Using The Regression Method to Discover the Relationship Between Real Estate and Stock Market
DOI:
https://doi.org/10.54097/0crx5r02Keywords:
Real estate; Stock market index; Regression; Machine learning; Finance.Abstract
Recently, with the economic fluctuation, the relationship between house price and the stock market index has been paying much attention. However, this relationship has not been fully clarified yet through historical research. In this paper, several regression models including linear regression model and non-linear regression model are constructed to test for both single and dual relationship between the house price and market index. The assumption and method used in building the model will also be discussed. From testing, there is a positive linear effect on house price from the market index (approximately 80% of house price variation has been explained by the market index). On the opposite side, house price affects 93% of the market index in a positive non-linear pattern. Besides that, GDP can explain around 90% of house price variation in a positive linear relationship. This paper aims to help investors to have a better understanding of the relationship between these two and to help them build a better investment portfolio.
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