Panel Data Regression Analysis Approach: Predict the Effect of Operating Cash Flows and Net Profit on Stock Returns

Sella Marselia; Deri Firmansyah

doi:10.59653/ijmars.v3i03.1951

Authors

Sella Marselia Department of Accounting STIE Pasim Sukabumi, Indonesia
Deri Firmansyah Department of Management STIE Pasim Sukabumi, Indonesia

DOI:

https://doi.org/10.59653/ijmars.v3i03.1951

Keywords:

Operating cash flow, net profit, stock returns, panel data regression models, CEM

Abstract

This study aims to explore the predictive relationship between operating cash flows (OCF) and Net Profit (NP) with stock returns (SR). Quantitative research design adopts the ex-post facto model. Secondary data is used as the main source of data obtained from financial statements from four manufacturing companies from food and beverages listed in the Indonesia Stock Exchange (IDX) for the 2016-2023 period, analyzed in 32 quarters of the financial statements chosen with purposive sample techniques. Data analysis from the panel data regression model approach was adopted, which is estimated to use EViews v.12. Research findings, the Common Effects Model (CEM) approach was chosen as the best data panel regression model through the Chow test, Hausman test, and LM test. The findings conclude that OCF has no positive effect on SR. NP does not have a significant positive effect on SR. This finding also confirmed that OCF and NP simultaneously do not have a significant positive effect on SR. This illustrates the variant of the relationship between OCF and NP simultaneously has a low prediction power in explaining the total SR variant. This finding can fill the existing gap, and practically the relevant data panel regression model is used to predict the return of cash flow-based shares from business operations and periodic income in several companies. But the findings of this research emphasize that many other financial performance measures are more dominant than OCF and NP, as a determinant of SR in the capital market.

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