Volatility change point detection using stochastic differential equations and time series control charts

Abstract

The article focuses on volatility change point detection using SPC (Statistical Process Control), specifically through time series control charts, and stochastic differential equations (SDEs). In the paper, recent advances in timechange point for process volatility component satisfying a stochastic differential equation (SDE) based on discrete observations and also using time series control charts will be reviewed. Theoretical part will discuss the methodology of time series control charts and SDEs driven by a Brownian motion. Research part will demonstrate the methodologies using a case study focusing on analysis of Slovak currency during the period of 2000 - 2004 from the perspective of its usefulness for generating profits for company management through time series control charts and SDEs. The aim of the paper is to demonstrate use of change point detection in time series of the Slovak crown. It also aims to highlight versatility of control charts not only in manufacturing but also in managing financial stability of cash flows.