Change point analysis in Vasicek interest rate model

This research paper investigates the impact of using colored noises instead of conventional Brownian motion in change-point detection problems with stochastic financial models. The study aims to understand how the incorporation of colored noises affects change points and forecasting outcomes. The Vasicek stochastic model is widely used to simulate interest rate paths.The paper provides an introduction to multiple stable states and abrupt shifts in complex systems, including financial and economic systems. It highlights the extensive literature on this topic and discusses the Vasicek model and its applications in financial analysis, including change-point detection.The research methodology involves replacing Brownian motion with colored noises such as pink and red. The Euler-Maruyama method is used to generate numerical solutions of the model. The paper also discusses parameter estimation, integration step adjustment, and change-point detection using the Pruned Exact Linear Time (PELT) algorithm.