A Study on Unobserved Structural Innovations of Oil Price: Evidence from Global Stock, Bond, Foreign Exchange, and Energy Markets

Baek, Jungho; Seo, Jiyong

doi:10.1142/s0219091515500046

Cited by 9 publications

(4 citation statements)

References 29 publications

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“…The correlation coefficients are consistent among the models and exhibit a significant negative correlation. This result that is similar to the empirical results in financial market and energy market that negative correlation between asset returns and its volatility (Eraker 2004;Chen et al 2009;Baek and Seo 2015).…”

Section: Parameters Estimationsupporting

confidence: 90%

The affine styled-facts price dynamics for the natural gas: evidence from daily returns and option prices

Hsu

Chen

Lin

et al. 2016

Rev Quant Finan Acc

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This study analyzes affine styled-facts price dynamics of Henry Hub natural gas price by incorporating the price features of jump risk, and seasonality within stochastic volatility framework. Affine styled-facts dynamics has the advantage of being able to incorporate mean reversion (MR), stochastic volatility (SV), seasonality trends (S), and jump diffusion (J) in a standardized inclusive framework. Our main finding is that models that incorporate jumps significantly improve overall out-of-sample option pricing performance. The combined MRSVJS model provides the best fit of both daily gas price returns and the related cross section of option prices. Incorporating seasonal effects tend to provide more stable pricing ability, especially for the long-term option contracts.

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Section: Parameters Estimationsupporting

confidence: 90%

The affine styled-facts price dynamics for the natural gas: evidence from daily returns and option prices

Hsu

Chen

Lin

et al. 2016

Rev Quant Finan Acc

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“…It, however, shows that the degree of spillover between the two was high during the period 2008–2011, owing to the effect of global financial crisis. In an attempt to examine the effect of volatility spillover from global oil shock to a good swathe of the financial market, Baek and Seo (2015) examine the effects of oil shocks and volatility spillover including leverage effects on global stock, bond, foreign exchange and energy market. Using structural VAR, they establish significant effect of global oil price shock on these financial assets.…”

Section: Literature Reviewmentioning

confidence: 99%

Oil price shocks and volatility spillovers in the Nigerian sovereign bond market

Tule¹,

Ndako²,

Onipede³

2017

Rev Financ Econ

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This paper investigates volatility spillover in the Nigerian sovereign bond market arising from oil price shocks, using Vector Autoregressive Moving Average ‐ Asymmetric Generalized Autoregressive Conditional Heteroscedasticity (VARMA‐AGARCH) model. The paper covers the period March 22, 2011 to April 14, 2016 and makes use of the daily data of the Nigerian Sovereign Bond, Brent oil and West Texas Intermediate (WTI), respectively. We endogenously and sequentially detect structural break points using the test of Bai and Perron (2003) framework. In order to accurately estimate the model, we modify it by incorporating the break points into the VARMA‐AGARCH model, a process which if ignored would lead to model misspecification. The results obtained demonstrate a significant cross‐market volatility transmission between oil and sovereign bond market with ample sensitivity to structural breaks. The study also computes optimum weight portfolio and hedge ratio both with and without structural breaks and results equally indicate sensitivity to structural breaks.

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“…Several studies indicate that there is a significant relationship between oil prices shocks and stock market returns and volatility (see Mohanty et al, 2011;Gupta and Wohar, 2017;Mohanty et al, 2017;and Smyth and Narayan, 2018). Since oil is an indicator of global growth, similar findings also exist in the bond market, foreign exchange market and energy market; yet, the effects of oil price shocks vary within markets (Baek and Seo, 2015). Other studies, such as that of Filis and Chatziantoniou (2014), indicate that the reaction of interest rates to an oil price shock is mostly based on the regime of monetary policy of each country.…”

Section: Introductionmentioning

confidence: 98%

Oil shocks and volatility jumps

Γκίλλας

Gupta

Wohar

2019

Rev Quant Finan Acc

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In this paper, we analyse the role of oil price shocks, derived from expectations of consumers, economists, financial market, and policymakers, in predicting volatility jumps in the S&P500 over the monthly period of 1988:01 to 2015:02, with the jumps having been computed based on daily data over the same period. Standard linear Granger causality tests fail to detect any evidence of oil shocks causing volatility jumps. But given strong evidence of nonlinearity and structural breaks between jumps and oil shocks, we next employed a nonparametric causality-in-quantiles test, as the linear model is misspecified. Using this data-driven robust approach, we were able to detect overwhelming evidence of oil shocks predicting volatility jumps in the S&P500 over its entire conditional distribution, with the strongest effect observed at the lowest considered conditional quantile. Interestingly, the predictive ability of the four oil shocks on volatility jumps is found to be both qualitatively and quantitatively similar.

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A Study on Unobserved Structural Innovations of Oil Price: Evidence from Global Stock, Bond, Foreign Exchange, and Energy Markets

Cited by 9 publications

References 29 publications

The affine styled-facts price dynamics for the natural gas: evidence from daily returns and option prices

The affine styled-facts price dynamics for the natural gas: evidence from daily returns and option prices

Oil price shocks and volatility spillovers in the Nigerian sovereign bond market

Oil shocks and volatility jumps

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