Identifying change point in production time-series volatility using control charts and stochastic differential equations

Abstract

The article focuses on volatility change point detection using SPC (Statistical Process Control) methods, specifically time-series control charts and stochastic differential equations (SDEs). Contribution will review recent advances in change point detection for the volatility component of a process satisfying stochastic differential equation (SDE) based on discrete observations, and also by using time-series control charts. Theoretical part will discuss methodology of time-series control charts and SDEs driven by a Brownian motion. Research part will demonstrate the methodologies in a simulation study focusing on analysis of the AR(1) process by means of time-series control charts and SDEs. The aim is to make use of change point detection in time series of production processes and highlight versatility of control charts not only in manufacturing but also in managing financial cash flow stability. © 2014, World Scientific and Engineering Academy and Society. All rights reserved.