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The Effects of Oil Price Shocks on Stock Market Volatility: Evidence from European Data

Stavros Degiannakis, George Filis, and Renatas Kizys

Year: 2014
Volume: Volume 35
Number: Number 1
DOI: 10.5547/01956574.35.1.3
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Abstract:
The paper investigates the effects of oil price shocks on stock market volatility in Europe by focusing on three measures of volatility, i.e. the conditional, the realized and the implied volatility. The findings suggest that supply-side shocks and oil specific demand shocks do not affect volatility, whereas, oil price changes due to aggregate demand shocks lead to a reduction in stock market volatility. More specifically, the aggregate demand oil price shocks have a significant explanatory power on both current-and forward-looking volatilities. The results are qualitatively similar for the aggregate stock market volatility and the industrial sectors' volatilities. Finally, a robustness exercise using short-and long-run volatility models supports the findings.



Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence

Stavros Degiannakis, George Filis, and Vipin Arora

Year: 2018
Volume: Volume 39
Number: Number 5
DOI: 10.5547/01956574.39.5.sdeg
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Abstract:
Do oil prices and stock markets move in tandem or in opposite directions? The complex and time varying relationship between oil prices and stock markets has caught the attention of the financial press, investors, policymakers, researchers, and the general public in recent years. In light of such attention, this paper reviews research on the oil price and stock market relationship. The majority of papers we survey study the impacts of oil markets on stock markets, whereas, little research in the reverse direction exists. Our review finds that the causal effects between oil and stock markets depend heavily on whether research is performed using aggregate stock market indices, sectorial indices, or firm-level data and whether stock markets operate in net oil-importing or net oil-exporting countries. Additionally, conclusions vary depending on whether studies use symmetric or asymmetric changes in the price of oil, or whether they focus on unexpected changes in oil prices. Finally, we find that most studies show oil price volatility transmits to stock market volatility, and that including measures of stock market performance improves forecasts of oil prices and oil price volatility. Several important avenues for further research are identified.Keywords: Oil prices, oil price volatility, stock markets, interconnectedness, forecasting, oil-importers, oil-exporters



Oil price volatility is effective in predicting food price volatility. Or is it?

Ioannis Chatziantoniou, Stavros Degiannakis, George Filis, and Tim Lloyd

Year: 2021
Volume: Volume 42
Number: Number 6
DOI: 10.5547/01956574.42.6.icha
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Abstract:
Volatility spillovers between food commodities and oil prices have been identified in the literature, yet, there has been no empirical evidence to suggest that oil price volatility improves real out-of-sample forecasts of food price volatility. In this study we provide new evidence showing that oil price volatility does not improve forecasts of agricultural price volatility. This finding is based on extensive and rigorous testing of five internationally traded agricultural commodities (soybeans, corn, sugar, rough rice and wheat) and two oil benchmarks (Brent and WTI). We employ monthly and daily oil and food price volatility data and two forecasting frameworks, namely, the HAR and MIDAS-HAR, for the period 2nd January 1990 until 31st March 2017. Results indicate that oil volatility-enhanced HAR or MIDAS-HAR models cannot systematically outperform the standard HAR model. Thus, contrary to what has been suggested by the existing literature based on in-sample analysis, we are unable to find any systematic evidence that oil price volatility improves out-of-sample forecasts of food price volatility. The results remain robust to the choice of different out-of-sample forecasting periods and three different volatility measures.



What Should be Taken into Consideration when Forecasting Oil Implied Volatility Index?

Panagiotis Delis, Stavros Degiannakis, and Konstantinos Giannopoulos

Year: 2023
Volume: Volume 44
Number: Number 5
DOI: 10.5547/01956574.44.4.pdel
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Abstract:
This study forecasts the oil volatility index (OVX) incorporating information from other implied volatility (IV) indices. We provide evidence for the existence of long memory in the OVX in order to justify the use of the Heterogeneous AutoRegressive (HAR) model. We extend the HAR model by implementing a dynamic model averaging (DMA) method in order to allow for IV indices from other asset classes to be applicable at different time periods. Apart from the statistical evaluation, a straddle options trading strategy validates our results from an economic point of view. The IV of Dow Jones is highly significant for short- and mid-run forecasting horizons, whereas, at longer horizons, the IV of Energy Sector provides accurate forecasts but only from an economic point of view.





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