A Bayesian Approach to Adapting Forecasts to Structural Changes in a Simple State-Space Model

34 Pages Posted: 29 Nov 2013

See all articles by Duk Bin Jun

Duk Bin Jun

College of Business, Korea Advanced Institute of Science and Technology (KAIST)

Seung Hyun Kim

KAIST Business School

Churlzu Lim

University of North Carolina (UNC) at Charlotte

Myoung Hwan Park

Hansung University

Date Written: November 1, 2013

Abstract

Most forecasting models often fail to produce appropriate forecasts because they are built on the assumption that data is being generated from only one stochastic process. However, in many real world problems, the time series data are generated from one stochastic process initially and then abruptly undergo certain structural changes. In this paper, we assume that the basic underlying process is the simple state-space model with random level and deterministic drift, but is interrupted by three types of exogenous shocks; level shift, drift change, and outlier. A Bayesian procedure to detect, estimate, and adapt to the structural changes is developed and compared to simple, double, and adaptive exponential smoothing using simulated data and the U.S. leading composite index.

Suggested Citation

Jun, Duk Bin and Kim, Seung Hyun and Lim, Churlzu and Park, Myoung Hwan, A Bayesian Approach to Adapting Forecasts to Structural Changes in a Simple State-Space Model (November 1, 2013). KAIST College of Business Working Paper Series No. 2013-030, Available at SSRN: https://ssrn.com/abstract=2360856 or http://dx.doi.org/10.2139/ssrn.2360856

Duk Bin Jun (Contact Author)

College of Business, Korea Advanced Institute of Science and Technology (KAIST) ( email )

85 Hoegiro, Dongdaemoon-gu
Seoul 02455
Korea, Republic of (South Korea)

Seung Hyun Kim

KAIST Business School ( email )

85 Hoegiro Dongdaemun-Gu
Seoul 02455
Korea, Republic of (South Korea)

Churlzu Lim

University of North Carolina (UNC) at Charlotte ( email )

9201 University City Boulevard
Charlotte, NC 28223
United States

Myoung Hwan Park

Hansung University ( email )

Seoul, 136-792
Korea

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
68
Abstract Views
587
Rank
603,784
PlumX Metrics