Early Warning System in ASEAN Countries Using Capital Market Index Return: Modiied Markov Regime Switching Model - Wahyudi, Imam; Luxianto, Rizky; Suryaputri, Niken Iwani; Sulung, Liyu Adhika Sari (The Indonesian Capital Market Review, 2011)
Asia's financial crisis in July 1997 affects currency, capital market, and real market throughout Asian countries. Countries in southeast region (ASEAN), including Indonesia, Malaysia, Philippines, Singapore, and Thailand, are some of the countries where the crisis hit the most. In these countries, where financial sectors are far more developed than real sectors and the money market sectors, most of the economic activities are conducted in capital market. Movement in the capital market could be a proxy to describe the overall economic situation and therefore the prediction of it could be an early warning system of economic crises. This paper tries to investigate movement in ASEAN (Indonesia, Malaysia, Philippines, Singapore, and Thailand) capital market to build an early warning system from financial sectors perspective. This paper will be very beneficial for the government to anticipate the forthcoming crisis. The insight of this paper is from Hamilton (1990) model of regime switching process in which he divide the movement of currency into two regimes, describe the switching transition based on Markov process and creates different model for each regimes. Differ from Hamilton, our research focuses on index return instead of currency to model the regime switching. This research aimed to ind the probability of crisis in the future by combining the probability of switching and the probability distribution function of each regime. Probability of switching is estimated by categorizing the movement in index return into two regimes (negative return in regime 1 and positive return in regime 2) then measuring the proportion of switching to regime 1 in t given regime 1 in t-1 (P11) and to regime 2 in t given regime 2 in t-1 (P22). The probability distribution function of each regime is modeled using t-student distribution. This paper is able to give signal of the 1997/8 crisis few periods prior the crisis.