The Power of a Leading Indicators Fluctuation Trend for Forecasting Taiwans Real Estate Business Cycle: An Application of a Hidden Markov Model

Abstract

This paper employ the discrete hidden Markov model (HMM) in order to capture information about the Markov switching model’s inner states that is not directly observable, and to pre-detect the real estate business cycle’s volatility trend. The empirical results show that this HMM can capture the asymmetry in the duration of states. Compared with the real estate leading indicator announced by the Taiwan Real Estate Research Center, this HMM yields the same results in terms of forecasting the trends of cycle fluctuations. The explanatory power of the HMM in 4-steps out-of-sample forecasting is supported both conceptually and methodologically.