IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v227y2013i2p367-384.html
   My bibliography  Save this article

A Tabu Search heuristic procedure in Markov chain bootstrapping

Author

Listed:
  • Cerqueti, Roy
  • Falbo, Paolo
  • Guastaroba, Gianfranco
  • Pelizzari, Cristian

Abstract

Markov chain theory is proving to be a powerful approach to bootstrap finite states processes, especially where time dependence is non linear. In this work we extend such approach to bootstrap discrete time continuous-valued processes. To this purpose we solve a minimization problem to partition the state space of a continuous-valued process into a finite number of intervals or unions of intervals (i.e. its states) and identify the time lags which provide “memory” to the process. A distance is used as objective function to stimulate the clustering of the states having similar transition probabilities. The problem of the exploding number of alternative partitions in the solution space (which grows with the number of states and the order of the Markov chain) is addressed through a Tabu Search algorithm. The method is applied to bootstrap the series of the German and Spanish electricity prices. The analysis of the results confirms the good consistency properties of the method we propose.

Suggested Citation

  • Cerqueti, Roy & Falbo, Paolo & Guastaroba, Gianfranco & Pelizzari, Cristian, 2013. "A Tabu Search heuristic procedure in Markov chain bootstrapping," European Journal of Operational Research, Elsevier, vol. 227(2), pages 367-384.
    • Handle: RePEc:eee:ejores:v:227:y:2013:i:2:p:367-384
    DOI: 10.1016/j.ejor.2012.11.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221712008338
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2012.11.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Weron, R & Bierbrauer, M & Trück, S, 2004. "Modeling electricity prices: jump diffusion and regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 39-48.
    2. Ehrgott, Matthias & Klamroth, Kathrin & Schwehm, Christian, 2004. "An MCDM approach to portfolio optimization," European Journal of Operational Research, Elsevier, vol. 155(3), pages 752-770, June.
    3. Stanislav Anatolyev & Andrey Vasnev, 2002. "Markov chain approximation in bootstrapping autoregressions," Economics Bulletin, AccessEcon, vol. 3(19), pages 1-8.
    4. Guastaroba, Gianfranco & Mansini, Renata & Speranza, M. Grazia, 2009. "On the effectiveness of scenario generation techniques in single-period portfolio optimization," European Journal of Operational Research, Elsevier, vol. 192(2), pages 500-511, January.
    5. Roy Cerqueti & Paolo Falbo & Cristian Pelizzari, 2009. "Optimal Dimension of Transition Probability Matrices for Markov Chain Bootstrapping," Working Papers 53-2009, Macerata University, Department of Finance and Economic Sciences, revised Apr 2009.
    6. repec:ebl:ecbull:v:3:y:2002:i:19:p:1-8 is not listed on IDEAS
    7. S. Anily & A. Federgruen, 1991. "Structured Partitioning Problems," Operations Research, INFORMS, vol. 39(1), pages 130-149, February.
    8. Huisman, Ronald & Mahieu, Ronald, 2003. "Regime jumps in electricity prices," Energy Economics, Elsevier, vol. 25(5), pages 425-434, September.
    9. Woodside-Oriakhi, M. & Lucas, C. & Beasley, J.E., 2011. "Heuristic algorithms for the cardinality constrained efficient frontier," European Journal of Operational Research, Elsevier, vol. 213(3), pages 538-550, September.
    10. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number hsbook0601, December.
    11. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Eduard Gabriel Ceptureanu & Sebastian Ceptureanu & Claudiu Herteliu, 2021. "Evidence regarding external financing in manufacturing MSEs using partial least squares regression," Annals of Operations Research, Springer, vol. 299(1), pages 1189-1202, April.
    2. Cerqueti, Roy & Falbo, Paolo & Pelizzari, Cristian, 2017. "Relevant states and memory in Markov chain bootstrapping and simulation," European Journal of Operational Research, Elsevier, vol. 256(1), pages 163-177.
    3. Roy Cerqueti & Paolo Falbo & Cristian Pelizzari & Federica Ricca & Andrea Scozzari, 2017. "A mixed integer linear program to compress transition probability matrices in Markov chain bootstrapping," Annals of Operations Research, Springer, vol. 248(1), pages 163-187, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Roy Cerqueti & Paolo Falbo & Cristian Pelizzari & Federica Ricca & Andrea Scozzari, 2017. "A mixed integer linear program to compress transition probability matrices in Markov chain bootstrapping," Annals of Operations Research, Springer, vol. 248(1), pages 163-187, January.
    2. Roy Cerqueti & Paolo Falbo & Cristian Pelizzari & Federica Ricca & Andrea Scozzari, 2012. "A Mixed Integer Linear Programming Approach to Markov Chain Bootstrapping," Working Papers 67-2012, Macerata University, Department of Finance and Economic Sciences, revised Nov 2012.
    3. Mari, Carlo & Tondini, Daniela, 2010. "Regime switches induced by supply–demand equilibrium: a model for power-price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4819-4827.
    4. Pawel Maryniak & Stefan Trueck & Rafal Weron, 2016. "Carbon pricing, forward risk premiums and pass-through rates in Australian electricity futures markets," HSC Research Reports HSC/16/10, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    5. Eichler, M. & Türk, D.D.T., 2012. "Fitting semiparametric Markov regime-switching models to electricity spot prices," Research Memorandum 035, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    6. Stephen Machin & Olivier Marie & Sunčica Vujić, 2012. "Youth Crime and Education Expansion," German Economic Review, Verein für Socialpolitik, vol. 13(4), pages 366-384, November.
    7. Pape, Christian & Hagemann, Simon & Weber, Christoph, 2016. "Are fundamentals enough? Explaining price variations in the German day-ahead and intraday power market," Energy Economics, Elsevier, vol. 54(C), pages 376-387.
    8. Janczura, Joanna & Trück, Stefan & Weron, Rafał & Wolff, Rodney C., 2013. "Identifying spikes and seasonal components in electricity spot price data: A guide to robust modeling," Energy Economics, Elsevier, vol. 38(C), pages 96-110.
    9. Mayer, Klaus & Trück, Stefan, 2018. "Electricity markets around the world," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 77-100.
    10. Janczura, Joanna & Weron, Rafal, 2010. "An empirical comparison of alternate regime-switching models for electricity spot prices," Energy Economics, Elsevier, vol. 32(5), pages 1059-1073, September.
    11. Misiorek Adam & Trueck Stefan & Weron Rafal, 2006. "Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-36, September.
    12. Eichler, M. & Türk, D., 2013. "Fitting semiparametric Markov regime-switching models to electricity spot prices," Energy Economics, Elsevier, vol. 36(C), pages 614-624.
    13. Joanna Janczura & Rafal Weron, 2012. "Inference for Markov-regime switching models of electricity spot prices," HSC Research Reports HSC/12/01, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    14. Sandro Sapio, 2012. "Modeling the distribution of day-ahead electricity returns: a comparison," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1935-1949, December.
    15. Gianfreda, Angelica & Grossi, Luigi, 2012. "Forecasting Italian electricity zonal prices with exogenous variables," Energy Economics, Elsevier, vol. 34(6), pages 2228-2239.
    16. Mari, Carlo & Cananà, Lucianna, 2012. "Markov switching of the electricity supply curve and power prices dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1481-1488.
    17. Christensen, T.M. & Hurn, A.S. & Lindsay, K.A., 2012. "Forecasting spikes in electricity prices," International Journal of Forecasting, Elsevier, vol. 28(2), pages 400-411.
    18. Trueck, Stefan & Weron, Rafal & Wolff, Rodney, 2007. "Outlier Treatment and Robust Approaches for Modeling Electricity Spot Prices," MPRA Paper 4711, University Library of Munich, Germany.
    19. Alain Monfort & Olivier Féron, 2012. "Joint econometric modeling of spot electricity prices, forwards and options," Review of Derivatives Research, Springer, vol. 15(3), pages 217-256, October.
    20. Rafał Weron, 2009. "Heavy-tails and regime-switching in electricity prices," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 457-473, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:227:y:2013:i:2:p:367-384. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.