Stock Portfolio Analysis Using the Capital Asset Pricing Model (CAPM) on Companies in the IDX30 Index
This study aims to provide guidance to investors in identifying efficient and inefficient stocks, as well as evaluating stocks that have an optimal balance between return and risk using the Capital Asset Pricing Model (CAPM). The CAPM method is used to predict the return of risky securities and as...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas KH Abdul Chalim, Prodi Ekonomi Syariah
2025-01-01
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| Series: | Indonesian Interdisciplinary Journal of Sharia Economics |
| Subjects: | |
| Online Access: | https://e-journal.uac.ac.id/index.php/iijse/article/view/5842 |
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| Summary: | This study aims to provide guidance to investors in identifying efficient and inefficient stocks, as well as evaluating stocks that have an optimal balance between return and risk using the Capital Asset Pricing Model (CAPM). The CAPM method is used to predict the return of risky securities and as a benchmark in assessing the level of investment returns. By implementing CAPM, investors can make more informed and strategic investment decisions in portfolio management. This study uses a purposive sampling technique to select samples, where the specific criteria are companies listed on the Indonesia Stock Exchange and consistently included in the IDX30 stock index in the 2020-2023 period. Selection is made based on stock efficiency, where individual returns are greater than expected returns (Ri>ERi). There is a linear relationship between systematic risk and expected returns, where stocks that have a high beta value, the expected return will also be high, and vice versa. Of the 16 stocks analyzed, 7 company stocks are included in the efficient stock category, namely ADRO, ANTM, BBCA, BBNI, BBRI, BMRI, and UNTR, while the other 9 stocks are included in the inefficient category. The results of this study are expected to provide insight to investors in selecting efficient stocks for optimal investment decision-making.
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| ISSN: | 2621-606X |