Amraini Amraini, Muchriana Muchran, Mira Mira

Optimizing invesment decisions: A comparative analysis of fundamental and technical approaches

Introduction

Optimizing invesment decisions: a comparative analysis of fundamental and technical approaches. Optimize stock investment decisions. This study compares technical vs. fundamental analysis. Technical yields higher profit/accuracy (92%), but combined reduces risk. Guides investor strategy.

Abstract

This study discusses the comparison between using technical analysis independently and combining fundamental analysis with technical analysis in optimizing stock investment decision-making. The data used is secondary data from LQ45 stocks during the period of February to July 2024. Technical analysis in this study uses the Stochastic RSI indicator, while fundamental analysis refers to the Price to Book Value (PBV) ratio. The results show using technical analysis has an accuracy rate of 92% with a profit of 16.224, which is higher than the combination of both analyses which recorded an accuracy of 87% and a profit of 5.999. Nevertheless, the combined strategy is proven to be more effective in reducing investment risk, making it still relevant for investors who focus on long-term security. This study is important because in investment practice, market participants often face confusion in choosing the most suitable analytical approach. By empirically comparing the two strategies, and this study provides insights that can help investors adjust their strategies based on their goals, risk tolerance, and investment horizon, so that the decisions made are more targeted and measurable.

Review

This study addresses a highly relevant and practical question for market participants: how to optimally combine or choose between fundamental and technical analysis for investment decisions. By specifically comparing an independent technical analysis strategy (using the Stochastic RSI indicator) against a combined approach (Stochastic RSI with the Price to Book Value ratio) within the LQ45 stock universe, the research aims to provide empirical guidance. The abstract clearly articulates the study's objective to alleviate investor confusion regarding analytical methodologies, making its contribution potentially valuable for practitioners seeking to align their strategies with their risk tolerance and investment horizons. The core findings indicate that technical analysis independently yielded a higher accuracy rate (92%) and significantly greater profit (16.224) compared to the combined strategy (87% accuracy, 5.999 profit). However, the combined approach is posited as more effective in reducing investment risk and being relevant for long-term security. A significant methodological concern arises from the stated data period, "February to July 2024." As this period extends into the future, it strongly suggests a potential error in the abstract, or it implies a simulation rather than an analysis of secondary historical data as claimed. If the latter, this needs explicit clarification and detailed methodology for the simulation. Furthermore, a six-month period is exceedingly short for any robust investment analysis, especially when claiming insights into "long-term security," and the units or scale of the reported "profit" figures (16.224 and 5.999) are not defined, making their absolute meaning unclear. While the study addresses a critical gap in investment practice by offering a direct empirical comparison, the reliability and generalizability of its conclusions are significantly hampered by the methodological ambiguities. The claim of analyzing "secondary data from LQ45 stocks during the period of February to July 2024" needs immediate clarification, as does the precise nature and currency of the "profit" metric. To enhance the study's impact and credibility, future revisions should provide a clear justification for the chosen indicators, ideally extend the data analysis period significantly to support claims about long-term effectiveness, and precisely define all quantitative outcomes. Addressing these points would transform a potentially insightful initial exploration into a more robust and publishable contribution to investment literature.

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