Analisis pengaruh indeks saham asing terhadap indeks harga saham gabungan dengan pendekatan Error Correction Model

Abstract

The Composite Stock Price Index (IHSG) is a composite index of many shares listed on the stock exchange and their movements show conditions that occur in the capital market. JCI is confident of macroeconomic factors and foreign exchange indexes. The purpose of this study was to analyze the effect of the Dow Jones Index, the Straits Time Index, the Hang Seng Index, the Nikkei 225 Index, and the FTSE 100 Index on the composite price index. The research method used is the Error Correction Model (ECM). In the short term, the DJIA and FTSE 100 variables have a positive effect on the JCI, the STI and Hang Seng variables have no significant on the JCI, while the Nikkei 225 has a negative effect on the JCI. In the long term, the DJIA and STI variables have a positive effect on the IHSG, the JSI and FTSE 100 variables have no effect on the IHSG, while the Nikkei 225 variable has a negative effect on the JCI.

The effect of gold price and NIKKEI on market return in Indonesia

“…Bakhtiar and Purwani (2021) find that NIKKEI had a negative and significant relationship with the IHSG from 2014 to 2018. Nuraeni and Panjawa (2021) also prove that NIKKEI had a negative effect and is significant to the IHSG in the period January 2016 to December 2020. However, Gerung et al ( 2022) also find that NIKKEI had a positive impact in the period June to December 2021 but had a negative impact in the period January to May 2022.…”

Analysis of the Existence of Environmental Kuznets Curve (EKC) Hypothesis on CO2 Emission, Energy Consumption, and Economic Growth in Indonesia

“…VECM takes into account short-term errors that will be balanced in the long term (Saboori & Sulaiman, 2013b). In the VECM analysis, several steps were carried out, including determining the optimal lag, cointegration test, causality analysis (Johansen test), Vector Error Correction Model modelling, impulse response function (IRF), and forecasting error variance decomposition (FEVD) (Nugroho et al, 2016). The following are the models in this study:…”