Title

Daily Stock Price Regime Model Detection using Markov Switching Model.

Authors

Prihartanti, Wiwik; Rasyid, Dwilaksana Abdullah; Iriawan, Nur

Abstract

Changes in stock prices randomly occur due to market forces with reoccurrence possibilities. This process, also known as the structural break model, is captured through changes in the linear model parameters among periods with the Markov Switching Model (MSwM) used for detection. Furthermore, using the smallest Akaike Information Criterion (AIC) value on all feasible MSwM alternatives formed for a daily stock price, the complete MSwM model with its Markov transition is determined. This method has been tested and applied to daily stock price data in several sectors. The result showed that the number of regime models coupled with its transition probability helped investors make investment decisions.

Subjects

MARKOV processes; AKAIKE information criterion; INVESTOR confidence

Publication

Matematika, 2020, Vol 36, p127

ISSN

0127-8274

Publication type

Academic Journal

DOI

10.11113/matematika.v36.n2.1189