Abstract
The study aimed to investigate the financial performance with the proxy of economic value added and market value added in influencing the stock price of manufacturing companies from 2014 to 2023. The study used a quantitative approach method. The sampling technique used is a non-probability sampling technique with a sample of 41 companies. The study uses secondary data from company financial reports and other supporting data. The study tested regression data using panel data by conducting the estimation model testing stage for the common, fixed, and random effect models through the Chow and Hausman tests. The model used in this study is a random effect, which is included in the Generalized Least Square (GLS) method in the Eviews12 application. The research findings show that the economic and market value-added variables partially and simultaneously affected stock prices in manufacturing companies from 2014 to 2023.
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