Bayesian Unit Root Test with Outliers Observations: The Case of Daily Returns of 50 Active in Tehran Stock Exchange Companies

The main drawback of classical ADF and PP tests is the low power of test in small samples and their asymptotic distribution discontinuous. In contrast, many prominent scholars support the Bayesian unit root tests. In the present study, Bayesian unit root tests as an alternative to the classical meth...

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Bibliographic Details
Main Authors: Mojtaba Rostami, Seyed Nezamuddin Makiyan
Format: Article
Language:fas
Published: Semnan University 2019-08-01
Series:مدلسازی اقتصادسنجی
Subjects:
Online Access:https://jem.semnan.ac.ir/article_3979_432bebad194649f4462a6adf1aee29b8.pdf
Description
Summary:The main drawback of classical ADF and PP tests is the low power of test in small samples and their asymptotic distribution discontinuous. In contrast, many prominent scholars support the Bayesian unit root tests. In the present study, Bayesian unit root tests as an alternative to the classical methods are investigated. Because of the unconditional distribution structure of financial data, the focus of this study is to adjust the likelihood function with the distribution of the Scale Mixture of Normal. Daily stock returns data of 50 active stock companies were used. Due to the high probability of outliers, the unit root test was performed in terms of outliers’ observations without the need to construct new test statistics. The simulation results with Gibbs sampling algorithm show high probability of stationery. Also, the simulation of the distribution of the unit root test parameter shows that the Bayesian approach is more accurate than the classical one.
ISSN:2345-654X
2821-2150