The Effect of Commodity Prices and Exchange Rate on the Stock Return of Agriculture and Animal Feed Companies in Indonesia

Author:

Oktrevina Oktrevina1ORCID,Kurniawan Yohannes2,Anwar Norizan3ORCID

Affiliation:

1. School of Accounting, Bina Nusantara University, Jakarta, Indonesia

2. School of Information Systems, Bina Nusantara University, Jakarta, Indonesia

3. Faculty of Information Management, Universiti Teknologi Mara, UiTM, Puncak Perdana Campus, 40150, Shah Alam, Selangor, Malaysia

Abstract

Purpose of the study: This study aims to examine the key drivers for the effect of selected commodity ratios and the exchange rate that haveinfluenced the return on investment of agriculture and animal feed companies in Indonesia. Methodology: This study uses the GARCH methodology. Using GARCH and IGARCH for monthly and daily data from 2014 until 2021, we also have a different timeline between before COVID and after COVID-19. Main Findings: According to the results of the study, there are generally significant effects of commodity prices and exchange rates on stock return, as for the COVID timeline, there are several companies that have been affected. Research limitation: There is a problem with finding the parameter estimates for the error distribution both in GED and Student’s t when finding the best GARCH (1,1) model. The best model finding may not present the best probability due to distributions that affect the tail distribution. Novelty/Originality of the study: This study suggests to look for more details on the effect of commodity ratio in daily data and monthly data, as thetransaction is mostly using USD rate with IDR rate. There are great possibilities that their movement will impact the return on the investment and people who like to invest in a certain company can use this study as a reference.

Publisher

International Collaboration for Research and Publications

Subject

General Medicine

Reference57 articles.

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3. Albulescu, C. (2020). COVID-19 and the United States financial markets’ volatility. Finance Research Letters, 38:101699.

4. Almeida, R. J., Basturk, N., Kaymak, U., & Sousa, J. M. (2014). Estimation of flexible fuzzy garch models for conditional density estimation. Information Sciences, 267 (p):252-264.

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