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Empirical Economics

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07.07.2017

Forecasting the volatility of crude oil futures using high-frequency data: further evidence

verfasst von: Feng Ma, Yu Wei, Wang Chen, Feng He

Erschienen in: Empirical Economics | Ausgabe 2/2018

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Abstract

We forecast the realized volatility of crude oil futures market using the heterogeneous autoregressive model for realized volatility and its various extensions. Out-of-sample findings indicate that the inclusion of jumps does not improve the forecasting accuracy of the volatility models, whereas the “leverage effect” pertaining to the difference between positive and negative realized semi-variances can significantly improve the forecasting accuracy in predicting the short- and medium-term volatility. However, the signed jump variations and its decomposition couldn’t significantly enhance the models’ forecasting accuracy on the long-term volatility.

Vorheriger Artikel A latent dynamic factor approach to forecasting multivariate stock market volatility

Nächster Artikel Herding in Chinese stock markets: a nonparametric approach

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Andersen et al. (2007) use the realized volatility and realized variation interchangeably.

https://www.tickdata.com/

Please see more details in Zivot and Wang (2005) and Sévi (2014). In addition, we are thankful to Benoît Sévi, who give us some suggestions to measure the data.

The spot prices of oil are collected by https://www.eia.gov/dnav/pet/pet_pri_spt_s1_d.htm.

We use the econometric software, WINRATS (V 8.00, 32 bit) to test the null hypothesis, “Skewness = 0” and “ Kurtosis = 3”.

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Titel: Forecasting the volatility of crude oil futures using high-frequency data: further evidence
verfasst von: Feng Ma
Yu Wei
Wang Chen
Feng He
Publikationsdatum: 07.07.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: Empirical Economics / Ausgabe 2/2018
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI: https://doi.org/10.1007/s00181-017-1294-6

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