Abstract
The objective of this paper empirically analyzes the relations between information and housing market volatility using the housing price index of Seoul, San Francisco and Los Angeles for the time period from January 1995 to July 2019. For the empirical test of the asymmetric effect of information on housing market volatility, this paper employs GJR-GARCH model which enable good information and bad information to have impact on volatility. The analysis results are as follows. First, it was found that the GJR-GARCH (1,1) model is suitable for analyzing the asymmetric reaction of housing price volatility for information types. Second, it was found that for information types, Seoul, San Francisco, and Los Angeles all displayed asymmetric housing price volatility. It was found that Seoul reacted greater to volatility for unexpected positive earnings rate information than unexpected negative earnings rate information, while on the contrary, San Francisco and Los Angeles showed that they reacted greater to unexpected negative earnings rate information than to unexpected positive earnings rate information. These findings support the hypothesis. Third, for sensitivity to volatility, Seoul was found to be about five times higher than San Francisco and Los Angeles. It is necessary to differentiate the housing price volatility prediction model and portfolio composition according to the information type.
Highlights
Housing is both consumer goods and investment goods
The first time-difference coefficient ρ has a positive (+) sign and when it is statistically significant at levels below 1%, it means that the rises or drops in housing prices in Seoul, San Francisco, and Los Angeles would continue in the following month as well
An empirical analysis was conducted on the asymmetrical response of housing price volatility for information types using the GRJ-GARCH [1,1] model using the housing price indices of Seoul, San Francisco, and Los Angeles
Summary
Housing is both consumer goods and investment goods. As a consumer goods, a house has the characteristics of a general good that provides residential services. [9] A hypothesis can be set that the housing market shows greater housing price volatility when the economy is improving resulting in speculative investments, but when the economy slows down, it results in a lock-in-effect that leads to decrease housing price volatility. The identification of this hypothesis can provide important information for strategic investment, portfolio management and real estate policy. This study is unique in that it is the first attempt at analyzing asymmetric reaction of volatility according to information type for the housing markets of Korea and the USA.
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