PEMODELAN RISIKO PASAR DAN NILAI TUKAR TERHADAP RETURN SAHAM SEKTORAL DI BURSA EFEK INDONESIA

Abstract

This study analyzes sectoral stock return risk in the Indonesia Stock Exchange using multiple linear regression and historical Value at Risk. Market risk is represented by the return of the Indonesia Composite Index, while exchange rate risk is represented by the return of USD/IDR. This study uses daily time series data obtained from Yahoo Finance using Python. Sectoral stock returns are constructed using a proxy approach by calculating the average return of selected representative stocks in each sector. The methods include return calculation, sectoral return construction, multicollinearity testing using Variance Inflation Factor, multiple linear regression estimated by Ordinary Least Squares with HC3 robust standard error, and risk measurement using volatility, Value at Risk, Conditional Value at Risk, maximum drawdown, and risk scoring. The results show that IHSG return significantly affects all sectoral stock returns, while USD/IDR return significantly affects the Properties and Technology sectors. The risk classification shows that Technology, Basic Materials, Transportation, and Properties are high-risk sectors, while Consumer Non-Cyclicals and Healthcare are low-risk sectors. These findings indicate that combining multiple linear regression and historical risk measurement can support sectoral risk mapping for investors and decision-makers.