Granger causality testing for Argentina MERVAL index and the major world stock markets
In this paper are analyzed the causal links among a selected group of global stock market indices, with special focus on the role of Argentina MERVAL index. With this objective in mind, two types of non-conventional Granger causality test are performed in order to avoid the theoretical limitations o...
Guardado en:
| Autores principales: | , |
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| Formato: | conferenceObject |
| Lenguaje: | Inglés |
| Publicado: |
2022
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/11086/23764 |
| Aporte de: |
| Sumario: | In this paper are analyzed the causal links among a selected group of global stock market indices, with special focus on the role of Argentina MERVAL index. With this objective in mind, two types of non-conventional Granger causality test are performed in order to avoid the theoretical limitations of the traditional test which requires stationary time series. The first test is based in a surplus-lag VAR model and allows testing for Granger causality in thecontext of non-stationary processes. The second test rests on the estimation of a VARX model and is robust to non-stationarity; long memory; and non-modeled structural breaks. This second test also admits conditioning on endogenous modeled control variables. The estimations are performed using daily data for a long time period, being both testing procedures implemented in the programming language R. Finally the results from both tests are compared and interpreted in order to capture their economic meaning. |
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