Dynamic analysis of the volatility of Ibovespa returns: an application of the Markov Switching autoregressive model
DOI:
https://doi.org/10.6008/CBPC2179-684X.2020.004.0001Keywords:
Ibovespa, Markov Switching Autoregressive Model, Probability of Transition, Regime DurationAbstract
The present article uses the two-state Markov Switching autoregressive model developed by Hamilton (1989), to capture regime changes both in the mean and in the variance of Ibovespa returns, between January 2000 and May 2020. The empirical evidence indicates probabilities of transition suggesting that only events can change the series from a low volatility regime to a high volatility regime and contrary. It was found that the results of the MS(2)-AR(1) model detected moment of changes in returns regimes, because of the presidential election, financial crises 2008 and the pandemic (coronavírus 2020).
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