Ignatius Roni Setyawan
Master of Management Program, Universitas Tarumanagara, Jakarta, Indonesia

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ANALYSIS OF THE CAPITAL ASSET PRICING MODEL (CAPM) AND THE FAMA FRENCH THREE-FACTOR MODEL (FF3) IN ESTIMATING STOCK RETURNS (A STUDY OF COMPANIES LISTED ON THE IDX30 INDEX FOR THE 2021–2024 PERIOD) Jessica Jessica; Ignatius Roni Setyawan
International Journal of Application on Economics and Business Vol. 3 No. 4 (2025): November 2025
Publisher : Graduate Program of Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/ijaeb.v3i4.2085-2095

Abstract

This study aimed to analyse and compare the effectiveness of the Capital Asset Pricing Model (CAPM) and the Fama-French Three-Factor Model (FF3) in estimating the returns of companies listed on the IDX30 index for the period 2021 to 2024. This study was based on the increasing number of investors in the Indonesian capital market, which raises questions regarding the relevance of conventional asset valuation models in an ever-changing market structure. This study used panel data from 13 IDX30 companies selected through purposive sampling. The secondary data used included monthly stock prices, the IHSG index, the benchmark interest rate (BI Rate), market capitalization, and the book-to-market ratio. The CAPM model considers only systematic risk (beta), while the FF3 model incorporates two additional risk factors: the size premium (SMB) and the value premium (HML). Data processing was conducted using Microsoft Excel and EViews 10. The results showed that the market risk premium had a significant positive effect on stock returns. The SMB factor had a significant positive impact, suggesting that small-cap stocks typically generated higher returns. However, the HML factor did not have a significant effect, indicating that the value premium was less relevant in the IDX30 context. Generally, the FF3 model was superior to the CAPM in explaining stock return variation. These findings were expected to serve as a reference for investors, analysts, and regulators in evaluating stock performance and selecting more accurate investment models.