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Inference for a change-point problem under an OU setting with unequal and unknown volatilities |
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| Authors: | Fuqi Chen Rogemar Mamon Sévérien Nkurunziza |
| Affiliation: | 1. Bureau of Food Surveillance and Science Integration, Food Directorate, Health Products and Food Branch, Health Canada, Ottawa, Ontario, Canada;2. Department of Statistical and Actuarial Sciences, The University of Western Ontario, London, Ontario, Canada;3. Department of Mathematics and Statistics, University of Windsor, Windsor, Ontario, Canada |
| Abstract: | An Ornstein–Uhlenbeck (OU) process is employed as a versatile model to capture the mean-reverting and stochastic evolution of many variables in various fields of applications including finance and economics. Within the OU setting, we develop a new estimation method to determine the unknown change-point location under the assumption that the volatilities before and after the change point in a time series are unequal. Our method hinges on the concept of a weighted least sum of squared errors approach and enhanced by a fusion of an iterative algorithm. The consistency of the change-point estimator is established. This article highlights a numerical implementation on simulated and observed financial market data demonstrating the significant flexibility and accuracy of our proposed modelling and estimation method. The Canadian Journal of Statistics 48: 62–78; 2020 © 2019 Statistical Society of Canada |
| Keywords: | Asymptotic property consistent estimator financial modelling iterative weighted least sum of squared errors oil spot price |