Delis, Panagiotis and Degiannakis, Stavros and Giannopoulos, Kostantinos (2021): What should be taken into consideration when forecasting oil implied volatility index?

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Abstract
Crude oil is considered a key commodity in all the economies around the world. This study forecasts the oil volatility index (OVX), which is the market’s expectation of future oil volatility, by incorporating information from other asset classes. The literature does not extensively test the long memory of the targeted volatility. Thus, we estimate the Hurst exponent implementing a rolling window rescaled analysis. We provide evidence for a strong long memory in the implied volatility (IV) indices which justifies the use of the HAR model in obtaining multiple days ahead OVX forecasts. We also define a dynamic model averaging (DMA) structure in the HAR model in order to allow for IV indices from other asset classes to be applicable at different time periods. The implementation of the DMAHAR models informs forecasters to focus on the major stock market IV indices, and more specifically on the DJIA Volatility Index. Our results lead us to the conclusion that accurate OVX forecasts are obtained for short and midrun forecasting horizons. The evaluation framework is not limited to statistical loss functions but also embodies an options straddle trading strategy.
Item Type:  MPRA Paper 

Original Title:  What should be taken into consideration when forecasting oil implied volatility index? 
Language:  English 
Keywords:  crude oil, implied volatility, HAR modelling, trading strategies, dynamic model averaging, long memory 
Subjects:  C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C58  Financial Econometrics G  Financial Economics > G1  General Financial Markets > G17  Financial Forecasting and Simulation Q  Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4  Energy > Q47  Energy Forecasting 
Item ID:  110831 
Depositing User:  Mr Panagiotis Delis 
Date Deposited:  01 Dec 2021 09:29 
Last Modified:  01 Dec 2021 09:29 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/110831 