Abstract
This study verifies that housing prices in China follow Zipf's law by analyzing the average housing prices in 200 Chinese cities between 2015 and 2023. The Kolmogorov-Smirnov (KS) test further supports this conclusion. Furthermore, the study explores housing price trends in different city tiers and uses rank clocks to reveal price fluctuations, which is not captured by the Zipf's law. Using nine-year housing price time series data, the ARIMA and ConvLSTM models generate short-term forecasts. The forecasting results are evaluated using various indicators, and KS tests on the predicted prices show a better conformity to Zipf's law. This paper also builds a dynamic housing price model, offering a new perspective to understand and predict housing price trends. The results of this paper can shed light on the real estate market.