• Title/Summary/Keyword: 비모수 분위수 인과관계 검정

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Quantile causality from dollar exchange rate to international oil price (원유가격에 대한 환율의 인과관계 : 비모수 분위수검정 접근)

  • Jeong, Kiho
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.2
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    • pp.361-369
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    • 2017
  • This paper analyzes the causal relationship between dollar exchange rate and international oil price. Although large literature on the relationship has accumulated, results are not unique but diversified. Based on the idea that such diversified results may be due to different causality at different economic status, we considers an approach to test the causal relationship at each quantile. This approach is different from the mean causality analysis widely employed by the existing literature of the causal relationship. In this paper, monthly data from May 1987 to 2013 is used for the causal analysis in which Brent oil price and Major Currencies Dollar Index (MCDI) are considered. The test method is the nonparametric test for causality in quantile suggested by Jeong et al. (2012). The results show that although dollar exchange rate causes oil price in mean, the causal relationship does not exist at most quantiles.

Impact of Oil Price Shocks on Stock Prices by Industry (국제유가 충격이 산업별 주가에 미치는 영향)

  • Lee, Yun-Jung;Yoon, Seong-Min
    • Environmental and Resource Economics Review
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    • v.31 no.2
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    • pp.233-260
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    • 2022
  • In this paper, we analyzed how oil price fluctuations affect stock price by industry using the non-parametric quantile causality test method. We used weekly data of WTI spot price, KOSPI index, and 22 industrial stock indices from January 1998 to April 2021. The empirical results show that the effect of changes in oil prices on the KOSPI index was not significant, which can be attributed to mixed responses of diverse stock prices in several industries included in the KOSPI index. Looking at the stock price response to oil price by industry, the 9 of 18 industries, including Cloth, Paper, and Medicine show a causality with oil prices, while 9 industries, including Food, Chemical, and Non-metal do not show a causal relationship. Four industries including Medicine and Communication (0.45~0.85), Cloth (0.15~0.45), and Construction (0.5~0.6) show causality with oil prices more than three quantiles consecutively. However, the quantiles in which causality appeared were different for each industry. From the result, we find that the effects of oil price on the stock prices differ significantly by industry, and even in one industry, and the response to oil price changes is different depending on the market situation. This suggests that the government's macroeconomic policies, such as industrial and employment policies, should be performed in consideration of the differences in the effects of oil price fluctuations by industry and market conditions. It also shows that investors have to rebalance their portfolio by industry when oil prices fluctuate.