Measuring housing price volatilities：A comparison between GARCH and Markov switching models
In many situations,measuring the uncertainty of housing price fluctuations is an important issue.This study employed two types of univariate time-series models,GARCH and Markov Regime Switching,to study the housing price dynamics in four Chinese cities.Both housing price votatility and the probability of downturns were used to evaluate the housing price uncertainty for each model.The two models have very limited differences for the in-sample fitness.However,the out-of-sample forecasts differ greatly.This paper shows that the Markov Regime Switching model tends to make over-confident predictions while the GARCH model is relatively conservative.Nevertheless,the trends of both risk measurements from the two models were consistent with each other,providing valuable information to investors.
housing price volatilityhousing price downturn probabilityGARCH modelMarkov regime switching model
NETL
NSTL
万方数据
维普
