CONSTRUCTING AN OPTIMAL PORTFOLIO USING CLUSTERING LARGE APPLICATION AND VALUE AT RISK ANALYSIS FOR IDX80 STOCKS - Sania Pujianti; Hendra Perdana; Neva Satyahadewi (PATTIMURA UNIVERSITY, 2026)
Investment is a way to manage wealth and achieve financial goals in the future. Stocks are an attractive investment instrument due to their high potential returns, although they also carry significant risks. These risks can be minimized through portfolio diversification. Diversification is carried out by selecting representative stocks from the clustering results. This study aims to construct an optimal portfolio using the Clustering Large Application (CLARA) method and conduct portfolio risk analysis using Value at Risk (VaR). The data used includes IDX80 stock closing prices from November 1, 2024, to January 31, 2025, the financial ratios of IDX80 stocks on December 2024, and the Bank Indonesia (BI-Rate) interest rate from November 2024 to January 2025. The CLARA method produces four stock clusters with a silhouette coefficient of 0.18226. This value indicates a low level of separation between clusters, as there might be overlapping features among the clusters. Representative stocks from each cluster are selected based on the highest Sharpe ratio: SCMA, JPFA, GOTO, and BRIS. The portfolio weights based on MVEP are 15.002% (SCMA), 29.786% (JPFA), 1.858% (GOTO), and 53.354% (BRIS). The VaR calculation shows a potential maximum loss of Rp137,139 in one day, with a 99% confidence level, from an initial investment of Rp10,000,000.