TY - JOUR
T1 - A common factor of stochastic volatilities between oil and commodity prices
AU - Lee, Eunhee
AU - Han, Doo Bong
AU - Nayga, Rodolfo M.
N1 - Funding Information:
This work was supported by the National Research Foundation of Korea [NRF-2014S1A3A2044459].
Publisher Copyright:
© 2016 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2017/5/9
Y1 - 2017/5/9
N2 - This article analyses the multivariate stochastic volatilities (SVs) with a common factor influencing volatilities in the prices of crude oil and agricultural commodities, used for both biofuel and nonbiofuel purposes. Modelling the volatility is crucial because the volatility is an important variable for asset allocation, risk management and derivative pricing. We develop a SV model comprising a latent common volatility factor with two asymptotic regimes with a smooth transition between them. In contrast to conventional volatility models, SVs are generated by the logistic transformation of latent factors, which comprise two components: the common volatility factor and an idiosyncratic component. We present a SV model with a common factor for oil, corn and wheat from 8 August 2005 to 10 October 2014, using a Markov chain Monte Carlo method to estimate the SVs and extract the common volatility factor. We find that the volatilities of oil and grain markets are persistent. According to the estimated common volatility factor, high volatility periods match the 2007–2009 recession and the 2007–2008 financial crisis quite well. Finally, the extracted common volatility factor exhibits a distinct pattern.
AB - This article analyses the multivariate stochastic volatilities (SVs) with a common factor influencing volatilities in the prices of crude oil and agricultural commodities, used for both biofuel and nonbiofuel purposes. Modelling the volatility is crucial because the volatility is an important variable for asset allocation, risk management and derivative pricing. We develop a SV model comprising a latent common volatility factor with two asymptotic regimes with a smooth transition between them. In contrast to conventional volatility models, SVs are generated by the logistic transformation of latent factors, which comprise two components: the common volatility factor and an idiosyncratic component. We present a SV model with a common factor for oil, corn and wheat from 8 August 2005 to 10 October 2014, using a Markov chain Monte Carlo method to estimate the SVs and extract the common volatility factor. We find that the volatilities of oil and grain markets are persistent. According to the estimated common volatility factor, high volatility periods match the 2007–2009 recession and the 2007–2008 financial crisis quite well. Finally, the extracted common volatility factor exhibits a distinct pattern.
KW - Oil and commodity prices
KW - common volatility factor
KW - stochastic volatility
UR - http://www.scopus.com/inward/record.url?scp=84992116145&partnerID=8YFLogxK
U2 - 10.1080/00036846.2016.1234701
DO - 10.1080/00036846.2016.1234701
M3 - Article
AN - SCOPUS:84992116145
SN - 0003-6846
VL - 49
SP - 2203
EP - 2215
JO - Applied Economics
JF - Applied Economics
IS - 22
ER -