ESTIMATING PARAMETERS IN A GARCH (1,1) MODEL BASED ON TWO OBSERVATIONS: A CRITIQUE OF THE LARGE NUMBERS' LAW

被引：0
|
作者：
Agapie, Adriana [1 ]
机构：
[1] Acad Econ Studies, Bucharest, Romania
来源：
PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON BUSINESS EXCELLENCE, VOL 1 | 2009年
关键词：
Behavioral Algorithms; Decision Making; Emergent Financial Markets; Evolutionary Algorithms; GUESSTIMATION;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
In the particular behavioral algorithm under study, estimators delivered by this one for the example of a GARCH(1,1) model are dependent on some computational capabilities-namely number of iterations and replications performed. Therefore, the Large Numbers Law might he 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. Also, prediction and political decisions based on these estimations are more properly grounded.
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页码：1 / 4
页数：4
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