Analyzing the Causality and Dependence between Exchange Rate and Real Estate Prices in Boom-and-Bust Markets: Quantile Causality and DCC Copula GARCH Approaches

Yamaka, Woraphon; Liu, Jianxu; Li, Mingyang; Maneejuk, Paravee; Dinh, Hai Q.

doi:10.3390/axioms11030113

Cited by 3 publications

(1 citation statement)

References 44 publications

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“…Liu et al (2016) [ 12 ] investigated the spillover and nonlinear correlation between housing prices, exchange rates, and stock prices using a smooth transition vector error correction GARCH (STVEC-GARCH) model. Yamaka et al (2022) [ 13 ] investigated the nonlinear causality and dynamic correlation between exchange rates and housing prices in the boom-and-business market using the panel quantile Granger causality and dynamic conditional correlation (DCC) copula GARCH method. Some scholars have also applied the GARCH model to study the linkage effect of housing prices between regions.…”

Section: Introductionmentioning

confidence: 99%

Research on China’s Risk of Housing Price Contagion Based on Multilayer Networks

Qiu

Wang

2022

Entropy

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The major issue in the evolution of housing prices is risk of housing price contagion. To model this issue, we constructed housing multilayer networks using transfer entropy, generalized variance decomposition, directed minimum spanning trees, and directed planar maximally filtered graph methods, as well as China’s comprehensive indices of housing price and urban real housing prices from 2012 to 2021. The results of our housing multilayer networks show that the topological indices (degree, PageRank, eigenvector, etc.) of new first-tier cities (Tianjin, Qingdao, and Shenyang) rank higher than those of conventional first-tier cities (Beijing, Shanghai, Guangzhou, and Shenzheng).

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Section: Introductionmentioning

confidence: 99%

Research on China’s Risk of Housing Price Contagion Based on Multilayer Networks

Qiu

Wang

2022

Entropy

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Volatility research of nickel futures and spot prices based on copula-GARCH model

Hong

Luo²,

Li³

et al. 2022

Front. Energy Res.

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Nickel, an essential strategic emerging mineral in China, plays a vital role in promoting the development of the new energy vehicle industry and protecting the security of energy resources. However, the linkage between international and domestic nickel futures markets and the spot market is increasing. It is necessary to analyze and study the correlation characteristics and influence mechanisms to help investors avoid risks and judge the market situation which will improve the risk control ability and promote the steady development of the domestic market. Therefore, from the perspective of international and domestic markets and based on the yield sequence of the nickel futures prices and the spot prices, the study first discusses the characteristics of the volatility aggregation effect and asymmetries of the nickel futures and spot prices. Second, select an appropriate GARCH model to fit the marginal distribution sequence of the yields. Third, use the Copula function to connect the financial time series to find the correlation. The results indicate that the Copula-GARCH model can better fit the tail correlation between nickel futures market and spot market. Finally, we put forward policy recommendations for strengthening and improving the domestic nickel futures market, actively participating in the international competition mechanism, and preventing and controlling the risk of market price fluctuations.

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The Mathematical Simulation of South Korea’s Financial and Economic Impacts from Real Estate Bubbles: Lessons from the China Evergrande Collapse

Wang,

2024

Mathematics

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This study investigates the macroeconomic and financial repercussions of a real estate bubble burst in South Korea through the application of Bayesian estimation and impulse response function analysis. By utilizing this approach tailored to the specific economic conditions of South Korea, the research effectively captures the complex ripple effects across a range of financial and macroeconomic variables. The results demonstrate that a real estate bubble burst markedly increases financial market risks, leading to heightened liquidity demands within the banking sector and necessitating adjustments in both deposit rates and bond yields. The study also emphasizes the differentiated impacts on patient and impatient households, where wealth losses drive significant shifts in consumption and labor supply behaviors, further constrained by prevailing labor market conditions. Additionally, the broader economic implications are examined, revealing the adverse effects on corporate output and investment, as well as the dynamics of international capital flows that impact foreign exchange reserves and exchange rates. These findings highlight the urgent need for proactive monitoring and policy interventions to mitigate the detrimental effects of real estate bubbles, ensuring financial stability and fostering sustainable economic growth in South Korea.

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Analyzing the Causality and Dependence between Exchange Rate and Real Estate Prices in Boom-and-Bust Markets: Quantile Causality and DCC Copula GARCH Approaches

Cited by 3 publications

References 44 publications

Research on China’s Risk of Housing Price Contagion Based on Multilayer Networks

Research on China’s Risk of Housing Price Contagion Based on Multilayer Networks

Volatility research of nickel futures and spot prices based on copula-GARCH model

The Mathematical Simulation of South Korea’s Financial and Economic Impacts from Real Estate Bubbles: Lessons from the China Evergrande Collapse

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