The Implementation of Roy's Safety-First Criterion in Stock Portfolio Selection

  • Amal M
  • Laksito G
  • Sulaiman I
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Abstract

Statistical data shows that the Indonesian capital market has experienced significant growth. This growth is attributed to public awareness of the benefits of stock investments. However, with an increasing number of new investors entering the stock market, attention to investment risks deepens. Many investors prefer stocks that are easily predictable and have low risk, as higher volatility increases the level of uncertainty in obtaining returns. The relatively high risk level in investing requires investors to minimize risks, one of which is by diversifying funds into various investment assets, commonly known as optimal portfolio selection. An optimal portfolio can be formed using various methods and approaches. One method for portfolio selection is the application of the Safety First Criterion, a method dependent on downside risk, referring to risks that result in losses. This article conducts a simulation of the implementation of Roy's Safety First Criterion using stock data from the largest companies in eleven sectors over the past year. These sectors include basic materials, communication services, consumer cyclical, consumer defensive, energy, financial services, healthcare, real estate, technology, and utilities. Based on this analysis, out of the eleven stocks, six stocks meet Roy's criteria: LIN, GOOG, AMZN, BRK-B, LLY, and AAPL, with respective weights of LIN=10.84%, GOOG=12.61%, AMZN=24.67%, BRK-B=1.37%, LLY=34.17%, and AAPL=16.35%. Using Roy's Safety First Criterion for selected stocks from various sectors indicates that the resulting portfolio has a very low risk level, specifically 1%. This means that by using the portfolio obtained from the eleven stocks, investors can achieve minimal risk, making this portfolio secure for new investors.

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APA

Amal, Moh. A., Laksito, G. S., & Sulaiman, I. M. (2024). The Implementation of Roy’s Safety-First Criterion in Stock Portfolio Selection. International Journal of Mathematics, Statistics, and Computing, 2(1), 1–8. https://doi.org/10.46336/ijmsc.v2i1.64

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