Repetitive Stochastic Guesstimation for Estimating Parameters in a GARCH(1,1) Model
AbstractA 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Institute for Economic Forecasting in its journal Romanian Journal for Economic Forecasting.
Volume (Year): (2010)
Issue (Month): 2 (July)
Contact details of provider:
Postal: Casa Academiei, Calea 13, Septembrie nr.13, sector 5, Bucureşti 761172
Phone: 004 021 3188148
Fax: 004 021 3188148
Web page: http://www.ipe.ro/
More information through EDIRC
RSG; GARCH Model; financial markets;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Corina Saman).
If references are entirely missing, you can add them using this form.