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Journal : International Journal of Mathematics, Statistics, and Computing

Application of the Compound Interest Model in Analyzing Long-Term Investments on Nvdia Company Stock Sanita, Indri; Ananta, Galen; Laksito, Grida Saktian
International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 1 (2024): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v2i1.62

Abstract

Long-term investment is a strategic decision that requires careful planning and in-depth analysis. One approach to analyze the potential returns from long-term investments is through the application of the compound interest model. This model considers the accumulation of interest on both the principal amount and the previously earned interest, providing a more realistic picture of investment growth over time.This research aims to explore how the application of the compound interest model can enhance the analysis of long-term investments. The analysis of these variables provides a comprehensive picture of the dynamics of investment growth and opens up opportunities for more informed investment decision-making. This research emphasizes the importance of a thorough understanding of the key variables in the compound interest model to enhance the accuracy of investment decisions.The findings of this research are expected to offer practical guidance for investors and financial practitioners in managing their portfolios more intelligently and measurably. These findings make a significant contribution to the development of more effective long-term investment strategies, thereby enhancing portfolio performance and overall investment outcomes.
The Implementation of Roy's Safety-First Criterion in Stock Portfolio Selection Amal, Moh. Alfi; Laksito, Grida Saktian; Salih, Yasir
International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 1 (2024): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v2i1.64

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.