Piko Hamudin, Irni Yunita

Optimization of Stock Portfolio Investment on the IDXHIDIV20 Index Using the Single Index Model and Markowitz Model Approach for Beginner Investors

Introduction

Optimization of stock portfolio investment on the idxhidiv20 index using the single index model and markowitz model approach for beginner investors. Optimize IDXHIDIV20 stock portfolios for beginners using SIM & Markowitz Models. Markowitz outperforms SIM (23.56% return, 2.81% risk). Make informed investment decisions.

Abstract

Purpose - This study investigates the construction of optimal stock portfolios using the Single Index Model (SIM) and the Markowitz Mean-Variance Model (MM), applied to the IDX High Dividend 20 (IDXHIDIV20) index. With a growing number of novice investors in Indonesia, understanding which classical model offers better guidance for dividend-oriented investing is increasingly essential. Design/methodology/approach - A descriptive quantitative approach was used, employing weekly secondary data of 20 IDXHIDIV20 constituents from 2019 to 2024. The SIM was applied through regression-based estimations and excess return-to-beta ranking, while the Markowitz Model utilized a full variance-covariance matrix with Excel Solver optimization. Originality - This research contributes empirical evidence to modern portfolio theory by comparing the effectiveness of SIM and MM in the context of novice investors in emerging markets. It also incorporates the relevance of sustainability factors through dividend strategies. Findings and Discussion - The Markowitz portfolio consistently outperforms the SIM portfolio in both return and risk dimensions, achieving an expected annual return of 23.56% with a standard deviation of 2.81%, compared to SIM's 22.96% return with 5.89% volatility. While the SIM offers practical simplicity for novice investors, the MM provides superior diversification through covariance-based optimization. These findings validate the importance of robust model selection in portfolio strategy. Conclusion - The Markowitz Model is preferable for investors with access to analytical tools and data due to its superior risk-return performance, while SIM remains a valuable approach for those with limited resources. The study enhances financial education and supports informed investment decisions for dividend-focused strategies in emerging markets.

Review

This study offers a timely and relevant comparison of the Single Index Model (SIM) and Markowitz Mean-Variance Model (MM) for constructing optimal stock portfolios, specifically targeting novice investors in Indonesia's IDXHIDIV20 index. The research diligently employs a descriptive quantitative approach, analyzing weekly data from 2019-2024 for 20 constituent stocks. A key strength lies in its empirical validation, demonstrating that the Markowitz model consistently outperforms the SIM in both return and risk dimensions, achieving a superior risk-adjusted return (23.56% return with 2.81% standard deviation) compared to SIM (22.96% return with 5.89% volatility). This finding provides crucial guidance for dividend-oriented investment strategies within an emerging market context, highlighting the tangible benefits of sophisticated diversification. While the study's core comparison is robust, some aspects could be further elaborated. The abstract mentions the "relevance of sustainability factors through dividend strategies" in the originality section, yet the findings and discussion do not explicitly detail how this connection is established or measured beyond simply using a dividend-focused index. A deeper dive into how dividend policies intrinsically link to sustainability, or how investors might interpret this, would enrich this claim. Furthermore, while the study targets "novice investors," the practical implications for truly novice individuals—who might lack access to or understanding of "analytical tools and data" beyond basic spreadsheets—could be explored in more detail. The conclusion acknowledges this by differentiating between investors with and without such access, but the practical bridging of this gap remains a challenge for application. Overall, this research makes a valuable contribution to both financial education and portfolio theory, particularly within the context of growing retail investor participation in emerging markets. It underscores the importance of robust model selection and the benefits of advanced diversification techniques for optimizing investment outcomes. The findings are directly applicable to practitioners and academics seeking to understand the efficacy of classical portfolio models in a modern, dividend-focused investment landscape. Future research could extend this work by incorporating behavioral finance aspects relevant to novice investors, exploring the computational burden of these models for those with limited resources, or investigating the performance of these portfolios under varying market conditions and economic cycles.

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