빈도영역 분석법을 통한 주택가격과 거래량의 공통 사이클 분석

The movements of housing prices and trading volume have long-term cycles. Thus, it can be presumed that there would be a close relationship between the cyclic components embedded in these two variables. However, it has been challenging to find studies that analyzed the cyclical characteristics and the relationship between the common cycles embedded in these two variables. This study, in contrast to previous studies that used methodologies in the time domain analysis to confirm the correlation and lead-lag relationship between housing prices and trading volume, analyzed, from different perspectives, the cyclical characteristics embedded in these two variables, using spectral analysis in the frequency domain. When forecasting cycles in housing prices and trading volume, for comparison, we added the results of the VAR(p) model analysis in the time domain to the results of the spectral analysis in the frequency domain. We could confirm that there were common cycles between the movements of housing prices and trading volume. Further, we confirmed that the movement of trading volume slightly precedes that of housing prices. According to our results, when the housing price has an upward trend, the housing market was expected to face a slow speed of an increase in housing prices while a decrease in trading volume for the time being after 2019. However, after 2020, both the trading volume and housing prices were expected to witness a relatively rapid increase. Ultimately, we improved the rationality of the forecasting results of future cycles by confirming the results from the time and frequency domain analyses.