Peramalan Indeks Saham Syariah di Indonesia dengan Menggunakan Pendekatan Vector Error Correction Model (VECM)

Adiningtias, Angelia Mahardika (2024) Peramalan Indeks Saham Syariah di Indonesia dengan Menggunakan Pendekatan Vector Error Correction Model (VECM). Other thesis, Institut Teknologi Sepuluh Nopember.

[thumbnail of 5003201161-Undergraduate_Thesis.pdf] Text
5003201161-Undergraduate_Thesis.pdf - Accepted Version
Restricted to Repository staff only

Download (3MB) | Request a copy

Abstract

Pasar modal syariah menunjukkan pertumbuhan yang stabil dengan kinerja positif yang berdampak pada perekonomian global. Hal ini terbukti dengan industri keuangan syariah Indonesia yang mencatat pertumbuhan sebesar 15.87% (year on year) dan pasar modal syariah berkontribusi sebagai sektor terbesar dengan andil aset mencapai 60.08%. Indonesia merupakan salah satu negara berkembang yang sistem perekonomian masih sangat bergantung dengan negara maju lainnya. Ketergantungan tersebut seringkali menjadi salah satu penyebab terjadinya gejolak pada sektor ekonomi yang mengganggu stabilitas sistem keuangan di Indonesia, khususnya pada masar moda syariah. Oleh karena itu, peramalan dan analisis indeks saham syariah terutama variabel makroekonomi menjadi penting untuk dilakukan agar dapat memberikan nilai indeks yang akurat. Peramalan indeks saham syariah di Indonesia menggunakan pendekatan Vector Error Correction Model (VECM) dengan variabel yang digunakan yaitu Indeks Saham Syariah Indonesia (ISSI), Jakarta Islamic Index(JII), Indeks Harga Saham Gabungan (IHSG) dan kurs. Peramalan dengan menggunakan metode VECM menghasilkan dua model yaitu model dengan menggunakan intercept dan model tanpa intercept. Kriteria pemilihan model terbaik berdasarkan nilai RMSE dan MAPE. Peramalan menggunakan model terbaik pada variabel ISSI, JII, IHSG dan kurs masing-masing mampu digunakan untuk tujuh periode kedepan.
========================================================================================================================
The Islamic capital market shows stable growth with positive performance which has an impact on the global economy. This is proven by the Indonesian sharia financial industry which recorded growth of 15.87% (year on year) and the sharia capital market contributed as the largest sector with an asset share reaching 60.08%. Indonesia is a developing country whose economic system is still very dependent on other developed countries. This dependence is often one of the causes of turmoil in the economic sector which disrupts the stability of the financial system in Indonesia, especially in the sharia fashion market. Therefore, it is important to forecast and analyze sharia stock indices, especially macroeconomic variables, in order to provide accurate index values. Forecasting the Islamic stock index in Indonesia uses the Vector Error Correction Model (VECM) approach with the variables used, namely the Indonesian Sharia Stock Index (ISSI), Jakarta Islamic Index (JII), Composite Stock Price Index (IHSG) and the exchange rate. Forecasting using the VECM method produces two models, namely a model using intercept and a model without intercept. The criteria for selecting the best model are based on RMSE and MAPE values. Forecasting using the best model for the variables ISSI, JII, IHSG and the respective exchange rates can be used for the next seven periods.

Item Type: Thesis (Other)
Uncontrolled Keywords: Indeks Saham Syariah, Kointegrasi, Peramalan, Stasioner, VECM, Cointegration, Forecasting, Sharia Stock Index, Stationary, VECM.
Subjects: H Social Sciences > HB Economic Theory > Economic forecasting--Mathematical models.
Q Science > Q Science (General)
Q Science > QA Mathematics > QA275 Theory of errors. Least squares. Including statistical inference. Error analysis (Mathematics)
Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry)
Divisions: Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User: Angelia Mahardika Adiningtias
Date Deposited: 09 Aug 2024 03:32
Last Modified: 09 Aug 2024 03:32
URI: http://repository.its.ac.id/id/eprint/114920

Actions (login required)

View Item View Item