The Accuration of Expected Return Prediction of Pharmaceutical Sub-Sector Companies during COVID-19 Pandemic
Keywords:Expected Return; Asset Pricing Model; The Accuracy of Expected Return Prediction; Mean Average Deviation. Multifactor Model
This study aims to analyze the expected return of stocks in the pharmaceutical sub-sector based on the capital asset pricing model (CAPM), arbitrage pricing theory (APT), and the Three Factor Model (TFM) during the COVID-19 pandemic from March 2020 to December 2023, and test the accuracy of the expected return prediction using the Mean Average Deviation (MAD). Determination of the pharmaceutical sub-sector as a research sample with the consideration of producing positive return growth during the COVID-19 pandemic, while at the same time, other companies were experiencing a downturn. The results showed that the average expected return was 3.69% based on the CAPM, 3.88% based on the APT formula, and 3.66% based on TFM calculations. However, there is no significant difference in the resulting expected return. The regression analysis concludes TFM is better than other asset pricing models. Beta significantly explains the average weekly pharmaceutical stock return. The measure of the MAD test concluded the CAPM is a model that can predict the expected return more accurately by the smallest MAD value. TFM is a model with the highest MAD value. The highest level of MAD, the less accurate prediction of the expected return.