Quantile time-frequency connectedness analysis between crude oil, gold, financial markets, and macroeconomic indicators: Evidence from the US and EU

被引:1
|
作者
Shang, Jin [1 ]
Hamori, Shigeyuki [2 ]
机构
[1] Kobe Univ, Grad Sch Econ, Kobe 6578501, Japan
[2] Kobe Univ, Fac Econ, Nada Ku, Kobe 6578501, Japan
关键词
Commodity markets; Crude oil; Gold; Stock markets; Currency index; Industrial production index; CPI; US; EU; QVAR; Quantile time-frequency connectedness; IMPULSE-RESPONSE ANALYSIS; PRICE SHOCKS; VOLATILITY SPILLOVERS; EFFICIENT TESTS; MONETARY-POLICY; EXCHANGE-RATE; STOCK-MARKET; RISK; IMPACT; GDP;
D O I
10.1016/j.eneco.2024.107473
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study examines the relationships between various financial and economic sectors using a method called quantile time-frequency connectedness. We use the quantile time-frequency connectedness approach developed by Chatziantoniou et al. (2022) to investigate how commodity markets, such as crude oil and gold, interact with stock markets, currency markets, industrial production indices, and consumer price indices (CPI) in both the United States (US) and the European Union (EU), comparing the differences between crude oil and gold in the US and EU. The main findings of the study reveal that system risk varies over time and quantiles, with dynamic total connectedness being more significant during extreme market conditions (5% and 95% quantiles) and short-term spillovers outweighing long-term spillovers for both the US and the EU. Crude oil consistently serves as the primary net transmitter of shocks in both short-term and long-term dynamics across various quantiles. In contrast, gold ' s role varies, generally transmitting long-term shocks and receiving short-term shocks. The study also identifies the asymmetric nature of connectedness between bullish and bearish markets in the US, while connectedness in the EU appears more symmetric. Furthermore, different indicators serve as net transmitters or receivers of shocks based on quantiles and time intervals, revealing the sources of market uncertainties and the indicators most vulnerable to shocks. This research is among the first to use this method to study these connections across different domains ' indices and macroeconomic and for different situations in both the US and the EU, which can help policymakers and investors obtain a comprehensive understanding of the dynamic quantile time-frequency connectedness between these relationships.
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页数:42
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