题名 | Are Gold and Government Bond Safe-Haven Assets? An Extremal Quantile Regression Analysis |
作者 | |
发表日期 | 2020-06-01
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DOI | |
发表期刊 | |
ISSN | 1369-412X
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EISSN | 1468-2443
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卷号 | 20期号:2页码:451-483 |
摘要 | This study reexamines gold and government bonds as potential safe-haven assets (SHAs) during market turmoil from daily data in 16 international markets over the past 20 years. We apply the extremal quantile regression model by Chernozhukov and Chernozhukov and Fernandez-Val for empirical investigation. The outcomes indicate that a government bond is more likely to be qualified an active SHA, which can increase in value during market turmoil. Gold can be generally evaluated as a passive SHA, which is uncorrelated with market slumps. However, at the extremal 0.001 quantile level, neither asset can be qualified as a SHA. Since both assets exhibit a similar number of cases of being qualified as SHAs, we cannot significantly differentiate the “flight-to-liquidity” and “flight-to-quality” hypotheses. In terms of market selection, United States and Singapore are the top two choices while France and Hungary are the least commended markets to invest their local gold market as SHA. |
相关链接 | [Scopus记录] |
收录类别 | |
语种 | 英语
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学校署名 | 第一
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WOS研究方向 | Business & Economics
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WOS类目 | Business, Finance
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WOS记录号 | WOS:000536609900006
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出版者 | |
Scopus记录号 | 2-s2.0-85054171203
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来源库 | Scopus
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引用统计 |
被引频次[WOS]:12
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成果类型 | 期刊论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/138128 |
专题 | 商学院 商学院_金融系 |
作者单位 | School of Business,Southern University of Science and Technology,Shenzhen,China |
第一作者单位 | 商学院 |
第一作者的第一单位 | 商学院 |
推荐引用方式 GB/T 7714 |
Liu,Wei han. Are Gold and Government Bond Safe-Haven Assets? An Extremal Quantile Regression Analysis[J]. International Review of Finance,2020,20(2):451-483.
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APA |
Liu,Wei han.(2020).Are Gold and Government Bond Safe-Haven Assets? An Extremal Quantile Regression Analysis.International Review of Finance,20(2),451-483.
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MLA |
Liu,Wei han."Are Gold and Government Bond Safe-Haven Assets? An Extremal Quantile Regression Analysis".International Review of Finance 20.2(2020):451-483.
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