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Journal ArticleDOI

Extreme risk spillover of the oil, exchange rate to Chinese stock market: Evidence from implied volatility indexes

Lin Chen, +4 more
- 01 Jan 2022 - 
- Vol. 107, pp 105857-105857
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TLDR
In this article , the authors explored extreme risk spillover of the oil and USD/CNY exchange rate to Chinese stock market from the uncertainty volatility perspective, based on the upside and downside conditional value-at-risk (CoVaR) values.
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This article is published in Energy Economics.The article was published on 2022-01-01. It has received 26 citations till now. The article focuses on the topics: Spillover effect & Downside risk.

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Asymmetric causality of economic policy uncertainty and oil volatility index on time-varying nexus of the clean energy, carbon and green bond

TL;DR: In this article , the authors investigated the time-varying connections among clean energy, carbon, and green bonds through the DCC-MIDAS model, thus providing a bird's-eye view of their dynamic nexus.
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Industries' heterogeneous reactions during the COVID‐19 outbreak: Evidence from Chinese stock markets

TL;DR: In this paper , the authors examined the heterogeneous effects of the COVID-19 outbreak on stock prices in China and found that those with high asset intensity, low labor intensity, high inventory to revenue ratio, and small market value are more negatively affected than others.
Journal ArticleDOI

Oil price uncertainty and stock price crash risk: Evidence from China

TL;DR: Wang et al. as mentioned in this paper investigated the impact of oil price uncertainty on stock price crash risk in China and found that oil price price uncertainty positively affects stock price crashes risk, although its positive impact is significant both for the state-owned and non-state-owned enterprises.
Journal ArticleDOI

Frequency dependence between oil futures and international stock markets and the role of gold, bonds, and uncertainty indices: Evidence from partial and multivariate wavelet approaches

TL;DR: In this article , the frequency dynamic co-movements between crude oil prices and stock market returns of three developed economies (Canada, Japan, and the USA) and the emerging BRICS (Brazil, Russia, India, China, and South Africa) economies by considering four global factors (U.S. treasury bills, S&P volatility index, gold price, and U.S EPU index).
Journal ArticleDOI

Time-frequency connectedness and cross-quantile dependence between crude oil, Chinese commodity market, stock market and investor sentiment

TL;DR: Wang et al. as mentioned in this paper analyzed the time-frequency correlation between crude oil, Chinese commodity market, stock market and investor sentiment index, and investigated the cross-quantile dependence between the index and Chinese commodity futures or stock market.
References
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Book

An Introduction to Copulas

TL;DR: This book discusses the fundamental properties of copulas and some of their primary applications, which include the study of dependence and measures of association, and the construction of families of bivariate distributions.
Journal ArticleDOI

On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks

TL;DR: In this article, a modified GARCH-M model was used to find a negative relation between conditional expected monthly return and conditional variance of monthly return, using seasonal patterns in volatility and nominal interest rates to predict conditional variance.
Journal ArticleDOI

Measuring and Testing the Impact of News on Volatility

TL;DR: This paper defined the news impact curve which measures how new information is incorporated into volatility estimates and compared various ARCH models including a partially nonparametric one with daily Japanese stock return data.
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A conditionally heteroskedastic time series model for speculative prices and rates of return

TL;DR: In this article, a simple time series model designed to capture the dependence of speculative price changes and rates of return data was presented, which is an extension of the autoregressive conditional heteroskedastic (ARCH) and generalized ARCH (GARCH) models obtained by allowing for conditionally t-distributed errors.
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