The effect of commodity price changes and USD/IDR exchange rate on Indonesian mining companies’ stock return

Abstract

There are many variables which will be influencing stock return. Some of those variables are come from the commodity market, such as gold, price and crude oil price changes, and also come from the exchange rate market. This study is about to test the effect of changes prices of gold, silver, crude oil, and exchange rate to the stock return of mining sector companies in Indonesia. There are 48 companies engaged in the mining sector listed on the Indonesia Stock Exchange (IDX). From 48 companies this study uses the purposive sampling method to choose a sample within the criteria, and 13 selected companies will be the object of this study. This study also used an analysis tool GARCH (1,1) to avoid abnormal data. Before advancing to GARCH (1,1) analysis, the data must be tested the stationary first by using Augmented Dickey-Fuller Test (ADF) to make sure the data stationary or not by using level, 1st difference, and two difference. The result shows that gold has a significant positive effect on stock return mining sector companies such as INCO, KKGI, PTBA, and TINS. Silver has a significant positive effect on HRUM companies and negatively on RUIS. Crude oil has a significant positive effect on HRUM and PTBA firms. Exchange rates have a significant negative impact on companies. ANTM, CTTH, DOID, ELSA, HRUM, ITMG, and KKGI. Abstrak Ada banyak variabel yang akan memengaruhi return saham. Beberapa variabel tersebut berasal dari pasar komoditas, seperti emas, perubahan harga dan harga minyak mentah, dan juga berasal dari pasar nilai tukar. Penelitian ini akan menguji pengaruh perubahan harga emas, perak, minyak mentah, dan nilai tukar terhadap return saham perusahaan sektor pertambangan di Indonesia. Ada 48 perusahaan yang bergerak di sektor pertambangan yang terdaftar di Bursa Efek Indonesia (BEI). Dari 48 perusahaan penelitian ini menggunakan metode purposive sampling untuk memilih sampel dalam kriteria, dan ada 13 perusahaan yang dipilih yang akan menjadi objek penelitian ini. Penelitian ini juga menggunakan alat analisis GARCH (1.1) untuk menghindari data abnormal. Sebelum maju ke analisis GARCH (1.1), data harus diuji stasioner terlebih dahulu dengan menggunakan Augmented Dickey-Fuller Test (ADF) untuk memastikan data stasioner atau tidak dengan menggunakan level, perbedaan 1, dan dua perbedaan. Hasil penelitian menunjukkan bahwa emas memiliki pengaruh positif signifikan terhadap return saham perusahaan sektor pertambangan seperti INCO, KKGI, PTBA, dan TINS. Perak memiliki efek positif signifikan pada perusahaan HRUM dan negatif pada RUIS. Minyak mentah memiliki efek positif yang signifikan pada perusahaan HRUM dan PTBA. Nilai tukar memiliki dampak negatif yang signifikan terhadap perusahaan. ANTM,

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“…The fluctuations or movements in the stock prices can occur due to many factors, such as commodity prices. Arfaoui and Ben Rejeb (2017) found that the world oil price movement has a significant effect on the stock price, this finding also supported by Hersugondo, Robiyanto, Wahyudi, and Muharam (2015); Robiyanto (2018), while Putra and Robiyanto (2019) found that the precious metal prices can affect the mining stock price. This could happen because these commodities prices can affect the profitability level.…”

The Mediating Role of Debt and Dividend Policy on the Effect Profitability Toward Stock Price

“…The fluctuations or movements in the stock prices can occur due to many factors, such as commodity prices. Arfaoui and Ben Rejeb (2017) found that the world oil price movement has a significant effect on the stock price, this finding also supported by Hersugondo, Robiyanto, Wahyudi, and Muharam (2015); Robiyanto (2018), while Putra and Robiyanto (2019) found that the precious metal prices can affect the mining stock price. This could happen because these commodities prices can affect the profitability level.…”

Determinant of Indonesian Stock Market’s Volatility During the Covid-19 Pandemic

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“…Thus, due to the ARCH model"s shortcoming, Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH) model was advanced by Bollerslev (1986) in order to catch more long lagged effects with less parameters and the conditional variance. Moreover, GARCH model can be used for a research which has data abnormalities and heteroscedasticity issue (Putra & Robiyanto, 2019).…”