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Spillover and quantile linkage between oil price shocks and stock returns : new evidence from G7 countries

Jiang, Yonghong; Tian, Gengyu; Mo, Bin - In: Financial innovation : FIN 6 (2020) 42, pp. 1-26

autoregression framework to decompose crude oil price shocks into oil supply shock, oil aggregate demand shock, and oil …-specific demand shock. We then explore the distinct effects of different kinds of oil price shocks from various sources.Based on the … appear to be heterogeneous. Oil supply shock appears to be a net transmitter of spillover effects for all G7 countries within …

Persistent link: https://www.econbiz.de/10012418406

Internet Appendix to `Forecasting Realized Volatility of the Oil Future Prices via Machine Learning'

Kim, Byung-June; Kim, Taeyoon; Jang, Bong-Gyu - 2021

The Internet Appendix consists of three sections. Section A shows data sources and detailed data processing procedures. In Section B, we outline seven forecasting models. Last, Section C represents the empirical results

Persistent link: https://www.econbiz.de/10013241114

Forecasting Realized Volatility of the Oil Future Prices Via Machine Learning

Kim, Byung-June; Kim, Taeyoon; Jang, Bong-Gyu - 2021

This paper explores the possibility of the potential usage of machine learning models in the field of realized volatility forecasting of crude oil with a vast variety of empirical analyses and robustness checks. Although the conventional heterogeneous autoregressive (HAR) model is widely...

Persistent link: https://www.econbiz.de/10013241115

Downside Uncertainty Shocks in the Oil and Gold Markets

Roh, Tai-Yong - 2020

We construct downside variance risk premiums from the crude oil and gold option data and use them as proxies for market downside uncertainty risks. We find that these downside variance risk premiums contain commodity market specifc pricing information. Further- more, the gold market's exposure...

Persistent link: https://www.econbiz.de/10012839629

Economic determinants of oil futures volatility : term structure perspective

Kang, Boda; Nikitopoulos, Christina Sklibosios; … - In: Energy economics 88 (2020), pp. 1-27

Persistent link: https://www.econbiz.de/10012515144

Dynamic Roughness in the Term Structure of Oil Markets Volatility

Alfeus, Mesias; Sklibosios Nikitopoulos, Christina; … - 2023

This paper analyses the attributes and the significance of the roughness of oil market volatility. We employ unspanned stochastic volatility models driven by rough Brownian motions that yield semi-analytical prices for futures options entailing efficient calibration applications. By performing a...

Persistent link: https://www.econbiz.de/10014260238

Fundamentals, Derivatives Market Information and Oil Price Volatility

Robe, Michel A.; Wallen, Jonathan - 2021

We analyze empirically what drives market expectations of crude oil price volatility. Between 2000 and 2014, we investigate the links between the term structure of oil option-implied volatilities (IVs) and global macroeconomic conditions, physical market fundamentals (OPEC surplus output...

Persistent link: https://www.econbiz.de/10013245198

Fundamentals, Derivatives Market Information and Oil Price Volatility

Robe, Michel A.; Wallen, Jonathan - 2021

Persistent link: https://www.econbiz.de/10013245199

Do Scheduled Macroeconomic Announcements Influence Energy Price Jumps?

Chan, Kam Fong - 2016

For six important energy futures markets, this study examines whether large price movements (i.e., jumps) are related to the arrival and information content of scheduled macroeconomic announcements. Since prior studies by Kilian and Vega [(2011) Review of Economics and Statistics, 93, 660–671]...

Persistent link: https://www.econbiz.de/10012981311

Bank Share Prices, Oil Prices and Greek Stock Market

Georgiou, Miltiades N. - 2015

Persistent link: https://www.econbiz.de/10013027323

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