Portfolio risk and stress across the business cycle

Sampath, Aravind; Chakraborty, Sandip; Kakani, Ram Kumar

doi:10.1016/j.intfin.2022.101623

Cited by 2 publications

(2 citation statements)

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“…On this basis, with the continuous improvement of the VaR model, Adrian and Brunnermeier (2008) first proposed the Conditional Value at Risk (CoVaR) model, which not only analyses risk spillovers of individual financial market but also capture changes in risk across the entire system. The three common methods to calculate CoVaR are the quantile regression method (Mensi et al, 2022), the Copula function (Shahzad et al, 2018) and the GARCH model (Chakraborty et al, 2022). Wang et al (2014) compared these three methods from three aspects: advantages and disadvantages, principles and applicable scenarios.…”

Section: Literature Reviewmentioning

confidence: 99%

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Time–frequency correlation and risk spillovers between Euramerican mature and Asian emerging crude oil futures markets

Hong,

Luo,

et al. 2024

JRF

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PurposeThis paper aims to empirically investigate time–frequency linkages between Euramerican mature and Asian emerging crude oil futures markets in terms of correlation and risk spillovers.Design/methodology/approachWith daily data, the authors first undertake the MODWT method to decompose yield series into four different timescales, and then use the R-Vine Copula-CoVaR to analyze correlation and risk spillovers between Euramerican mature and Asian emerging crude oil futures markets.FindingsThe empirical results are as follows: (a) short-term trading is the primary driver of price volatility in crude oil futures markets. (b) The crude oil futures markets exhibit certain regional aggregation characteristics, with the Indian crude oil futures market playing an important role in connecting Euramerican mature and Asian emerging crude oil futures markets. What’s more, Oman crude oil serves as a bridge to link Asian emerging crude oil futures markets. (c) There are significant tail correlations among different futures markets, making them susceptible to “same fall but different rise” scenarios. The volatility behavior of the Indian and Euramerican markets is highly correlated in extreme incidents. (d) Those markets exhibit asymmetric bidirectional risk spillovers. Specifically, the Euramerican mature crude oil futures markets demonstrate significant risk spillovers in the extreme short term, with a relatively larger spillover effect observed on the Indian crude oil futures market. Compared with India and Japan in Asian emerging crude oil futures markets, China's crude oil futures market places more emphasis on changes in market fundamentals and prefers to hold long-term positions rather than short-term technical factors.Originality/valueThe MODWT model is utilized to capture the multiscale coordinated motion characteristics of the data in the time–frequency perspective. What’s more, compared to traditional methods, the R-Vine Copula model exhibits greater flexibility and higher measurement accuracy, enabling it to more accurately capture correlation structures among multiple markets. The proposed methodology can provide evidence for whether crude oil futures markets exhibit integration characteristics and can deepen our understanding of connections among crude oil futures prices.

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Section: Literature Reviewmentioning

confidence: 99%

“…The three common methods to calculate CoVaR are the quantile regression method (Mensi et al. , 2022), the Copula function (Shahzad et al ., 2018) and the GARCH model (Chakraborty et al ., 2022). Wang et al .…”

Section: Literature Reviewmentioning

confidence: 99%