IDEAS home Printed from https://ideas.repec.org/r/spr/empeco/v33y2007i2p231-244.html
   My bibliography  Save this item

Commodity price cycles and heterogeneous speculators: a STAR–GARCH model

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Fischer, Thomas, 2011. "News reaction in financial markets within a behavioral finance model with heterogeneous agents," Darmstadt Discussion Papers in Economics 205, Darmstadt University of Technology, Department of Law and Economics.
  2. Aït-Youcef, Camille & Joëts, Marc, 2024. "The role of index traders in the financialization of commodity markets: A behavioral finance approach," Energy Economics, Elsevier, vol. 136(C).
  3. Mohamed CHIKHI & Claude DIEBOLT, 2022. "Testing the weak form efficiency of the French ETF market with the LSTAR-ANLSTGARCH approach using a semiparametric estimation," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 13, pages 228-253, June.
  4. Wen, Shaobo & An, Haizhong & Chen, Zhihua & Liu, Xueyong, 2017. "Driving factors of interactions between the exchange rate market and the commodity market: A wavelet-based complex network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 299-308.
  5. Joëts, Marc, 2015. "Heterogeneous beliefs, regret, and uncertainty: The role of speculation in energy price dynamics," European Journal of Operational Research, Elsevier, vol. 247(1), pages 204-215.
  6. Maximo Camacho & Gabriel Perez-Quiros, 2014. "Commodity Prices and the Business Cycle in Latin America: Living and Dying by Commodities?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(2), pages 110-137, March.
  7. Kazi Abrar Hossain & Syed Abul Basher & A.K. Enamul Haque, 2018. "Quantifying the impact of Ramadan on global raw sugar prices," International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing Limited, vol. 11(4), pages 510-528, June.
  8. Cifarelli, Giulio & Paesani, Paolo, 2017. "On the difficulty of interpreting market behaviour in an uncertain world: the case of oil futures pricing between 2003 and 2016," MPRA Paper 84009, University Library of Munich, Germany.
  9. Stephanie-Carolin Grosche, 2014. "What Does Granger Causality Prove? A Critical Examination of the Interpretation of Granger Causality Results on Price Effects of Index Trading in Agricultural Commodity Markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 279-302, June.
  10. Murat Midilic, 2016. "Estimation Of Star-Garch Models With Iteratively Weighted Least Squares," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 16/918, Ghent University, Faculty of Economics and Business Administration.
  11. Giulio Cifarelli and Paolo Paesani, 2021. "Navigating the Oil Bubble: A Non-linear Heterogeneous-agent Dynamic Model of Futures Oil Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
  12. Zhenxi Chen & Stefan Reitz, 2020. "Dynamics of the European sovereign bonds and the identification of crisis periods," Empirical Economics, Springer, vol. 58(6), pages 2761-2781, June.
  13. Cifarelli, Giulio & Paladino, Giovanna, 2015. "A dynamic model of hedging and speculation in the commodity futures markets," Journal of Financial Markets, Elsevier, vol. 25(C), pages 1-15.
  14. Baur, Dirk G. & Glover, Kristoffer J., 2014. "Heterogeneous expectations in the gold market: Specification and estimation," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 116-133.
  15. Sigl-Grüb, C. & Schiereck, D., 2010. "Speculation and Nonlinear Price Dynamics in Commodity Futures Markets," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56603, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
  16. Reitz Stefan & Slopek Ulf, 2009. "Non-Linear Oil Price Dynamics: A Tale of Heterogeneous Speculators?," German Economic Review, De Gruyter, vol. 10(3), pages 270-283, August.
  17. Chatterjee, Snehamoy & Sethi, Manas Ranjan & Asad, Mohammad Waqar Ali, 2016. "Production phase and ultimate pit limit design under commodity price uncertainty," European Journal of Operational Research, Elsevier, vol. 248(2), pages 658-667.
  18. Frijns, Bart & Lehnert, Thorsten & Zwinkels, Remco C.J., 2010. "Behavioral heterogeneity in the option market," Journal of Economic Dynamics and Control, Elsevier, vol. 34(11), pages 2273-2287, November.
  19. Murat Midiliç, 2020. "Estimation of STAR–GARCH Models with Iteratively Weighted Least Squares," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 87-117, January.
  20. Lof, Matthijs, 2012. "Heterogeneity in stock prices: A STAR model with multivariate transition function," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1845-1854.
  21. 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.
  22. Jawadi, Fredj & Ftiti, Zied & Hdia, Mouna, 2017. "Assessing efficiency and investment opportunities in commodities: A time series and portfolio simulations approach," Economic Modelling, Elsevier, vol. 64(C), pages 567-588.
  23. Mohamed Chikhi & Claude Diebolt, 2019. "Testing Nonlinearity through a Logistic Smooth Transition AR Model with Logistic Smooth Transition GARCH Errors," Working Papers 03-19, Association Française de Cliométrie (AFC).
  24. Giulio Cifarelli, 2023. "Commodity Pricing Volatility Shifts in a Highly Turbulent Time Period. A Time-varying Transition Probability Markov Switching Analysis," Working Papers - Economics wp2023_11.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
  25. David Ubilava, 2012. "Modeling Nonlinearities in the U.S. Soybean‐to‐Corn Price Ratio: A Smooth Transition Autoregression Approach," Agribusiness, John Wiley & Sons, Ltd., vol. 28(1), pages 29-41, January.
  26. Lillo, Felipe & Valdés, Rodrigo, 2016. "Dynamics of financial markets and transaction costs: A graph-based study," Research in International Business and Finance, Elsevier, vol. 38(C), pages 455-465.
  27. Wan, Jer-Yuh & Kao, Chung-Wei, 2009. "Evidence on the contrarian trading in foreign exchange markets," Economic Modelling, Elsevier, vol. 26(6), pages 1420-1431, November.
  28. repec:bla:germec:v:10:y:2009:i::p:270-283 is not listed on IDEAS
  29. Andreas Fritz & Michael Stein & Christoph Weber, 2015. "The Role of Heterogeneous Agents in Fuel Markets: Testing Tales of Speculators in Oil Markets," EWL Working Papers 1505, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Aug 2015.
  30. Ruixin Su & Jianguo Du & Fakhar Shahzad & Xingle Long, 2020. "Unveiling the Effect of Mean and Volatility Spillover between the United States Economic Policy Uncertainty and WTI Crude Oil Price," Sustainability, MDPI, vol. 12(16), pages 1-12, August.
  31. Georg Lehecka, 2015. "Do hedging and speculative pressures drive commodity prices, or the other way round?," Empirical Economics, Springer, vol. 49(2), pages 575-603, September.
  32. Pede, Valerien O. & Valera, Harold Glenn A. & Alam, Mohammad Jahangir & McKenzie, Andrew M., 2013. "Nonlinearities in Regional Rice Prices in the Philippines: Evidence from a Smooth Transition Autoregressive (STAR) Approach," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150246, Agricultural and Applied Economics Association.
  33. Ellen, Saskia ter & Zwinkels, Remco C.J., 2010. "Oil price dynamics: A behavioral finance approach with heterogeneous agents," Energy Economics, Elsevier, vol. 32(6), pages 1427-1434, November.
  34. Lof, Matthijs, 2013. "Essays on Expectations and the Econometrics of Asset Pricing," MPRA Paper 59064, University Library of Munich, Germany.
  35. 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.
  36. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
  37. 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.
  38. Westerhoff, Frank & Wieland, Cristian, 2010. "A behavioral cobweb-like commodity market model with heterogeneous speculators," Economic Modelling, Elsevier, vol. 27(5), pages 1136-1143, September.
  39. Andreas Röthig, 2012. "Cross‐Speculation In Currency Futures Markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 17(3), pages 272-278, July.
  40. Alizadeh, Amir H. & Thanopoulou, Helen & Yip, Tsz Leung, 2017. "Investors’ behavior and dynamics of ship prices: A heterogeneous agent model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 98-114.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.