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The Markov switching vector autoregressive model is a dynamic stochastic system with stochastic autoregressive parameters. This model able to measure a time varying problem when the variables undergoing regime switching. Structural change or shock is an ordinary fact in time series data. Some shocks have an important role under specific regimes in examining the business cycle contraction. Excluding changes in regime for the measurement of variance decomposition may produce biased results. Moreover, the parameters in the time series model might also have a structural change. Therefore, linear models are no longer suitable to be used in analyzing the financial model; and nonlinear time series models that are Markov switching models are proposed to solve these kinds of problems. A two regimes Markov switching vector autoregressive model is used in this study to analysis the time series data. The regime is dependent heterogeneous with varying the variance to detect every change of the business cycle. The correlations between oil price, Malaysia, Singapore, Thailand and Indonesia stock price are examining using Markov switching model. The result shows that the regimes dependent models suitable to employ in study the asymmetric business cycle; and oil price have a negative relationship with the changes of the four selected Asian stock markets.

Asymmetric Effects of the Effect of Oil Price on Stock Markets in Four Asian Countries: Markov Switching Analysis