IDEAS home Printed from https://ideas.repec.org/a/rjr/romjef/vy2010i2p213-222.html

Repetitive Stochastic Guesstimation for Estimating Parameters in a GARCH(1,1) Model

Author

Listed:
  • Agapie, Adriana

    (UNESCO Chair for Business Administration, Academy of Economic Studies, Bucharest, Romania)

  • Bratianu, Constantin

    (UNESCO Chair for Business Administration, Academy of Economic Studies, Bucharest, Romania)

Abstract

A behavioral algorithm for optimization - Repetitive Stochastic Guesstimation (RSG) - is adapted, with complete proofs for its global convergence, for estimating parameters in a GARCH(1,1) model, based on a very small number of observations. Estimators delivered by this algorithm for the example of a GARCH(1,1) model are dependent on some computational capabilities - namely number of iterations and replications performed. In this context, the Large Numbers Law might be applied in a completely different dimension. An alternative toward waiting until the historical data series are recorded (while the underling process may change several times) is to use computers for correctly extracting information from the most recent data. Given the existent computational support, it is also possible to determine estimates for the rates of convergence. As a result, potential benefits of this econometric technique can be gained in case of very young financial markets from Eastern European countries. Also, prediction and political decisions based on these estimations are properly grounded.

Suggested Citation

  • Agapie, Adriana & Bratianu, Constantin, 2010. "Repetitive Stochastic Guesstimation for Estimating Parameters in a GARCH(1,1) Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 213-222, July.
    • Handle: RePEc:rjr:romjef:v::y:2010:i:2:p:213-222
    as

    Download full text from publisher

    File URL: http://www.ipe.ro/rjef/rjef2_10/rjef2_10_13.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    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. Acatrinei, Marius & Gorun, Adrian & Marcu, Nicu, 2013. "A DCC-GARCH Model To Estimate the Risk to the Capital Market in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 136-148, March.

    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. Thomas Baudin & Robert Stelter, 2022. "The rural exodus and the rise of Europe," Journal of Economic Growth, Springer, vol. 27(3), pages 365-414, September.
    2. Asgharian, Hossein & Hess, Wolfgang & Liu, Lu, 2013. "A spatial analysis of international stock market linkages," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4738-4754.
    3. Luca Benati & Paolo Surico, 2008. "Evolving U.S. Monetary Policy and The Decline of Inflation Predictability," Journal of the European Economic Association, MIT Press, vol. 6(2-3), pages 634-646, 04-05.
    4. John M. Abowd & Francis Kramarz & Sébastien Pérez-Duarte & Ian M. Schmutte, 2018. "Sorting Between and Within Industries: A Testable Model of Assortative Matching," Annals of Economics and Statistics, GENES, issue 129, pages 1-32.
    5. Haan, Peter & Prowse, Victoria L., 2010. "The Design of Unemployment Transfers: Evidence from a Dynamic Structural Life-Cycle Model," IZA Discussion Papers 4792, Institute of Labor Economics (IZA).
    6. Dufour, Jean-Marie, 2006. "Monte Carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics," Journal of Econometrics, Elsevier, vol. 133(2), pages 443-477, August.
    7. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2018. "Cross-commodity news transmission and volatility spillovers in the German energy markets," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 231-243.
    8. Kapetanios, George & Marcellino, Massimiliano & Papailias, Fotis, 2016. "Forecasting inflation and GDP growth using heuristic optimisation of information criteria and variable reduction methods," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 369-382.
    9. Roman Sustek, 2011. "Monetary Business Cycle Accounting," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(4), pages 592-612, October.
    10. Jeffrey M. Wooldridge, 2002. "Inverse probability weighted M-estimators for sample selection, attrition, and stratification," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 117-139, August.
    11. Max Jerrell, 2000. "Applications Of Public Global Optimization Software To Difficult Econometric Functions," Computing in Economics and Finance 2000 161, Society for Computational Economics.
    12. Robert G. King & Alexander Wolman & Michael Dotsey, 2009. "Inflation and Real Activity with Firm Level Productivity Shocks," 2009 Meeting Papers 367, Society for Economic Dynamics.
    13. Deb, Partha & Trivedi, Pravin K., 2002. "The structure of demand for health care: latent class versus two-part models," Journal of Health Economics, Elsevier, vol. 21(4), pages 601-625, July.
    14. Catherine Kyrtsou & Michel Terraza, 2003. "Is it Possible to Study Chaotic and ARCH Behaviour Jointly? Application of a Noisy Mackey–Glass Equation with Heteroskedastic Errors to the Paris Stock Exchange Returns Series," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 257-276, June.
    15. Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
    16. Sexton, Randall S. & Dorsey, Robert E. & Johnson, John D., 1999. "Optimization of neural networks: A comparative analysis of the genetic algorithm and simulated annealing," European Journal of Operational Research, Elsevier, vol. 114(3), pages 589-601, May.
    17. Lena Janys & Bettina Siflinger, 2021. "Mental Health and Abortions among Young Women: Time-varying Unobserved Heterogeneity, Health Behaviors, and Risky Decisions," Papers 2103.12159, arXiv.org, revised May 2022.
    18. Rubin, Ofir D. & Ihle, Rico & Kachel, Yael & Goodwin, Barry K., 2013. "The impact of violent political conflict on commodity prices: The Israeli food market," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150961, Agricultural and Applied Economics Association.
    19. Gianluca Cubadda & Francesco Giancaterini & Alain Hecq & Joann Jasiak, 2023. "Optimization of the Generalized Covariance Estimator in Noncausal Processes," Papers 2306.14653, arXiv.org, revised Jan 2024.
    20. M. Bierlaire & M. Thémans & N. Zufferey, 2010. "A Heuristic for Nonlinear Global Optimization," INFORMS Journal on Computing, INFORMS, vol. 22(1), pages 59-70, February.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    Statistics

    Access and download statistics

    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:rjr:romjef:v::y:2010:i:2:p:213-222. 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: Corina Saman The email address of this maintainer does not seem to be valid anymore. Please ask Corina Saman to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/ipacaro.html .

    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.