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Russian-Ukraine Invasion's Effect on the Stock Market: An Event Study on Kompas 100 Index i kadek bellyoni dwijaya; Saparman Saparman; muhammad yunus kasim
Jurnal Manajemen Bisnis Performa Vol 20, No 1 (2023)
Publisher : Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/performa.v20i1.11328

Abstract

This study evaluates the reaction of the stock market to the Russian-Ukraine invasion that occurred on February 24, 2022. Using an event study approach, test the average abnormal return and the cumulative average abnormal return. The research sample uses all stocks listed on the Kompas 100 index, with a classification of 9 sectors on the Indonesia Stock Exchange (IDX). The analytical method uses a nonparametric test of difference with the Wilcoxon signed rank test. Statistical results show that there is no significant difference in the average abnormal return indexed by Kompas 100 in all study window periods, despite one of the sectors having the most significant negative impact, namely the mining sector. Cumulatively, most of the stocks show a positive trend. The performance of stocks in Indonesia is better than that of stocks in Europe, which have been significantly affected. These results provide evidence that the stock market in Indonesia is more resilient as a result of the Russia-Ukraine conflict. This research has implications for mining company investors making investment decisions in turbulent situations.Keywords: Event Studies; Market Reaction; Russian-Ukraine Invasion Penelitian ini mengevaluasi reaksi pasar saham atas invasi Rusia-Ukraina yang terjadi pada 24 februari 2022. Dengan menggunakan pendekatan studi peristiwa dengan menguji average abnormal return dan Cummulative average abnormal return. Sampel penelitian menggunakan seluruh saham yang terdaftar pada indeks Kompas 100, dengan klasifikasi 9 sektor di Bursa Efek Indonesia (BEI). Metode analisis menggunakan uji beda nonparametrik dengan uji wilcoxonesigned rank test. Hasil statistik menunjukan tidak terdapat perbedaan yang signifikan average abnormal return diindeks Kompas 100 pada semua periode jendela penelitian,salah satu sektor yang paling berdampak negatif signifikan yaitu sektor pertambangan. Secara kumulatif sebagian besar saham menunjukan trend positif. Performa saham di Indonesialebih baik dibandingkan saham di Eropa yang sangat terdampak signifikan. Hasil ini memberikan bukti bahwa pasar saham di Indonesia lebih tanguh akibat dari konflik Rusia-Ukraina. Penelitian ini memberikan implikasi bagi investorperusahaan pertambangan dalam membuat keputusan investasipada situasi yang penuh gejolak.Kata Kunci: Invasi Russia-Ukraina; Reaksi Pasar; Studi Peristiwa
Prakiraan Laju Inflasi Kota-Kota di Pulau Sulawesi: Pendekatan Model ARMA: Forecasting Inflation Rate of Citie in Sulawesi Island: ARMA Model Approach Rahmawaty, Santi; I Kadek Bellyoni Dwijaya; Sri Dewi Fitrianingsih; Faris Septianto Nur Ali
Jurnal Kolaboratif Sains Vol. 8 No. 11: November 2025
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/jks.v8i11.9146

Abstract

Penelitian ini bertujuan untuk memproyeksikan angka inflasi 6 Kota di Sulawesi menggunakan data bulanan dengan metode Box dan Jenkins. Data meliputi inflasi bulanan periode januari 2013 – juni 2023 mencakup 6 Kota di Sulawesi. Adapun tahapan metode peramalan meliputi uji stasioneritas data yang telah stasioner pada tingkat level, pemilihan ordo terbaik menghasilkan model ARMAberbeda pada masing-masing Kota. Hasil analisis estimasi inflasi 6 Kota di Sulawesi menunjukan tren berfluktuatif dengan proyeksi inflasi Kota Gorontalo tahun 2023 diperkirakan sebesar 2,90, inflasi Kota Kendari sebesar 4,98, inflasi Kota Makassar sebesar 3,55, inflasi Kota Manado sebesar 2,80, inflasi Kota Palu sebesar 3,17 dan inflasi Kota Mamuju sebesar 3,65. Analisis estimasi tidak mengandung unsur heteroskedastisitas sehingga tidak perlukan pengujian model ARCH/GARCH.
Measuring the Efficiency of State-Owned Stocks Using Capital Asset Pricing Model (CAPM) I Kadek Bellyoni Dwijaya; Muhammad Yunus Kasim; Sri Dewi Fitrianingsih
Jurnal Nusantara Aplikasi Manajemen Bisnis Vol 9 No 1 (2024): Jurnal Nusantara Aplikasi Manajemen Bisnis
Publisher : UNIVERSITAS NUSANTARA PGRI KEDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/nusamba.v9i1.21162

Abstract

Abstract Research aim : This study examines market efficiency using the Capital Asset Pricing Model (CAPM) method on BUMN stocks in Indonesia. Design/Methode/Approach : This model explains the relationship between risk and return in an efficient market. The analysis focuses on using stock beta calculations for 5 years. Research Finding : The research results are as follows: 1) the BUMN stock market in Indonesia is classified as efficient, namely 11 stocks where 5 companies have positive individual returns, namely ANTM, TINS, KRAS, BBNI, and PGAS. There are 6 companies that have negative returns, namely WSKT, ADHI, WIKA, PTPP, SMBR, and BBTN. 2) the analysis was carried out during the covid-19 pandemic period, the basic material sector is a collection of stocks that are classified as resilient during the pandemic showing positive and efficient returns. 3) overall, there is a high systematic risk of BUMN stocks in Indonesia, and actively responds to any changes that occur in market prices. Theoretical contribution/Originality : This contribution is expected to be a reference for investors and market participants. Practitionel/Policy implication : These results provide information for investors to choose efficient State-Owned Enterprises (BUMN) stocks in deciding to invest and still consider the nature and characteristics of each investor. Research limitation : Future research is expected to use other methods in analyzing the level of stock risk such as Arbitrage Pricing Theory (APT) or estimating future stock prices using the ARIMA / GarCH forecasting method and increasing the number of samples in the study or different market indices so that the expected results are more accurate in predicting future stock prices.
Co-Authors Faris Septianto Nur Ali MUH. YUNUS KASIM, MUH. YUNUS KASIM Muhammad Yunus Kasim Rahmawaty, Santi Saparman Saparman Sri Dewi Fitrianingsih