & Sarosh Shabi & Taufiq Choudhry, 2018. "US Economic Uncertainty, EU Business Cycles and the Global Financial Crisis," Working Papers 2018-05, Swansea University, School of Management.
    21. Tan Le & Franck Martin & Duc Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Working Papers hal-01806733, HAL.
    22. Andreasson, Pierre & Bekiros, Stelios & Nguyen, Duc Khuong & Uddin, Gazi Salah, 2016. "Impact of speculation and economic uncertainty on commodity markets," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 115-127.
    23. Lei Wang & Provash Kumer Sarker & Elie Bouri, 2023. "Short- and Long-Term Interactions Between Bitcoin and Economic Variables: Evidence from the US," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1305-1330, April.
    24. Palazzi, Rafael Baptista & Figueiredo Pinto, Antonio Carlos & Klotzle, Marcelo Cabus & De Oliveira, Erick Meira, 2020. "Can we still blame index funds for the price movements in the agricultural commodities market?," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 84-93.
    25. Christos Kollias & Suzanna-Maria Paleologou & Panayiotis Tzeremes & Nickolaos Tzeremes, 2017. "Defence expenditure and economic growth in Latin American countries: evidence from linear and nonlinear causality tests," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 26(1), pages 1-25, December.
    26. Azizi, Firouzeh & Moradi, Fahimeh, . "Linear and Nonlinear Causality between Stock Market Volatility and the Business Cycle in Iran," Asian Journal of Applied Economics, Kasetsart University, Center for Applied Economics Research, vol. 26(1).
    27. Taamouti Abderrahim, 2015. "Stock market’s reaction to money supply: a nonparametric analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 669-689, December.
    28. Walid Mensi & Mobeen Ur Rehman & Muhammad Shafiullah & Khamis Hamed Al-Yahyaee & Ahmet Sensoy, 2021. "High frequency multiscale relationships among major cryptocurrencies: portfolio management implications," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-21, December.
    29. Mitica Pepi, 2022. "The Interdependence of the Stock Markets Developed in Central and Eastern- European Stock Markets - Represented by the Stock Indices," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 995-1000, Decembrie.
    30. De Vita, Glauco & Trachanas, Emmanouil, 2016. "‘Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India’ — A failed replication (negative Type 1 and Type 2)," Energy Economics, Elsevier, vol. 56(C), pages 150-160.
    31. Mirzosaid Sultonov, 2019. "Remittances, bilateral trade and linkage between foreign exchange markets: Evidence from the Commonwealth of Independent States (CIS)," International Journal of Economic Policy Studies, Springer, vol. 13(1), pages 65-74, January.
    32. Marinakis, Yorgos D. & White, Reilly & Walsh, Steven T., 2020. "Lotka–Volterra signals in ASEAN currency exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    33. Palazzi, Rafael Baptista & Júnior, Gerson de Souza Raimundo & Klotzle, Marcelo Cabus, 2021. "The dynamic relationship between bitcoin and the foreign exchange market: A nonlinear approach to test causality between bitcoin and currencies," Finance Research Letters, Elsevier, vol. 42(C).
    34. Xiaojie Xu, 2018. "Cointegration and price discovery in US corn cash and futures markets," Empirical Economics, Springer, vol. 55(4), pages 1889-1923, December.
    35. Chuliá, Helena & Fernández, Julián & Uribe, Jorge M., 2018. "Currency downside risk, liquidity, and financial stability," Journal of International Money and Finance, Elsevier, vol. 89(C), pages 83-102.

  11. Diks, C.G.H. & Dindo, P.D.E., 2006. "Informational differences and learning in an asset market with boundedly rational agents," CeNDEF Working Papers 06-11, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Valentyn Panchenko & Sergiy Gerasymchuk & Oleg V. Pavlov, 2013. "Asset Price Dynamics with Heterogeneous Beliefs and Local Network Interactions," Discussion Papers 2013-18, School of Economics, The University of New South Wales.
    2. Goldbaum, David & Panchenko, Valentyn, 2010. "Learning and adaptation's impact on market efficiency," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 635-653, December.
    3. Troy Tassier, 2013. "Handbook of Research on Complexity, by J. Barkley Rosser, Jr. and Edward Elgar," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 39(1), pages 132-133.
    4. Samuel Mayanja & Joseph M. Ntayi & John C. Munene & Waswa Balunywa & James R. K. Kagaari, 2021. "Informational differences and entrepreneurial networking among small and medium enterprises in Uganda," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 11(1), pages 563-577, December.
    5. Hommes, C.H., 2007. "Bounded Rationality and Learning in Complex Markets," CeNDEF Working Papers 07-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    6. Marc de Kamps & Daniel Ladley & Aistis Simaitis, 2012. "Heterogeneous Beliefs in Over-The-Counter Markets," Discussion Papers in Economics 13/03, Division of Economics, School of Business, University of Leicester, revised Sep 2013.
    7. Hommes, Cars, 2011. "The heterogeneous expectations hypothesis: Some evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 1-24, January.
    8. Michele Berardi, 2008. "Fundamentalists vs. chartists: learning and predictor choice dynamics," Centre for Growth and Business Cycle Research Discussion Paper Series 104, Economics, The University of Manchester.
    9. Xue, Yi & Gençay, Ramazan, 2012. "Hierarchical information and the rate of information diffusion," Journal of Economic Dynamics and Control, Elsevier, vol. 36(9), pages 1372-1401.
    10. Dieci, Roberto & Westerhoff, Frank, 2010. "Heterogeneous speculators, endogenous fluctuations and interacting markets: A model of stock prices and exchange rates," Journal of Economic Dynamics and Control, Elsevier, vol. 34(4), pages 743-764, April.
    11. Naimzada, Ahmad & Pireddu, Marina, 2015. "Real and financial interacting markets: A behavioral macro-model," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 111-131.
    12. De Grauwe, Paul & Rovira Kaltwasser, Pablo, 2012. "Animal spirits in the foreign exchange market," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1176-1192.
    13. Antonio Doria, Francisco, 2011. "J.B. Rosser Jr. , Handbook of Research on Complexity, Edward Elgar, Cheltenham, UK--Northampton, MA, USA (2009) 436 + viii pp., index, ISBN 978 1 84542 089 5 (cased)," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1-2), pages 196-204, April.
    14. Kaltwasser, Pablo Rovira, 2010. "Uncertainty about fundamentals and herding behavior in the FOREX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(6), pages 1215-1222.
    15. Ahmad Naimzada & Marina Pireddu, 2014. "Real and financial interacting oscillators: a behavioral macro-model with animal spirits," Working Papers 268, University of Milano-Bicocca, Department of Economics, revised Feb 2014.

  12. Diks, C.G.H. & Hommes, C.H. & Panchenko, V. & Weide, R. van der, 2006. "E&F Chaos: a user friendly software package for nonlinear economic dynamics," CeNDEF Working Papers 06-15, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Robert Calvert Jump & Cars Hommes & Paul Levine, 2018. "Learning, Heterogeneity, and Complexity in the New Keynesian Model," Working Papers 20181807, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    2. Valentyn Panchenko & Sergiy Gerasymchuk & Oleg V. Pavlov, 2013. "Asset Price Dynamics with Heterogeneous Beliefs and Local Network Interactions," Discussion Papers 2013-18, School of Economics, The University of New South Wales.
    3. Cars Hommes & Robert Calvert Jump & Paul Levine, 2017. "Internal rationalityuyuyuy, heterogeneity and complexity in the New Keynesian model," Working Papers 20171706, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    4. Alessia Cafferata & Marwil J. Dávila-Fernández & Serena Sordi, 2021. "(Ir)rational explorers in the financial jungle," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1157-1188, September.
    5. Charpe, Matthieu & Flaschel, Peter & Hartmann, Florian & Malikane, Christopher, 2014. "Segmented Labor Markets and the Distributive Cycle: A Roadmap towards Inclusive Growth," MPRA Paper 62832, University Library of Munich, Germany.
    6. Peter Flaschel & Florian Hartmann & Christopher Malikane & Christian Proaño, 2015. "A Behavioral Macroeconomic Model of Exchange Rate Fluctuations with Complex Market Expectations Formation," Computational Economics, Springer;Society for Computational Economics, vol. 45(4), pages 669-691, April.
    7. Luis-Felipe Zanna & Mr. Marco Airaudo, 2012. "Interest Rate Rules, Endogenous Cycles, and Chaotic Dynamics in Open Economies," IMF Working Papers 2012/121, International Monetary Fund.
    8. Waters, George A., 2009. "Chaos in the cobweb model with a new learning dynamic," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1201-1216, June.
    9. Airaudo, Marco, 2016. "Endogenous Stock Price Fluctuations with Dynamic Self-Control Preferences," School of Economics Working Paper Series 2016-2, LeBow College of Business, Drexel University.
    10. Florian Hartmann & Matthieu Charpe & Peter Flaschel & Roberto Veneziani, 2016. "A Basic Model of Real-Financial Market Interactions with Heterogeneous Opinion Dynamics," IEER Working Papers 104, Institute of Empirical Economic Research, Osnabrueck University, revised 26 May 2016.
    11. Matthieu Charpe & Peter Flaschel & Hans-Martin Krolzig & Christian Proaño & Willi Semmler & Daniele Tavani, 2015. "Credit-driven investment, heterogeneous labor markets and macroeconomic dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(1), pages 163-181, April.
    12. Fabio Lamantia & Anghel Negriu & Jan Tuinstra, 2018. "Technology choice in an evolutionary oligopoly game," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 335-356, November.
    13. Klaus Prettner, 2012. "Public education, technological change and economic prosperity: semi-endogenous growth revisited," PGDA Working Papers 9012, Program on the Global Demography of Aging.
    14. P. Luizi & F. Cruz & J. Graaf, 2010. "Assessing the Quality of Pseudo-Random Number Generators," Computational Economics, Springer;Society for Computational Economics, vol. 36(1), pages 57-67, June.
    15. Gilberto Tadeu Lima & Jaylson Jair Silveira, 2021. "Evolutionary microdynamics of employee profit sharing as productivity-enhancing device," Journal of Evolutionary Economics, Springer, vol. 31(2), pages 417-449, April.
    16. Bask, Mikael, 2007. "Long swings and chaos in the exchange rate in a DSGE model with a Taylor rule," Bank of Finland Research Discussion Papers 19/2007, Bank of Finland.
    17. Guo Feng & Liu Chong & Shi Qingling, 2019. "Smart or stupid depends on who is your counterpart: a cobweb model with heterogeneous expectations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(5), pages 1-17, December.
    18. Choudhary, M. Ali & Michael Orszag, J., 2008. "A cobweb model with local externalities," Journal of Economic Dynamics and Control, Elsevier, vol. 32(3), pages 821-847, March.
    19. Prettner, Klaus, 2012. "Public education and economic prosperity: Semi-endogenous growth revisited," ECON WPS - Working Papers in Economic Theory and Policy 02/2012, TU Wien, Institute of Statistics and Mathematical Methods in Economics, Economics Research Unit.
    20. Lamantia, F. & Negriu, A. & Tuinstra, J., 2016. "Evolutionary Cournot competition with endogenous technology choice: (in)stability and optimal policy," CeNDEF Working Papers 16-08, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    21. Xin, Baogui & Chen, Tong, 2011. "On a master-slave Bertrand game model," Economic Modelling, Elsevier, vol. 28(4), pages 1864-1870, July.
    22. Alessia Cafferata & Marwil J. Dávila-Fernández & Serena Sordi, 2020. "(Ir)rational explorers in the financial jungle: modelling Minsky with heterogeneous agents," Department of Economics University of Siena 819, Department of Economics, University of Siena.
    23. Mikhail Anufriev & Davide Radi & Fabio Tramontana, 2018. "Some reflections on past and future of nonlinear dynamics in economics and finance," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 91-118, November.

  13. Diks, C.G.H. & Wagener, F.O.O., 2006. "A weak bifurcation theory for discrete time stochastic dynamical systems," CeNDEF Working Papers 06-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Chiarella, Carl & He, Xue-Zhong & Zheng, Min, 2011. "An analysis of the effect of noise in a heterogeneous agent financial market model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 148-162, January.

  14. Diks, C.G.H. & Panchenko, V., 2006. "Rank-based entropy tests for serial independence," CeNDEF Working Papers 06-14, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Pál Rakonczai & László Márkus & András Zempléni, 2012. "Autocopulas: Investigating the Interdependence Structure of Stationary Time Series," Methodology and Computing in Applied Probability, Springer, vol. 14(1), pages 149-167, March.
    2. Luca Bagnato & Lucio De Capitani & Antonio Punzo, 2014. "Testing Serial Independence via Density-Based Measures of Divergence," Methodology and Computing in Applied Probability, Springer, vol. 16(3), pages 627-641, September.

  15. Diks, C.G.H. & Panchenko, V., 2004. "A note on the Hiemstra-Jones test for Granger non-causality," CeNDEF Working Papers 04-10, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. D. Hristu-Varsakelis & C. Kyrtsou, 2008. "Evidence for Nonlinear Asymmetric Causality in US Inflation, Metal, and Stock Returns," Discrete Dynamics in Nature and Society, Hindawi, vol. 2008, pages 1-7, May.
    2. Neto, David, 2022. "Revisiting spillovers between investor attention and cryptocurrency markets using noisy independent component analysis and transfer entropy," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    3. Dergiades, Theologos, 2012. "Do investors’ sentiment dynamics affect stock returns? Evidence from the US economy," Economics Letters, Elsevier, vol. 116(3), pages 404-407.
    4. Shahbaz, Muhammad & Shafiullah, Muhammad & Khalid, Usman & Song, Malin, 2020. "A nonparametric analysis of energy environmental Kuznets Curve in Chinese Provinces," Energy Economics, Elsevier, vol. 89(C).
    5. Apostolos Serletis & Khandokar Istiak, 2018. "Broker-dealer Leverage and the Stock Market," Open Economies Review, Springer, vol. 29(2), pages 215-222, April.
    6. Krzysztof Drachal, 2018. "Exchange Rate and Oil Price Interactions in Selected CEE Countries," Economies, MDPI, vol. 6(2), pages 1-21, May.
    7. Muhsin KAR & Saban NAZLIOGLU & Huseyin AGIR, 2014. "Trade Openness, Financial Development, and Economic Growth in Turkey: Linear and Nonlinear Causality Analysis," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 8(1), pages 63-86.
    8. Emmanuel Joel Aikins Abakah & Aviral Kumar Tiwari & Imhotep Paul Alagidede & Shawkat Hammoudeh, 2023. "Nonlinearity in the causality and systemic risk spillover between the OPEC oil and GCC equity markets: a pre- and post-financial crisis analysis," Empirical Economics, Springer, vol. 65(3), pages 1027-1103, September.
    9. Tarchella, Salma & Khalfaoui, Rabeh & Hammoudeh, Shawkat, 2024. "The safe haven, hedging, and diversification properties of oil, gold, and cryptocurrency for the G7 equity markets: Evidence from the pre- and post-COVID-19 periods," Research in International Business and Finance, Elsevier, vol. 67(PB).
    10. Mishra, Bibhuti Ranjan & Pradhan, Ashis Kumar & Tiwari, Aviral Kumar & Shahbaz, Muhammad, 2019. "The dynamic causality between gold and silver prices in India: Evidence using time-varying and non-linear approaches," Resources Policy, Elsevier, vol. 62(C), pages 66-76.
    11. Basse, Tobias & Desmyter, Steven & Saft, Danilo & Wegener, Christoph, 2023. "Leading indicators for the US housing market: New empirical evidence and thoughts about implications for risk managers and ESG investors," International Review of Financial Analysis, Elsevier, vol. 89(C).
    12. Li, Yang & Du, Qingfeng, 2024. "Oil price volatility and gold prices volatility asymmetric links with natural resources via financial market fluctuations: Implications for green recovery," Resources Policy, Elsevier, vol. 88(C).
    13. Yarovaya, Larisa & Zięba, Damian, 2022. "Intraday volume-return nexus in cryptocurrency markets: Novel evidence from cryptocurrency classification," Research in International Business and Finance, Elsevier, vol. 60(C).
    14. Parthajit Kayal & Moinak Maiti, 2023. "Examining the asymmetric information flow between pairs of gold, silver, and oil: a transfer entropy approach," SN Business & Economics, Springer, vol. 3(10), pages 1-22, October.
    15. Nick, Sebastian, 2013. "Price Formation and Intertemporal Arbitrage within a Low-Liquidity Framework: Empirical Evidence from European Natural Gas Markets," EWI Working Papers 2013-14, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    16. Stelios Bekiros, 2011. "Exchange Rates and Fundamentals: Co-Movement, Long-Run Relationships and Short-run Dynamics," Economics Working Papers ECO2011/21, European University Institute.
    17. Shahbaz, Muhammad & Shafiullah, Muhammad & Papavassiliou, Vassilios & Hammoudeh, Shawkat, 2017. "The CO2-Growth nexus revisited: A nonparametric analysis for G7 economies over nearly two centuries," MPRA Paper 79019, University Library of Munich, Germany, revised 07 May 2017.
    18. Matteo Bonato & Rangan Gupta & Chi Keung Marco Lau & Shixuan Wang, 2019. "Moments-Based Spillovers across Gold and Oil Markets," Working Papers 201966, University of Pretoria, Department of Economics.
    19. De Gooijer, Jan G. & Sivarajasingham, Selliah, 2008. "Parametric and nonparametric Granger causality testing: Linkages between international stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2547-2560.
    20. Rıza Demirer & Rangan Gupta & Tahir Suleman & Mark E. Wohar, 2017. "Time-Varying Rare Disaster Risks, Oil Returns and Volatility," Working Papers 201762, University of Pretoria, Department of Economics.
    21. Badshah, Ihsan & Bekiros, Stelios & Lucey, Brian M. & Uddin, Gazi Salah, 2018. "Asymmetric linkages among the fear index and emerging market volatility indices," Emerging Markets Review, Elsevier, vol. 37(C), pages 17-31.
    22. Xu, Xiaojie, 2014. "Price Discovery in U.S. Corn Cash and Futures Markets: The Role of Cash Market Selection," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169809, Agricultural and Applied Economics Association.
    23. Gurgul, Henryk & Lach, lukasz, 2011. "The role of coal consumption in the economic growth of the Polish economy in transition," Energy Policy, Elsevier, vol. 39(4), pages 2088-2099, April.
    24. Dergiades, Theologos & Martinopoulos, Georgios & Tsoulfidis, Lefteris, 2013. "Energy consumption and economic growth: Parametric and non-parametric causality testing for the case of Greece," Energy Economics, Elsevier, vol. 36(C), pages 686-697.
    25. Olivier Damette & Stephane Goutte & Qing Pei, 2020. "Climate and nomadic migration in a nonlinear world: evidence of the historical China," Climatic Change, Springer, vol. 163(4), pages 2055-2071, December.
    26. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch & Seong-Min Yoon, 2020. "OPEC News and Jumps in the Oil Market," Working Papers 202053, University of Pretoria, Department of Economics.
    27. Konstantinos Gkillas & Rangan Gupta & Mark E. Wohar, 2020. "Oil shocks and volatility jumps," Review of Quantitative Finance and Accounting, Springer, vol. 54(1), pages 247-272, January.
    28. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    29. Prasad Bal, Debi & Narayan Rath, Badri, 2015. "Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India," Energy Economics, Elsevier, vol. 51(C), pages 149-156.
    30. Balcilar, Mehmet & Bonato, Matteo & Demirer, Riza & Gupta, Rangan, 2018. "Geopolitical risks and stock market dynamics of the BRICS," Economic Systems, Elsevier, vol. 42(2), pages 295-306.
    31. Konstantinos Gkillas & Rangan Gupta & Mark E. Wohar, 2018. "Volatility Jumps: The Role of Geopolitical Risks," Working Papers 201805, University of Pretoria, Department of Economics.
    32. Ousama Ben-Salha & Abir Abid & Ghassen El Montasser, 2023. "Linear and Nonlinear Causal Linkages Between Exports and Growth in Next Eleven Economies," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(2), pages 1194-1226, June.
    33. Nazlioglu, Saban, 2011. "World oil and agricultural commodity prices: Evidence from nonlinear causality," Energy Policy, Elsevier, vol. 39(5), pages 2935-2943, May.
    34. Gurgul, Henryk & Lach, Łukasz, 2010. "The causal link between Polish stock market and key macroeconomic aggregates," MPRA Paper 52250, University Library of Munich, Germany.
    35. Bos, Martijn & Demirer, Riza & Gupta, Rangan & Tiwari, Aviral Kumar, 2018. "Oil returns and volatility: The role of mergers and acquisitions," Energy Economics, Elsevier, vol. 71(C), pages 62-69.
    36. Jain, Anshul & Biswal, Pratap Chandra, 2019. "Does internet search interest for gold move the gold spot, stock and exchange rate markets? A study from India," Resources Policy, Elsevier, vol. 61(C), pages 501-507.
    37. Gurgul, Henryk & Lach, Łukasz, 2010. "International trade and economic growth in the Polish economy," MPRA Paper 52286, University Library of Munich, Germany.
    38. Bekiros, Stelios D. & Diks, Cees G.H., 2008. "The nonlinear dynamic relationship of exchange rates: Parametric and nonparametric causality testing," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1641-1650, December.
    39. Xie, Zixiong & Chen, Shyh-Wei, 2019. "Exchange rates and fundamentals: A bootstrap panel data analysis," Economic Modelling, Elsevier, vol. 78(C), pages 209-224.
    40. Witold Orzeszko, 2021. "Nonlinear Causality between Crude Oil Prices and Exchange Rates: Evidence and Forecasting," Energies, MDPI, vol. 14(19), pages 1-16, September.
    41. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    42. Xu Xiaojie, 2018. "Linear and Nonlinear Causality between Corn Cash and Futures Prices," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 16(2), pages 1-16, November.
    43. Giovanni Bonaccolto & Massimiliano Caporin & Rangan Gupta, 2015. "The Dynamic Impact of Uncertainty in Causing and Forecasting the Distribution of Oil Returns and Risk," Working Papers 201564, University of Pretoria, Department of Economics.
    44. Lim, Shiok Ye & Ho, Chong Mun, 2013. "Nonlinearity in ASEAN-5 export-led growth model: Empirical evidence from nonparametric approach," Economic Modelling, Elsevier, vol. 32(C), pages 136-145.
    45. Atanu Ghoshray & Yurena Mendoza & Mercedes Monfort & Javier Ordoñez, 2018. "Re-assessing causality between energy consumption and economic growth," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-15, November.
    46. Junsheng Ha & Pei-Pei Tan & Kim-Leng Goh, 2018. "Linear and nonlinear causal relationship between energy consumption and economic growth in China: New evidence based on wavelet analysis," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-21, May.
    47. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
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    418. Chen, Bin-xia & Sun, Yan-lin, 2024. "Financial market connectedness between the U.S. and China: A new perspective based on non-linear causality networks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    419. Lin, Ling & Kuang, Yuanpei & Jiang, Yong & Su, Xianfang, 2019. "Assessing risk contagion among the Brent crude oil market, London gold market and stock markets: Evidence based on a new wavelet decomposition approach," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    420. Josué M. Polanco-Martínez & Luis M. Abadie, 2016. "Analyzing Crude Oil Spot Price Dynamics versus Long Term Future Prices: A Wavelet Analysis Approach," Energies, MDPI, vol. 9(12), pages 1-19, December.
    421. Tang, Yumei & Chen, Xihui Haviour & Sarker, Provash Kumer & Baroudi, Sarra, 2023. "Asymmetric effects of geopolitical risks and uncertainties on green bond markets," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    422. Bu, Hui & Tang, Wenjin & Wu, Junjie, 2019. "Time-varying comovement and changes of comovement structure in the Chinese stock market: A causal network method," Economic Modelling, Elsevier, vol. 81(C), pages 181-204.
    423. Mohammad Dulal Miah & Muhammad Shafiullah & Md. Samsul Alam, 2024. "The effect of financial stress on renewable energy consumption: evidence from US data," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(10), pages 26623-26646, October.
    424. Ogali, Oscar I.O. & Okoro, Emeka E. & Olafuyi, Saburi G., 2023. "Assessing consensus on nexus between natural gas consumption and economic growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    425. Liu, Li & Wan, Jieqiu, 2012. "The relationships between Shanghai stock market and CNY/USD exchange rate: New evidence based on cross-correlation analysis, structural cointegration and nonlinear causality test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 6051-6059.
    426. He, Yongda & Lin, Boqiang, 2019. "Regime differences and industry heterogeneity of the volatility transmission from the energy price to the PPI," Energy, Elsevier, vol. 176(C), pages 900-916.
    427. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2019. "Dynamics of oil price, precious metal prices and the exchange rate in the long-run," Energy Economics, Elsevier, vol. 84(C).

  17. Diks, C.G.H. & Weide, R. van der, 2003. "Heterogeneity as a natural source of randomness," CeNDEF Working Papers 03-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. 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.
    2. Schmitt, Noemi & Westerhoff, Frank, 2015. "Managing rational routes to randomness," Journal of Economic Behavior & Organization, Elsevier, vol. 116(C), pages 157-173.
    3. Cars Hommes & Florian Wagener, 2008. "Complex Evolutionary Systems in Behavioral Finance," Tinbergen Institute Discussion Papers 08-054/1, Tinbergen Institute.
    4. Diks, C.G.H. & Weide, R. van der, 2003. "Herding, A-synchronous Updating and Heterogeneity in Memory in a CBS," CeNDEF Working Papers 03-06, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    5. Michele Berardi, 2018. "Discrete beliefs space and equilibrium: a cautionary note," Centre for Growth and Business Cycle Research Discussion Paper Series 242, Economics, The University of Manchester.
    6. Brock,W.A. & Xepapadeas,A., 2005. "Optimal control and spatial heterogeneity : pattern formation in economic-ecological models," Working papers 11, Wisconsin Madison - Social Systems.
    7. Orlando Gomes, 2004. "A Continuous-Time Asset Pricing Model with Boundedly Rational Heterogeneous Agents," Finance 0409055, University Library of Munich, Germany.
    8. Orlando Gomes, . "Volatility, Heterogeneous Agents and Chaos," The Electronic Journal of Evolutionary Modeling and Economic Dynamics, IFReDE - Université Montesquieu Bordeaux IV.
    9. 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.
    10. Cees Diks & Roy van der Weide, 2003. "Herding, A-synchronous Updating and Heterogeneity in Memory in a CBS," Tinbergen Institute Discussion Papers 03-103/1, Tinbergen Institute.
    11. Kai Li, 2014. "Asset Price Dynamics with Heterogeneous Beliefs and Time Delays," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2014, January-A.
    12. Orlando Gomes, 2004. "Optimal Monetary Policy under Heterogeneous Expectations," Macroeconomics 0409023, University Library of Munich, Germany.
    13. Massaro, Domenico, 2013. "Heterogeneous expectations in monetary DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 680-692.
    14. Park, Beum-Jo, 2011. "Asymmetric herding as a source of asymmetric return volatility," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2657-2665, October.

  18. Diks, C.G.H. & Weide, R. van der, 2003. "Herding, A-synchronous Updating and Heterogeneity in Memory in a CBS," CeNDEF Working Papers 03-06, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Noemi Schmitt & Frank Westerhoff, 2017. "Heterogeneity, spontaneous coordination and extreme events within large-scale and small-scale agent-based financial market models," Journal of Evolutionary Economics, Springer, vol. 27(5), pages 1041-1070, November.
    2. Valentyn Panchenko & Sergiy Gerasymchuk & Oleg V. Pavlov, 2013. "Asset Price Dynamics with Heterogeneous Beliefs and Local Network Interactions," Discussion Papers 2013-18, School of Economics, The University of New South Wales.
    3. Barbara Annicchiarico & Fabio Di Dio & Francesca Diluiso, 2022. "Climate Actions, Market Beliefs and Monetary Policy," CEIS Research Paper 535, Tor Vergata University, CEIS, revised 25 Mar 2022.
    4. Gontis, V. & Havlin, S. & Kononovicius, A. & Podobnik, B. & Stanley, H.E., 2016. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1091-1102.
    5. Tatiana Kiseleva, 2016. "Heterogeneous Beliefs and Climate Catastrophes," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 65(3), pages 599-622, November.
    6. Cornea, A. & Hommes, C.H. & Massaro, D., 2012. "Behavioral Heterogeneity in U.S. Inflation Dynamics," CeNDEF Working Papers 12-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    7. Bao, Te & Hommes, Cars, 2019. "When speculators meet suppliers: Positive versus negative feedback in experimental housing markets," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.
    8. Hommes, Cars & Li, Kai & Wagener, Florian, 2022. "Production delays and price dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 341-362.
    9. Roberto Veneziani & Luca Zamparelli & Reiner Franke & Frank Westerhoff, 2017. "Taking Stock: A Rigorous Modelling Of Animal Spirits In Macroeconomics," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1152-1182, December.
    10. LeBaron, Blake, 2012. "Heterogeneous gain learning and the dynamics of asset prices," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 424-445.
    11. Franke, Reiner, 2014. "Aggregate sentiment dynamics: A canonical modelling approach and its pleasant nonlinearities," Structural Change and Economic Dynamics, Elsevier, vol. 31(C), pages 64-72.
    12. Elton Beqiraj & Giovanni Di Bartolomeo & Marco Di Pietro & Carolina Serpieri, 2018. "Bounded-rationality and heterogeneous agents: Long or short forecasters?," JRC Research Reports JRC111392, Joint Research Centre.
    13. 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.
    14. Dieci, Roberto & Mignot, Sarah & Schmitt, Noemi & Westerhoff, Frank H., 2022. "Production delays, supply distortions and endogenous price dynamics," BERG Working Paper Series 182, Bamberg University, Bamberg Economic Research Group.
    15. Schmitt, Noemi & Westerhoff, Frank, 2015. "Managing rational routes to randomness," Journal of Economic Behavior & Organization, Elsevier, vol. 116(C), pages 157-173.
    16. 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.
    17. Michael Wegener & Frank Westerhoff, 2012. "Evolutionary competition between prediction rules and the emergence of business cycles within Metzler’s inventory model," Journal of Evolutionary Economics, Springer, vol. 22(2), pages 251-273, April.
    18. Te Bao & Cars Hommes & Joep Sonnemans & Jan Tuinstra, 2012. "Individual Expectations, Limited Rationality and Aggregate Outcomes," Tinbergen Institute Discussion Papers 12-016/1, Tinbergen Institute.
    19. Colasante, Annarita & Alfarano, Simone & Camacho-Cuena, Eva, 2019. "Heuristic Switching Model and Exploration-Explotation Algorithm to describe long-run expectations in LtFEs: a comparison," MPRA Paper 92391, University Library of Munich, Germany.
    20. Hommes, C.H. & Zeppini Rossi, P., 2013. "Innovate or Imitate? Behavioural Technological Change," CeNDEF Working Papers 13-18, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    21. Troy Tassier, 2013. "Handbook of Research on Complexity, by J. Barkley Rosser, Jr. and Edward Elgar," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 39(1), pages 132-133.
    22. Colucci, Domenico & Doni, Nicola & Ricchiuti, Giorgio & Valori, Vincenzo, 2022. "Market dynamics with a state-owned dominant firm and a competitive fringe," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    23. Vygintas Gontis & Shlomo Havlin & Aleksejus Kononovicius & Boris Podobnik & H. Eugene Stanley, 2015. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Papers 1507.05203, arXiv.org, revised Oct 2016.
    24. Anufriev, Mikhail & Panchenko, Valentyn, 2009. "Asset prices, traders' behavior and market design," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1073-1090, May.
    25. Hommes, C.H., 2007. "Bounded Rationality and Learning in Complex Markets," CeNDEF Working Papers 07-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    26. Cars Hommes & Florian Wagener, 2008. "Complex Evolutionary Systems in Behavioral Finance," Tinbergen Institute Discussion Papers 08-054/1, Tinbergen Institute.
    27. Papadopoulos, Georgios, 2019. "Income inequality, consumption, credit and credit risk in a data-driven agent-based model," Journal of Economic Dynamics and Control, Elsevier, vol. 104(C), pages 39-73.
    28. Ya-Chi Huang & Chueh-Yung Tsao, 2018. "Evolutionary Frequency and Forecasting Accuracy: Simulations Based on an Agent-Based Artificial Stock Market," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 79-104, June.
    29. Hommes, Cars, 2011. "The heterogeneous expectations hypothesis: Some evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 1-24, January.
    30. Elton Beqiraj & Giovanni Di Bartolomeo & Marco Di Pietro & Carolina Serpieri, 2020. "Bounded rationality and heterogeneous expectations: Euler versus anticipated-utility approach," Journal of Economics, Springer, vol. 130(3), pages 249-273, August.
    31. Akvile Bertasiute & Domenico Massaro & Matthias Weber, 2018. "The behavioral economics of currency unions: Economic integration and monetary policy," Bank of Lithuania Working Paper Series 49, Bank of Lithuania.
    32. Gerasymchuk, S. & Pavlov, O.V., 2010. "Asset Price Dynamics with Local Interactions under Heterogeneous Beliefs," CeNDEF Working Papers 10-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    33. Colasante, Annarita & Alfarano, Simone & Camacho Cuena, Eva & Gallegati, Mauro, 2017. "Long-run expectations in a Learning-to-Forecast-Experiment: a simulation approach," MPRA Paper 77618, University Library of Munich, Germany.
    34. Hommes, C.H. & Kiseleva, T. & Kuznetsov, Y. & Verbic, M., 2009. "Is more memory in evolutionary selection (de)stabilizing?," CeNDEF Working Papers 09-07, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    35. Zeppini Rossi, P., 2013. "A Discrete Choice Model of Transitions to Sustainable Technologies," CeNDEF Working Papers 13-11, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    36. Vygintas Gontis & Aleksejus Kononovicius, 2017. "The consentaneous model of the financial markets exhibiting spurious nature of long-range memory," Papers 1712.05121, arXiv.org, revised Feb 2018.
    37. Cees Diks & Cars Hommes & Valentyn Panchenko & Roy Weide, 2008. "E&F Chaos: A User Friendly Software Package for Nonlinear Economic Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 32(1), pages 221-244, September.
    38. Serkov, Leonid & Krasnykh, Sergey, 2022. "Analysis of the external shocks impact on the behavior of agents with limited expectations: The case of Russian economy," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 67, pages 97-120.
    39. Agliari, Anna & Hommes, Cars H. & Pecora, Nicolò, 2016. "Path dependent coordination of expectations in asset pricing experiments: A behavioral explanation," Journal of Economic Behavior & Organization, Elsevier, vol. 121(C), pages 15-28.
    40. Gontis, V. & Kononovicius, A., 2018. "The consentaneous model of the financial markets exhibiting spurious nature of long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1075-1083.
    41. Kukacka, Jiri & Barunik, Jozef, 2013. "Behavioural breaks in the heterogeneous agent model: The impact of herding, overconfidence, and market sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5920-5938.
    42. Anufriev, M. & Hommes, C.H. & Philipse, R., 2010. "Evolutionary Selection of Expectations in Positive and Negative Feedback Markets," CeNDEF Working Papers 10-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    43. Cars Hommes & Domenico Massaro & Matthias Weber, 2015. "Monetary Policy under Behavioral Expectations: Theory and Experiment," Tinbergen Institute Discussion Papers 15-087/II, Tinbergen Institute.
    44. Giovanni Di Bartolomeo & Carolina Serpieri, 2018. "Robust Optimal Policies in a Behavioural New Keynesian Model," JRC Research Reports JRC111603, Joint Research Centre.
    45. Bekiros, Stelios & Jlassi, Mouna & Lucey, Brian & Naoui, Kamel & Uddin, Gazi Salah, 2017. "Herding behavior, market sentiment and volatility: Will the bubble resume?," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 107-131.
    46. Paolo Zeppini, 2014. "A discrete choice model of transitions to sustainable technologies: speed limits and optimal monetary policies," Department of Economics Working Papers 28/14, University of Bath, Department of Economics.
    47. Assenza, T. & Brock, W.A. & Hommes, C.H., 2012. "Animal Spirits, Heterogeneous Expectations and the Amplification and Duration of Crises," CeNDEF Working Papers 12-07, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    48. 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.
    49. Hommes, C.H. & Wagener, F.O.O., 2009. "Does eductive stability imply evolutionary stability?," CeNDEF Working Papers 09-10, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    50. Kai Li, 2014. "Asset Price Dynamics with Heterogeneous Beliefs and Time Delays," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2014, January-A.
    51. Domenico Colucci & Matteo Vigna & Vincenzo Valori, 2022. "Large and uncertain heterogeneity of expectations: stability of equilibrium from a policy maker standpoint," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(1), pages 319-348, January.
    52. Raja Mazhar Hameed & Abdul Rafae Mazhar Raja & Nida Zahid, 2023. "Herding Spillover among the Stock Markets: Pakistan & China Covering Covid-19 and Its Repercussions," Journal of Policy Research (JPR), Research Foundation for Humanity (RFH), vol. 9(2), pages 257-267.
    53. Zhu, Jiahua & Bao, Te & Chia, Wai Mun, 2021. "Evolutionary selection of forecasting and quantity decision rules in experimental asset markets," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 363-404.
    54. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    55. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    56. Mikhail Anufriev & Cars Hommes, 2012. "Evolutionary Selection of Individual Expectations and Aggregate Outcomes in Asset Pricing Experiments," American Economic Journal: Microeconomics, American Economic Association, vol. 4(4), pages 35-64, November.
    57. Antonio Doria, Francisco, 2011. "J.B. Rosser Jr. , Handbook of Research on Complexity, Edward Elgar, Cheltenham, UK--Northampton, MA, USA (2009) 436 + viii pp., index, ISBN 978 1 84542 089 5 (cased)," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1-2), pages 196-204, April.
    58. Roberto Dieci & Xue-Zhong He, 2021. "Cross-section instability in financial markets: impatience, extrapolation, and switching," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 727-754, December.
    59. Lines, Marji & Westerhoff, Frank, 2009. "Effects of inflation expectations on macroeconomic dynamics: Extrapolative versus regressive expectations," BERG Working Paper Series 68, Bamberg University, Bamberg Economic Research Group.
    60. Bazzana, Davide & Gilioli, Gianni & Simane, Belay & Zaitchik, Benjamin, 2021. "Analyzing constraints in the water-energy-food nexus: The case of eucalyptus plantation in Ethiopia," Ecological Economics, Elsevier, vol. 180(C).
    61. Bazzana, Davide & Zaitchik, Benjamin & Gilioli, Gianni, 2020. "Impact of water and energy infrastructure on local well-being: an agent-based analysis of the water-energy-food nexus," Structural Change and Economic Dynamics, Elsevier, vol. 55(C), pages 165-176.
    62. Massaro, Domenico, 2013. "Heterogeneous expectations in monetary DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 680-692.
    63. Park, Beum-Jo, 2011. "Asymmetric herding as a source of asymmetric return volatility," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2657-2665, October.
    64. Hommes, Cars, 2018. "Carl’s nonlinear cobweb," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 7-20.
    65. Jia-Ping Huang & Yang Zhang & Juanxi Wang, 2023. "Dynamic effects of social influence on asset prices," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 671-699, July.

  19. Diks, C.G.H. & Weide, R. van der, 2002. "Continuous Beliefs Dynamics," CeNDEF Working Papers 02-11, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Brock, W.A. & Hommes, C.H. & Wagener, F.O.O., 2002. "Evolutionary dynamics in markets with many trader types," CeNDEF Working Papers 02-10, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    2. Michele Berardi, 2018. "Discrete beliefs space and equilibrium: a cautionary note," Centre for Growth and Business Cycle Research Discussion Paper Series 242, Economics, The University of Manchester.
    3. Massaro, D., 2012. "Regime shifts: early warnings," CeNDEF Working Papers 12-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    4. Massaro, Domenico, 2013. "Heterogeneous expectations in monetary DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 680-692.

  20. Diks, C.G.H., 2002. "Detecting serial dependence in tail events: A test dual to BDS test," CeNDEF Working Papers 02-09, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Evzen Kocenda & Lubos Briatka, 2004. "Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power," Econometrics 0409001, University Library of Munich, Germany.
    2. Luo, Wenya & Bai, Zhidong & Zheng, Shurong & Hui, Yongchang, 2020. "A modified BDS test," Statistics & Probability Letters, Elsevier, vol. 164(C).
    3. Evzen Kocenda & Lubos Briatka, 2005. "Optimal Range for the iid Test Based on Integration Across the Correlation Integral," Econometric Reviews, Taylor & Francis Journals, vol. 24(3), pages 265-296.

  21. Diks, C.G.H. & Manzan, S., 2001. "Tests for serial independence and linearity based on correlation integrals," CeNDEF Working Papers 01-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Diks Cees & Panchenko Valentyn, 2008. "Rank-based Entropy Tests for Serial Independence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-21, March.
    2. Angeliki Papana & Catherine Kyrtsou & Dimitris Kugiumtzis & Cees Diks, 2017. "Assessment of resampling methods for causality testing: A note on the US inflation behavior," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-20, July.
    3. Papadopoulos, G. & Kugiumtzis, D., 2015. "Estimation of connectivity measures in gappy time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 387-398.
    4. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    5. Lanh Tran & Ba Chu & Chunfeng Huang & Kim P. Huynh, 2014. "Adaptive permutation tests for serial independence," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(3), pages 183-208, August.
    6. Gao, Wei & Zhao, Hongxia, 2013. "Conditional independence graph for nonlinear time series and its application to international financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2460-2469.
    7. Kugiumtzis Dimitris, 2008. "Evaluation of Surrogate and Bootstrap Tests for Nonlinearity in Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-26, March.

  22. Diks, C.G.H. & Mudelsee, M., 2000. "Redundancies in the Earth's climatological time series," CeNDEF Working Papers 00-07, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Fernández, Isabel & Hernández, Carmen N. & Pacheco, José M., 2003. "Is the North Atlantic Oscillation just a pink noise?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 705-714.

  23. Diks, C.G.H., 1999. "Consistent Testing for Serial Independence," CeNDEF Working Papers 99-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Diks, C.G.H. & Manzan, S., 2001. "Tests for serial independence and linearity based on correlation integrals," CeNDEF Working Papers 01-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    2. Cees Diks & Sebastiano Manzan, 2001. "Tests for Serial Independence and Linearity based on Correlation Integrals," Tinbergen Institute Discussion Papers 01-085/1, Tinbergen Institute.

Articles

  1. Diks, Cees & Panchenko, Valentyn & Sokolinskiy, Oleg & van Dijk, Dick, 2014. "Comparing the accuracy of multivariate density forecasts in selected regions of the copula support," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 79-94.

    Cited by:

    1. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    2. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    3. Jie Cheng, 2024. "Evaluating Density Forecasts Using Weighted Multivariate Scores in a Risk Management Context," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3617-3643, December.
    4. C. Alexander & M. Coulon & Y. Han & X. Meng, 2024. "Evaluating the discrimination ability of proper multi-variate scoring rules," Annals of Operations Research, Springer, vol. 334(1), pages 857-883, March.
    5. Diks, Cees & Fang, Hao, 2020. "Comparing density forecasts in a risk management context," International Journal of Forecasting, Elsevier, vol. 36(2), pages 531-551.
    6. Anufriev, Mikhail & Panchenko, Valentyn, 2015. "Connecting the dots: Econometric methods for uncovering networks with an application to the Australian financial institutions," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 241-255.
    7. Oleg Sokolinskiy, 2020. "Conditional dependence in post-crisis markets: dispersion and correlation skew trades," Review of Quantitative Finance and Accounting, Springer, vol. 55(2), pages 389-426, August.
    8. Collins, Sean & Gallagher, Emily, 2016. "Assessing the credit risk of money market funds during the eurozone crisis," Journal of Financial Stability, Elsevier, vol. 25(C), pages 150-165.
    9. Chiang, I-Hsuan Ethan & Liao, Yin & Zhou, Qing, 2021. "Modeling the cross-section of stock returns using sensible models in a model pool," Journal of Empirical Finance, Elsevier, vol. 60(C), pages 56-73.
    10. Aslanidis, Nektarios & Martinez, Oscar, 2021. "Correlation regimes in international equity and bond returns," Economic Modelling, Elsevier, vol. 97(C), pages 397-410.
    11. Xiaochun Meng & James W. Taylor & Souhaib Ben Taieb & Siran Li, 2020. "Scores for Multivariate Distributions and Level Sets," Papers 2002.09578, arXiv.org, revised Jun 2023.

  2. Diks, Cees & Hommes, Cars & Zeppini, Paolo, 2013. "More memory under evolutionary learning may lead to chaos," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 808-812.

    Cited by:

    1. Tapia Cortez, Carlos A. & Hitch, Michael & Sammut, Claude & Coulton, Jeff & Shishko, Robert & Saydam, Serkan, 2018. "Determining the embedding parameters governing long-term dynamics of copper prices," Chaos, Solitons & Fractals, Elsevier, vol. 111(C), pages 186-197.
    2. Xu, Liang & Cao, Xianbin & Du, Wenbo & Li, Yumeng, 2018. "Effects of taxation on the evolution of cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 113(C), pages 63-68.
    3. He, Kaijian & Xu, Yang & Zou, Yingchao & Tang, Ling, 2015. "Electricity price forecasts using a Curvelet denoising based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 425(C), pages 1-9.
    4. Fabio Lamantia & Anghel Negriu & Jan Tuinstra, 2018. "Technology choice in an evolutionary oligopoly game," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 335-356, November.
    5. Agliari, Anna & Naimzada, Ahmad & Pecora, Nicolò, 2017. "Dynamic effects of memory in a cobweb model with competing technologies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 340-350.
    6. Kukacka, Jiri & Barunik, Jozef, 2013. "Behavioural breaks in the heterogeneous agent model: The impact of herding, overconfidence, and market sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5920-5938.
    7. Cavalli, Fausto & Naimzada, Ahmad, 2015. "A tâtonnement process with fading memory, stabilization and optimal speed of convergence," Chaos, Solitons & Fractals, Elsevier, vol. 79(C), pages 116-129.
    8. He, Kaijian & Lu, Xingjing & Zou, Yingchao & Keung Lai, Kin, 2015. "Forecasting metal prices with a curvelet based multiscale methodology," Resources Policy, Elsevier, vol. 45(C), pages 144-150.
    9. Lamantia, F. & Negriu, A. & Tuinstra, J., 2016. "Evolutionary Cournot competition with endogenous technology choice: (in)stability and optimal policy," CeNDEF Working Papers 16-08, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    10. Mikhail Anufriev & Davide Radi & Fabio Tramontana, 2018. "Some reflections on past and future of nonlinear dynamics in economics and finance," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 91-118, November.

  3. Jan G. De Gooijer & Cees G. H. Diks & Łukasz T. Gątarek, 2012. "Information Flows Around the Globe: Predicting Opening Gaps from Overnight Foreign Stock Price Patterns," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(1), pages 23-44, March.
    See citations under working paper version above.
  4. Diks, Cees & Panchenko, Valentyn & van Dijk, Dick, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Journal of Econometrics, Elsevier, vol. 163(2), pages 215-230, August.
    See citations under working paper version above.
  5. Diks, Cees & Panchenko, Valentyn & van Dijk, Dick, 2010. "Out-of-sample comparison of copula specifications in multivariate density forecasts," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1596-1609, September.
    See citations under working paper version above.
  6. Diks Cees & Panchenko Valentyn, 2008. "Rank-based Entropy Tests for Serial Independence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-21, March.
    See citations under working paper version above.
  7. Bekiros, Stelios D. & Diks, Cees G.H., 2008. "The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality," Energy Economics, Elsevier, vol. 30(5), pages 2673-2685, September.
    See citations under working paper version above.
  8. Diks, Cees & Dindo, Pietro, 2008. "Informational differences and learning in an asset market with boundedly rational agents," Journal of Economic Dynamics and Control, Elsevier, vol. 32(5), pages 1432-1465, May.
    See citations under working paper version above.
  9. Cees Diks & Cars Hommes & Valentyn Panchenko & Roy Weide, 2008. "E&F Chaos: A User Friendly Software Package for Nonlinear Economic Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 32(1), pages 221-244, September.
    See citations under working paper version above.
  10. Bekiros, Stelios D. & Diks, Cees G.H., 2008. "The nonlinear dynamic relationship of exchange rates: Parametric and nonparametric causality testing," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1641-1650, December.
    See citations under working paper version above.
  11. Diks, Cees, 2006. "Comments on "Global sunspots in OLG models"," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 46-50, March.

    Cited by:

    1. Kyrtsou, Catherine, 2008. "Re-examining the sources of heteroskedasticity: The paradigm of noisy chaotic models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6785-6789.

  12. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    See citations under working paper version above.
  13. Diks Cees & Panchenko Valentyn, 2005. "A Note on the Hiemstra-Jones Test for Granger Non-causality," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-9, June.
    See citations under working paper version above.
  14. Diks, Cees & van der Weide, Roy, 2005. "Herding, a-synchronous updating and heterogeneity in memory in a CBS," Journal of Economic Dynamics and Control, Elsevier, vol. 29(4), pages 741-763, April.
    See citations under working paper version above.
  15. Diks, Cees, 2003. "Detecting serial dependence in tail events: a test dual to the BDS test," Economics Letters, Elsevier, vol. 79(3), pages 319-324, June.
    See citations under working paper version above.
  16. Diks Cees & Manzan Sebastiano, 2002. "Tests for Serial Independence and Linearity Based on Correlation Integrals," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(2), pages 1-22, July.
    See citations under working paper version above.
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