Application of Support Vector Regression in Time Series Analysis of Dior Stock Prices - Sari, Adma Novita; Zuleika, Talitha; Mardianto, M. Fariz Fadillah; Pusporani, Elly (Zeta - Math Journal, 2025)
Christian Dior (Dior) is a multinational company focusing on luxury goods, including fashion products, cosmetics, and accessories. In 2020–2024, Dior's share price will experience significant fluctuations influenced by financial performance, global market trends, etc. These fluctuations require investors to implement appropriate strategies to minimize the risk of losses and support sustainable economic growth. This step aligns with goal 8 of the Sustainable Development Goals (SDGs), emphasizing the importance of sustainable economic growth through investment and infrastructure development for economic prosperity. One of the effective methods for modeling and predicting stock prices is Support Vector Regression (SVR). By applying SVR using the Radial Basis Function (RBF) kernel, this study shows that the model can generate predictions with a MAPE value of 2.5864% on the test data. The SVR method is expected to provide accurate predictions, making it a helpful tool for investors and market analysts to make better investment decisions.