关键词: 房地产股价波动, 高技术板块, 溢出效应, DGC-t-MSV模型

Abstract: With the wide opening of the financial market, the internal connection between the traditional industry and emerging one is gradually strengthened. Since September in 2021, there have been frequent debt defaults of housing enterprises, some stocks have fallen by more than 50% since the peak of 2018, the Hang Seng Real Estate Construction Index has fallen by nearly 18%, and stocks such as China Evergrande, China Fortune Happiness and Sun City Group have fallen by more than 50% this year. Short bursts and shocks have become the basic trend of the real estate sector, and it is more necessary for the high-tech sector to assume the important task of guiding the flow of social funds and dispersing price risks in the stock market. Exploring the risk linkage structure and spillover effect mechanism between “the real estate and high-tech” has important academic value and practical significance.
   Existing researches, to some extent, have ignored the actual impact of real estate stock price fluctuations on the high-tech sector in the stock market. To this end, based on Maximum Overlapping Discrete Wavelet (MODWT) decomposition and DGC-t-MSV model, this paper focuses on the spillover effect of real estate stocks on high-tech sectors. First, wavelet theory is widely applied to the multi-dimensional decomposition of financial time series. MODWT is not limited by ordinary discrete wavelet for the amount of data, also known as displacement invariant discrete wavelet transform or stationary wavelet transform, and after each decomposition of the same amount of data, has stronger applicability than ordinary discrete wavelet transform. Second, stochastic volatility model can better describe the real characteristics of financial volatility by introducing stochastic process. The DGC-t-MSV model constructed in this paper can estimate the dynamic correlation coefficient of the return series and obtain the intensity and direction of spillover effect based on Granger causality test.
   Based on the index compilation methods published by China Securities Index Company and Shenzhen Securities Information Company Limited, this paper extracts the real estate blue chip stocks in Shanghai and Shenzhen stock markets to build the real estate top50 index (RE). First, the total average daily market value and average daily turnover of the selected stocks in the sample space in the last half a year are collected, and the stocks that rank the bottom 20% in average daily turnover are excluded. Secondly, the top 50 stocks are selected to form the initial sample stocks according to the total average daily market value from the highest to the lowest. Finally, the real-time price index is calculated according to the Pai weighting method, and the base date of the index is April 20, 2003. The index base point is at 1000 points. The construction method of high-tech industrial Composite index (HT) is the same as above.
   In this paper, WinBUGS software is used for MCMC iteration. The results show that: (1)There is a dynamic correlation between the real estate and high-tech sector, and volatility spillovers in real estate stocks are stronger. (2)The restrictions on innovation inputs brought by the real estate industry are gradually reduced after the government’s restrictive policies. (3)Frequent trading in the short and medium term is the main reason for the real estate premium, and the high-tech sector needs to be alert to the spillover risks faced by the high-tech sector. Therefore, actively guiding value investment in the high-tech sector and reasonably allocating technology elements can promote the high-tech industry development effectively.

Key words: real estate stock price volatility, high technology sector, spillover effect, DGC-t-MSV model