Fads Models with Markov Switching Hetroskedasticity: decomposing Tehran Stock Exchange return into Permanent and Transitory Components

Abstract

Stochastic behavior of stock returns is very important for investors and policy makers in the stock market. In this paper, the stochastic behavior of the return index of Tehran Stock Exchange (TEDPIX) is examined using unobserved component Markov switching model (UC-MS) for the 3/27/2010 until 8/3/2015 period. In this model, stock returns are decomposed into two components; a permanent component and a transitory component. This approach allows analyzing the impact of shocks of permanent and transitory components. The transitory component has a three-state Markov switching heteroscedasticity (low, medium, and high variances). Results show that the unobserved component Markov switching model is appropriate for this data. Low value of RCM criteria implies that the model can successfully distinguish among regimes. The aggregate autoregressive coefficients in the temporary component are about 0.4. The duration of high-variance regime for the transitory component is short-lived and reverts to normal levels quickly. The implied result of the research is that the presidential election may have a significant effect on being in the third regime.