• Title/Summary/Keyword: HPPCI

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Analysis of KOSPI·Apartment Prices in Seoul·HPPCI·CLI's Correlation and Precedence (종합주가지수·서울지역아파트가격·전국주택매매가격지수·경기선행지수의 상관관계와 선행성 분석)

  • Choi, Jeong-Il;Lee, Ok-Dong
    • Journal of Digital Convergence
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    • v.12 no.5
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    • pp.89-99
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    • 2014
  • Correlation of KOSPI from stock market and Apartment Prices in Seoul HPPCI from real estate market has been found from this research. Furthermore, from the comparison of those indicators' flows, certain precedence was found as well. The purpose of this research is to analyze correlation and precedence among KOSPI, Apartment price in Seoul, HPPCI and CLI. As for predicting KOSPI of stock market and real estate market, it is necessary to find out preceding indices and analyzing their progresses first. For 27 years from the January 1987 to December 2013, KOSPI has been grown by 687%, while CLI showed 443%, Apartment of Seoul showed 391%, HPPCI showed 263% of growth rate in order. As the result of correlation analysis among Apartment of Seoul, CLI, KOSPI and HPPCI, KOSPI and HPPCI showed high correlation coefficient of 0.877, and Apartment of Seoul and CLI showed that of 0.956 which is even higher. Result from the analysis, CLI shows high correlation with stock and real estate market, it is a good option to watch how CLI flows to predict stock and real estate market.

Relationship between Stock Market & Housing Market Trends and Liquidity (주식시장과 주택시장의 동향 및 유동성과의 관계)

  • Choi, Jeong-Il
    • Journal of Digital Convergence
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    • v.19 no.6
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    • pp.133-141
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    • 2021
  • Governments of each country are actively implementing fiscal expansion policies to recover the real economy after Corona 19. In Korea, the stock market and housing market are greatly affected as liquidity in the market increases due to the implementation of disaster subsidies and welfare policies. The purpose of this study is to analyze the relationship between stock market and housing market trends and liquidity. Data were collected by the Bank of Korea and Kookmin Bank. The analysis period is from January 2000 to December 2020, and monthly data are used. For empirical analysis, the rate of change from the same month of the previous year was calculated for each variable, and numerical analysis, index analysis, and model analysis were performed. As a result of the analysis, it was found that the stock index showed a positive(+) relationship with the house price, while a negative(-) relationship with M2. Previous studies have suggested that, in general, an increase in liquidity affects the stock market and the housing market, and inflation also rises. In this study, it was found that the stock market and the housing market had an effect on each other. However, it was investigated that liquidity showed an inverse relationship with the stock market and had no relationship with the housing market. Through this, this study estimated that there is a time difference in the relationship between liquidity and the stock market & housing market.