Articles

Impact of Fama and French Six Factor Model on Indonesian Healthcare Stock Returns

/in /by

The Fama and French Six Factor Model (FF6FM) is an extension of the Fama and French Five Factor Model (FF5FM). The purpose of this study was to examine the Fama and French Six Factor Model’s ability to explain the excess returns of healthcare sector companies listed on the Indonesia Stock Exchange (BEI). The Fama and French Six Factor Model consists of six factors: Market Excess Return (MKT), Size Factor (SMB), Book to Market Ratio (HML), Profitability (RMW), Investment (CMA), and Momentum (UMD). This study employed a purposive sampling method to get a sample of 18 healthcare sector companies listed on the Indonesia Stock Exchange (BEI) during the Covid-19 epidemic, specifically from March 2020 to June 2023. The data is derived from secondary sources and is of a quantitative nature. This study uses a panel data regression analysis model as its primary analytical technique. The findings indicate that Momentum (UMD), Market Excess Return (MKT), Size Factor (SMB), and Investment (CMA) have a statistically significant positive impact on excess returns. Among these variables, Momentum (UMD) has the most influence on excess returns. However, it has been observed that the Book to Market Ratio (HML) and Profitability (RMW) do not exhibit a positive and statistically significant impact on excess returns. Nevertheless, according to the adjusted r-square results, the Fama and French six factor models demonstrate a lower capacity to elucidate the additional returns observed in healthcare sector stocks during the period spanning from March 2020 to June 2023.

An Exploratory Data Analysis (EDA) Approach for Analyzing Financial Statements in Pharmaceutical Companies Using Machine Learning

/in /by

This research investigates the use of Exploratory Data Analysis (EDA) and machine learning techniques to analyze financial statements (FSs) of pharmaceutical companies. The study focuses on three major Indonesian pharmaceutical companies: Kimia Farma, Kalbe Farma, and IndoFarma. By leveraging EDA, this study aims to uncover hidden patterns and insights within financial data, such as earnings per share (EPS), return on capital employed (ROCE), net profit margin, and inventory turnover ratio. Additionally, the study employs machine learning models, including Linear Regression, K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Decision Tree, to predict financial performance metrics and trends. The performance of these models is evaluated using metrics such as Root Mean Squared Error (RMSE), Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). Among the models tested, the Decision Tree model demonstrated the highest performance, indicating high accuracy and a strong fit to the data. These results highlight the potential of data-driven approaches in improving the operational efficiency and financial stability of healthcare organizations.

Do Firms Change the Working Capital Management Policy During The Covid-19 Pandemic? Case of Transportation & Logistics and Healthcare Industries in Indonesia

/in /by

This study explores the crucial role of working capital management in balancing profitability and risk for companies. Economic conditions and sector-specific fluctuations in GDP influence working capital decisions. The transportation and logistics industry faced challenges with reduced demand, while the healthcare industry dealt with increased demand and longer payment collection periods during the pandemic. Using panel data regression on healthcare and transportation companies listed on the Indonesia Stock Exchange from 2017 to 2021, the study examines the impact of working capital management on profitability. Findings show significant correlations between working capital components and company profitability in both sectors. Specifically, before the pandemic, Days Sales Outstanding (DSO) positively affected Return on Assets (ROA), while Working Capital Financing Policy (WCFP) had a negative impact. During the pandemic, DSO and Working Capital Investment Policy (WCIP) positively influenced ROA in the transportation sector, while WCFP negatively affected it. In the healthcare sector during the pandemic, both DSO and Days Inventory Outstanding (DIO) positively affected ROA. For Net Profit Margin (NPM), the significance of working capital variables changed during the pandemic in the transportation sector, with DSO negatively impacting NPM, while WCIP and WCFP had a positive effect. In the healthcare sector during the pandemic, WCIP positively correlated with NPM, while WCFP had a negative correlation. Effective working capital management is essential for companies to navigate economic fluctuations and ensure uninterrupted operations.