High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets

By Jiawen Luo, Qiang Ji. Energy Economics, 2018

206 citations recorded by the source corpus.

Abstract This paper investigates the realised volatility connectedness of US crude oil futures and five China's agricultural commodity futures using connectedness measures and high-frequency data. Time-varying volatility connectedness characteristics are identified by combining a multivariate heteroscedastic autoregressive (HAR) model with the DCC-GARCH model. The results verify the existence of volatility spillover from the US crude oil market to China's agricultural commodity markets, although the magnitude of this spillover is weak. Furthermore, the realised volatility is decomposed into positive and negative components to identify the asymmetric effect of volatility connectedness. The results show that market interdependence has obviously increased for negative volatility relative to positive volatility, implying that volatility transmission has a leverage effect across markets.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/ad7ec30a5f6ed1164f910300323682196c2fd78c

Citations in the corpus

• Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models (2019, unknown): “Luo & Ji (2018) combine HAR-type models with dynamic correlation modelling (DCC, Engle, 2002) and detect a spillover from U.S. crude markets to Chinese agriculture commodities.”