Time-varying causality between stock and housing markets in China

Shi, Guangping; Liu, Xiaoxing; Zhang, Xu

doi:10.1016/j.frl.2017.06.003

Cited by 22 publications

(9 citation statements)

References 7 publications

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“…The sample period of almost two decades in this study naturally leads us to think that there might exist a structural change in the causal relationship between the Asian emerging stock markets' volatilities and gold shocks. In other words, the causal relationships between the two considered variables may change over time and the structural change might affect temporal Granger causality effects that can be sensitive to the sample period adopted [39]. Thus, in this section, the rolling window Granger causality test is considered to investigate the time-varying Granger causality.…”

Section: Estimates Of Causality Using the Rolling Window Granger Causmentioning

confidence: 99%

Analyzing the Causality and Dependence between Gold Shocks and Asian Emerging Stock Markets: A Smooth Transition Copula Approach

Yamaka

Maneejuk

2020

Mathematics

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This study aims to investigate the causality and dependence structure of gold shocks and Asian emerging stock markets. The positive and negative shocks of gold prices are quantified, and Granger causality-based Vector autoregressive and Copula approaches are employed to measure the causality and contagion effect, respectively, between the positive and negative gold shocks and Asian emerging stock markets’ volatilities. In addition, the nonlinear link between gold and stock markets is of concern and this motivates us to propose a Smooth Transition Dynamic Copula that allows for the structural change in time-varying dependence between gold shocks and Asian stock markets’ volatilities. Several Copula families are also considered, and the best-fit Copula model is used to explain the correlation or contagion effects. The findings of the study show that there is some significant causality between gold shocks and Asian stock markets’ volatilities in some parts of the sample period. We also observe a stronger correlation during the global financial crisis when compared to the pre- and post-crisis periods. In addition, the tail dependence is found between Indian stock and negative gold shock and between Korean stock and negative gold shock, which indicated the existence of the risk contagion effects between gold and these two stock markets.

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Section: Estimates Of Causality Using the Rolling Window Granger Causmentioning

confidence: 99%

Analyzing the Causality and Dependence between Gold Shocks and Asian Emerging Stock Markets: A Smooth Transition Copula Approach

Yamaka

Maneejuk

2020

Mathematics

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“…is subsection provides an explanation of a robust test that may be used to validate the findings of empirical research. Following Tsai [49], Shi et al [50], and Mori [51], for the purpose of providing an explanation for the rationale behind utilizing CSI300 index as the proxy variable for stock market performance, the SSE50 index, which is another major Chinese stock index, is included in the process of assessing the relationship between the shock market and the housing market. Using the same method, the relationship between the stock market (SSE50 index) and the housing market is reestimated.…”

Section: Robustness Testmentioning

confidence: 99%

Causality Tests and Their Applications to China’s Stock and Housing Markets

2022

Discrete Dynamics in Nature and Society

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The link between the stock market and the housing market is well known to be sensitive. At present, the possibility of a connection between them remains intriguing. Therefore, China works as a case study for the research inquiry into the causal relationship between the stock market and the housing market. Using the monthly data from January 2000 to January 2021 and employing the cross-correlation function approach to perform empirical analysis, the results indicate that the bidirectional causal relationship between the stock market and the housing market has been recognized as one of the most interesting findings, which constitutes a significant departure from previous research. Moreover, the other interesting result is that, from the housing market to the stock market, a causality-in-mean and a causality-in-variance are discovered. Only a tiny number of previous studies have addressed this achievement in the context of China. Meanwhile, this article’s findings have both theoretical and practical implications for China’s proposition.

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“…Finally, the author shows a bidirectional causality between the money supply and the spillover index and the fact that the spillovers cause the variabilities of the treasury bill rate. Shi (2017) shows a time-varying causality between Chinese stock and housing markets (first-, second-, and thirdtier cities) during bull market and financial crisis episodes. More recently, Tsai (2018) used Markov-switching models to investigate housing affordability in UK regional housing markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Is the Korean housing market following Gangnam style?

Al‐Yahyaee

Mensi

Ko³

et al. 2020

Empir Econ

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Highlights This paper examines housing sales and rental market spillovers in Korean regional markets from 1991 to 2016. We employ the spillover index of Diebold and Yilmaz ( 2014) and the quantile regression approach. The 1997-1998 Asian currency crisis intensified regional spillovers in the Korean housing market. Gangnam region is a hub of connectedness, implying that it is the most influential shock transmitter among the regional housing markets. Macroeconomic factors impact the spillovers across regional housing sales and rental markets under different degree of spillovers.

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Time-varying causality between stock and housing markets in China

Cited by 22 publications

References 7 publications

Analyzing the Causality and Dependence between Gold Shocks and Asian Emerging Stock Markets: A Smooth Transition Copula Approach

Analyzing the Causality and Dependence between Gold Shocks and Asian Emerging Stock Markets: A Smooth Transition Copula Approach

Causality Tests and Their Applications to China’s Stock and Housing Markets

Is the Korean housing market following Gangnam style?

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