On Modelling of Crude Oil Futures in a Bivariate State-Space Framework
@article{He2021OnMO,
title={On Modelling of Crude Oil Futures in a Bivariate State-Space Framework},
author={Peilun He and Karol Binkowski and Nino Kordzakhia and Pavel V. Shevchenko},
journal={Mathematical and Statistical Methods for Actuarial Sciences and Finance},
year={2021}
}We study a bivariate latent factor model for the pricing of commodity futures. The two unobservable state variables representing the short and long term factors are modelled as Ornstein-Uhlenbeck (OU) processes. The Kalman Filter (KF) algorithm has been implemented to estimate the unobservable factors as well as unknown model parameters. The estimates of model parameters were obtained by maximising a Gaussian likelihood function. The algorithm has been applied to WTI Crude Oil NYMEX futures…
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