Evaluasi Metodologi Baru dalam Pengambilan Keputusan Investasi

Ngadi Permana; Mohammad Chaidir

doi:10.61132/jubid.v1i1.421

Authors

Ngadi Permana Sekolah Tinggi Ilmu Ekonomi Kasih Bangsa
Mohammad Chaidir Sekolah Tinggi Ilmu Ekonomi Kasih Bangsa

DOI:

https://doi.org/10.61132/jubid.v1i1.421

Keywords:

Capital Asset Pricing Model, Investment Decision-Making, Market Index, Market Prediction, Regression Tree

Abstract

This study aims to evaluate the application of a new methodology in investment decision-making, specifically using the regression tree approach on stock market indices. This approach is expected to enhance prediction accuracy and assist investors in making more informed investment decisions, especially in volatile and uncertain markets. Based on the literature review, regression trees offer advantages in identifying non-linear relationships between market variables that are often undetected by traditional models such as the Capital Asset Pricing Model (CAPM). Despite its advantages, the application of regression trees also faces challenges, such as overfitting issues and the need for large and complex data. This study concludes that regression trees can improve investment decision-making, but careful attention is required regarding model tuning and data quality.

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