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 DMA-HAR 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 mid-run forecasting horizons. The evaluation framework is not limited to statistical loss functions but also embodies an options straddle trading strategy.
Item Type: | MPRA Paper |
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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.uni-muenchen.de/id/eprint/110831 |