Evaluasi Emiten Indeks MNC 36 dengan Klasterisasi Rasio Keuangan dan Peramalan Time Series: Studi pada Saham PT Indofood CBP Sukses Makmur Tbk
DOI:
https://doi.org/10.51278/bce.v4i3.1605Keywords:
Fundamental Analysis, Technical Analysis, Time Series Analysis, ICBP stockAbstract
Stocks are a popular investment instrument among the public due to their high return potential. To aid investors in selecting suitable stocks, various stock indices serve as benchmarks to assess stock performance. One notable index for its solid performance is the MNC 36 index, which comprises 36 selected stocks on the Indonesia Stock Exchange (IDX). This study builds upon prior research by focusing on fundamental and technical analyses of companies in the MNC 36 index. Fundamental analysis calculates financial ratios including the current ratio, quick ratio, cash ratio, ROA, and ROE, while technical analysis uses time series methods such as moving average, exponential smoothing, and ECM to identify the best forecasting model. The analysis process begins with assessing risk and return, followed by clustering companies through random sampling. From the three clusters formed, one with the best financial ratios is selected, with the top-performing company in this cluster undergoing further analysis. Fundamental analysis results indicate minimal variation in ROA and ROE ratios among MNC 36 companies, with ICBP identified as the top stock in the selected cluster. Technical analysis, using single exponential smoothing with an alpha of 0.7, is the most accurate for forecasting ICBP’s stock price, yielding the lowest MAPE, MAD, and MSD values. Additionally, ECM analysis reveals both short-term and long-term relationships between ICBP’s stock price and external variables such as the dollar index, trade balance, and U.S. wheat prices, supported by IIDN tests meeting criteria for normality, identity, and independence.
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Copyright (c) 2024 Azzam Pahlawan Ramadhan, Oktaviana Nur Rohmatulillah, Faniya Mahesty Septiadi, Syefa Ilmi Beandita Putri, Aditya Adinata, Trian Servica, Alyaa Nidya Shadrina Anwar, Siti Nabila, Fausania Hibatullah
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